Super B-Malware
Mario I-Malware
Run I-Malware
Malware I-Malware
# O
2 O
– O
DroidJack B-Malware
RAT I-Malware
Gamers O
love O
Mario B-System
and O
Pokemon B-System
, O
but O
so O
do O
malware O
authors O
. O
A O
few O
days O
back O
, O
we O
wrote O
about O
an O
Android B-System
Marcher B-Malware
trojan O
variant O
posing O
as O
the O
Super B-System
Mario I-System
Run I-System
game O
for O
Android B-System
. O
We O
have O
found O
another O
instance O
of O
malware O
posing O
as O
the O
Super B-System
Mario I-System
Run I-System
Android B-System
app O
, O
and O
this O
time O
it O
has O
taken O
the O
form O
of O
DroidJack B-Malware
RAT I-Malware
( O
remote O
access O
trojan O
) O
. O
Proofpoint B-Organization
wrote O
about O
the O
DroidJack B-Malware
RAT I-Malware
side-loaded O
with O
the O
Pokemon B-System
GO I-System
app O
back O
in O
July O
2016 O
; O
the O
difference O
here O
is O
that O
there O
is O
no O
game O
included O
in O
the O
malicious O
package O
. O
The O
authors O
are O
trying O
to O
latch O
onto O
the O
popularity O
of O
the O
Super B-System
Mario I-System
Run I-System
game O
to O
target O
eagerly O
waiting O
Android B-System
users O
. O
Details O
: O
Name O
: O
Super B-System
Mario I-System
Run I-System
Package O
Name O
: O
net.droidjack.server B-Indicator
MD5 O
: O
69b4b32e4636f1981841cbbe3b927560 B-Indicator
Technical O
Analysis O
: O
The O
malicious O
package O
claims O
to O
be O
the O
Super B-System
Mario I-System
Run I-System
game O
, O
as O
shown O
in O
the O
permissions O
screenshot O
below O
, O
but O
in O
reality O
this O
is O
a O
malicious O
RAT O
called O
DroidJack B-Malware
( O
also O
known O
as O
SandroRAT B-Malware
) O
that O
is O
getting O
installed O
. O
Once O
installed O
, O
the O
RAT O
registers O
the O
infected O
device O
as O
shown O
below O
. O
DroidJack B-Malware
RAT I-Malware
starts O
capturing O
sensitive O
information O
like O
call O
data O
, O
SMS O
data O
, O
videos O
, O
photos O
, O
etc O
. O
Observe O
below O
the O
code O
routine O
for O
call O
recording O
. O
This O
RAT O
records O
all O
the O
calls O
and O
stores O
the O
recording O
to O
an O
“ O
.amr B-Indicator
” O
file O
. O
The O
following O
is O
the O
code O
routine O
for O
video O
capturing O
. O
Here O
, O
the O
RAT O
stores O
all O
the O
captured O
videos O
in O
a O
“ O
video.3gp B-Indicator
” O
file O
. O
It O
also O
harvests O
call O
details O
and O
SMS O
logs O
as O
shown O
below O
. O
Upon O
further O
inspection O
, O
we O
have O
observed O
that O
this O
RAT O
extracts O
WhatsApp B-System
data O
too O
. O
The O
RAT O
stores O
all O
the O
data O
in O
a O
database O
( O
DB O
) O
in O
order O
to O
send O
it O
to O
the O
Command O
& O
Control O
( O
C O
& O
C O
) O
server O
. O
The O
following O
are O
the O
DBs O
created O
and O
maintained O
by O
the O
RAT O
. O
We O
saw O
the O
following O
hardcoded O
C O
& O
C O
server O
location O
in O
the O
RAT O
package O
: O
Conclusion O
: O
The O
DroidJack B-Malware
RAT I-Malware
is O
another O
example O
of O
a O
growing O
trend O
in O
which O
malware O
authors O
seek O
to O
exploit O
public O
interest O
as O
a O
way O
to O
spread O
malware O
. O
In O
this O
case O
, O
like O
others O
before O
, O
the O
event O
of O
a O
popular O
game O
release O
became O
an O
opportunity O
to O
trick O
unsuspecting O
users O
into O
downloading O
the O
RAT O
. O
As O
a O
reminder O
, O
it O
is O
always O
a O
good O
practice O
to O
download O
apps O
only O
from O
trusted O
app O
stores O
such O
as O
Google B-System
Play I-System
. O
This O
practice O
can O
be O
enforced O
by O
unchecking O
the O
" O
Unknown O
Sources O
'' O
option O
under O
the O
" O
Security O
'' O
settings O
of O
your O
device O
. O
XLoader B-Malware
Disguises O
as O
Android B-System
Apps O
, O
Has O
FakeSpy B-Malware
Links O
This O
new O
XLoader B-Malware
variant O
poses O
as O
a O
security O
app O
for O
Android B-System
devices O
, O
and O
uses O
a O
malicious O
iOS B-System
profile O
to O
affect O
iPhone B-System
and O
iPad B-System
devices O
. O
By O
: O
Hara O
Hiroaki O
, O
Lilang O
Wu O
, O
Lorin O
Wu O
April O
02 O
, O
2019 O
In O
previous O
attacks O
, O
XLoader B-Malware
posed O
as O
Facebook B-System
, O
Chrome B-System
and O
other O
legitimate O
applications O
to O
trick O
users O
into O
downloading O
its O
malicious O
app O
. O
Trend B-Organization
Micro I-Organization
researchers O
found O
a O
new O
variant O
that O
uses O
a O
different O
way O
to O
lure O
users O
. O
This O
new O
XLoader B-Malware
variant O
poses O
as O
a O
security O
app O
for O
Android B-System
devices O
, O
and O
uses O
a O
malicious O
iOS B-System
profile O
to O
affect O
iPhone B-System
and O
iPad B-System
devices O
. O
Aside O
from O
a O
change O
in O
its O
deployment O
techniques O
, O
a O
few O
changes O
in O
its O
code O
set O
it O
apart O
from O
its O
previous O
versions O
. O
This O
newest O
variant O
has O
been O
labeled O
XLoader B-Malware
version O
6.0 O
( O
detected O
as O
AndroidOS_XLoader.HRXD B-Indicator
) O
, O
following O
the O
last O
version O
discussed O
in O
a O
previous O
research O
on O
the O
malware O
family O
. O
Infection O
chain O
The O
threat O
actors O
behind O
this O
version O
used O
several O
fake O
websites O
as O
their O
host O
— O
copying O
that O
of O
a O
Japanese O
mobile O
phone O
operator O
’ O
s O
website O
in O
particular O
— O
to O
trick O
users O
into O
downloading O
the O
fake O
security O
Android B-System
application O
package O
( O
APK O
) O
. O
Monitoring O
efforts O
on O
this O
new O
variant O
revealed O
that O
the O
malicious O
websites O
are O
spread O
through O
smishing O
. O
The O
infection O
has O
not O
spread O
very O
widely O
at O
the O
time O
of O
writing O
, O
but O
we O
’ O
ve O
seen O
that O
many O
users O
have O
already O
received O
its O
SMS O
content O
. O
In O
the O
past O
, O
XLoader B-Malware
showed O
the O
ability O
to O
mine O
cryptocurrency O
on O
PCs O
and O
perform O
account O
phishing O
on O
iOS B-System
devices O
. O
This O
new O
wave O
also O
presents O
unique O
attack O
vectors O
based O
on O
the O
kind O
of O
device O
it O
has O
accessed O
. O
In O
the O
case O
of O
Android B-System
devices O
, O
accessing O
the O
malicious O
website O
or O
pressing O
any O
of O
the O
buttons O
will O
prompt O
the O
download O
of O
the O
APK O
. O
However O
, O
successfully O
installing O
this O
malicious O
APK O
requires O
that O
the O
user O
has O
allowed O
the O
installation O
of O
such O
apps O
as O
controlled O
in O
the O
Unknown O
Sources O
settings O
. O
If O
users O
allow O
such O
apps O
to O
be O
installed O
, O
then O
it O
can O
be O
actively O
installed O
on O
the O
victim O
’ O
s O
device O
. O
The O
infection O
chain O
is O
slightly O
more O
roundabout O
in O
the O
case O
of O
Apple B-System
devices O
. O
Accessing O
the O
same O
malicious O
site O
would O
redirect O
its O
user O
to O
another O
malicious O
website O
( O
hxxp B-Indicator
: I-Indicator
//apple-icloud I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
qwq-japan I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
or O
hxxp B-Indicator
: I-Indicator
//apple-icloud I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
zqo-japan I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
) O
that O
prompts O
the O
user O
to O
install O
a O
malicious O
iOS B-System
configuration O
profile O
to O
solve O
a O
network O
issue O
preventing O
the O
site O
to O
load O
. O
If O
the O
user O
installs O
the O
profile O
, O
the O
malicious O
website O
will O
open O
, O
revealing O
it O
to O
be O
an O
Apple B-Organization
phishing O
site O
, O
as O
seen O
in O
figure O
2 O
. O
Technical O
analysis O
Most O
of O
this O
new O
attack O
’ O
s O
routines O
are O
similar O
to O
those O
of O
the O
previous O
XLoader B-Malware
versions O
. O
However O
, O
as O
mentioned O
earlier O
, O
an O
analysis O
of O
this O
new O
variant O
showed O
some O
changes O
in O
its O
code O
in O
line O
with O
its O
new O
deployment O
method O
. O
We O
discuss O
these O
changes O
and O
its O
effect O
on O
Android B-System
and O
Apple B-System
devices O
. O
Malicious O
APK O
Like O
its O
previous O
versions O
, O
XLoader B-Malware
6.0 I-Malware
abuses O
social O
media O
user O
profiles O
to O
hide O
its O
real O
C O
& O
C O
addresses O
, O
but O
this O
time O
its O
threat O
actors O
chose O
the O
social O
media O
platform O
Twitter B-Organization
, O
which O
was O
never O
used O
in O
previous O
attacks O
. O
The O
real O
C O
& O
C O
address O
is O
encoded O
in O
the O
Twitter B-Organization
names O
, O
and O
can O
only O
be O
revealed O
once O
decoded O
. O
This O
adds O
an O
extra O
layer O
against O
detection O
. O
The O
code O
for O
this O
characteristic O
and O
the O
corresponding O
Twitter B-Organization
accounts O
can O
be O
seen O
in O
figures O
3 O
and O
4 O
respectively O
. O
Version O
6.0 O
also O
adds O
a O
command O
called O
“ O
getPhoneState O
” O
, O
which O
collects O
unique O
identifiers O
of O
mobile O
devices O
such O
as O
IMSI O
, O
ICCID O
, O
Android B-System
ID O
, O
and O
device O
serial O
number O
. O
This O
addition O
is O
seen O
in O
Figure O
5 O
. O
Considering O
the O
other O
malicious O
behaviors O
of O
XLoader B-Malware
, O
this O
added O
operation O
could O
be O
very O
dangerous O
as O
threat O
actors O
can O
use O
it O
to O
perform O
targeted O
attacks O
. O
Malicious O
iOS B-System
profile O
In O
the O
case O
of O
Apple B-System
devices O
, O
the O
downloaded O
malicious O
iOS B-System
profile O
gathers O
the O
following O
: O
Unique O
device O
identifier O
( O
UDID O
) O
International O
Mobile O
Equipment O
Identity O
( O
IMEI O
) O
Integrated O
Circuit O
Card O
ID O
( O
ICCID O
) O
Mobile O
equipment O
identifier O
( O
MEID O
) O
Version O
number O
Product O
number O
The O
profile O
installations O
differ O
depending O
on O
the O
iOS B-System
. O
For O
versions O
11.0 O
and O
11.4 O
, O
the O
installation O
is O
straightforward O
. O
If O
a O
user O
visits O
the O
profile O
host O
website O
and O
allows O
the O
installer O
to O
download O
, O
the O
iOS B-System
system O
will O
go O
directly O
to O
the O
“ O
Install O
Profile O
” O
page O
( O
which O
shows O
a O
verified O
safety O
certificate O
) O
, O
and O
then O
request O
the O
users O
’ O
passcode O
for O
the O
last O
step O
of O
installation O
. O
On O
later O
versions O
, O
specifically O
iOS B-System
12.1.1 I-System
and O
iOS B-System
12.2 I-System
, O
the O
process O
is O
different O
. O
After O
the O
profile O
is O
downloaded O
, O
the O
iOS B-System
system O
will O
first O
ask O
users O
to O
review O
the O
profile O
in O
their O
settings O
if O
they O
want O
to O
install O
it O
. O
Users O
can O
see O
a O
“ O
Profile O
Downloaded O
” O
added O
in O
their O
settings O
( O
this O
feature O
is O
in O
iOS B-System
12.2 I-System
, O
but O
not O
on O
iOS B-System
12.1.1 I-System
) O
. O
This O
gives O
users O
a O
chance O
to O
see O
details O
and O
better O
understand O
any O
changes O
made O
. O
After O
the O
review O
, O
the O
process O
is O
the O
same O
as O
above O
. O
After O
the O
profile O
is O
installed O
, O
the O
user O
will O
then O
be O
redirected O
to O
another O
Apple B-Organization
phishing O
site O
. O
The O
phishing O
site O
uses O
the O
gathered O
information O
as O
its O
GET O
parameter O
, O
allowing O
the O
attacker O
to O
access O
the O
stolen O
information O
. O
Ongoing O
activity O
While O
monitoring O
this O
particular O
threat O
, O
we O
found O
another O
XLoader B-Malware
variant O
posing O
as O
a O
pornography O
app O
aimed O
at O
South O
Korean O
users O
. O
The O
" O
porn O
kr O
sex O
'' O
APK O
connects O
to O
a O
malicious O
website O
that O
runs O
XLoader B-Malware
in O
the O
background O
. O
The O
website O
uses O
a O
different O
fixed O
twitter B-Organization
account O
( O
https B-Indicator
: I-Indicator
//twitter.com/fdgoer343 I-Indicator
) O
. O
This O
attack O
, O
however O
, O
seems O
exclusive O
to O
Android B-System
users O
, O
as O
it O
does O
not O
have O
the O
code O
to O
attack O
iOS B-System
devices O
. O
Succeeding O
monitoring O
efforts O
revealed O
a O
newer O
variant O
that O
exploits O
the O
social O
media O
platforms O
Instagram B-Organization
and O
Tumblr B-Organization
instead O
of O
Twitter B-Organization
to O
hide O
its O
C O
& O
C O
address O
. O
We O
labeled O
this O
new O
variant O
XLoader B-Malware
version O
7.0 O
, O
because O
of O
the O
different O
deployment O
method O
and O
its O
use O
of O
the O
native O
code O
to O
load O
the O
payload O
and O
hide O
in O
Instagram B-Organization
and O
Tumblr B-Organization
profiles O
. O
These O
more O
recent O
developments O
indicate O
that O
XLoader B-Malware
is O
still O
evolving O
. O
Adding O
connections O
to O
FakeSpy B-Malware
We O
have O
been O
seeing O
activity O
from O
XLoader B-Malware
since O
2018 O
, O
and O
have O
since O
followed O
up O
our O
initial O
findings O
with O
a O
detailed O
research O
revealing O
a O
wealth O
of O
activity O
dating O
back O
to O
as O
early O
as O
January O
2015 O
, O
which O
outlined O
a O
major O
discovery—its O
connection O
to O
FakeSpy B-Malware
. O
The O
emergence O
of O
XLoader B-Malware
6.0 I-Malware
does O
not O
only O
indicate O
that O
the O
threat O
actors O
behind O
it O
remain O
active O
; O
it O
also O
holds O
fresh O
evidence O
of O
its O
connection O
to O
FakeSpy B-Malware
. O
One O
such O
immediately O
apparent O
connection O
was O
the O
similar O
deployment O
technique O
used O
by O
both O
XLoader B-Malware
6.0 I-Malware
and O
FakeSpy B-Malware
. O
It O
had O
again O
cloned O
a O
different O
legitimate O
Japanese O
website O
to O
host O
its O
malicious O
app O
, O
similar O
to O
what O
FakeSpy B-Malware
had O
also O
done O
before O
. O
Their O
similarity O
is O
made O
more O
apparent O
by O
looking O
at O
their O
naming O
method O
for O
downloadable O
files O
, O
domain O
structure O
of O
fake O
websites O
and O
other O
details O
of O
their O
deployment O
techniques O
, O
exemplified O
in O
figure O
10 O
. O
XLoader B-Malware
6.0 I-Malware
also O
mirrors O
the O
way O
FakeSpy B-Malware
hides O
its O
real O
C O
& O
C O
server O
. O
When O
before O
it O
had O
used O
several O
different O
social O
media O
platforms O
, O
it O
now O
uses O
the O
Twitter B-Organization
platform O
, O
something O
FakeSpy B-Malware
has O
done O
in O
its O
past O
attacks O
. O
Analysis O
of O
the O
malicious O
iOS B-System
profile O
also O
revealed O
further O
connections O
, O
as O
the O
profile O
can O
also O
be O
downloaded O
from O
a O
website O
that O
FakeSpy B-Malware
deployed O
early O
this O
year O
. O
Conclusion O
and O
security O
recommendations O
The O
continued O
monitoring O
of O
XLoader B-Malware
showed O
how O
its O
operators O
continuously O
changed O
its O
features O
, O
such O
as O
its O
attack O
vector O
deployment O
infrastructure O
and O
deployment O
techniques O
. O
This O
newest O
entry O
seems O
to O
indicate O
that O
these O
changes O
won O
’ O
t O
be O
stopping O
soon O
. O
Being O
aware O
of O
this O
fact O
can O
help O
create O
defensive O
strategies O
, O
as O
well O
as O
prepare O
for O
upcoming O
attacks O
. O
In O
addition O
, O
just O
as O
uncovering O
new O
characteristics O
is O
important O
, O
finding O
ones O
we O
’ O
ve O
also O
seen O
in O
a O
different O
malware O
family O
like O
FakeSpy B-Malware
also O
provides O
valuable O
insight O
. O
Links O
between O
XLoader B-Malware
and O
FakeSpy B-Malware
can O
give O
clues O
to O
the O
much O
broader O
inner O
workings O
of O
the O
threat O
actors O
behind O
them O
. O
Perhaps O
more O
information O
on O
XLoader B-Malware
will O
be O
known O
in O
the O
future O
. O
For O
now O
, O
users O
can O
make O
the O
best O
of O
the O
knowledge O
they O
have O
now O
to O
significantly O
reduce O
the O
effectivity O
of O
such O
malware O
. O
Users O
of O
iOS B-System
can O
remove O
the O
malicious O
profile O
using O
the O
Apple B-Organization
Configurator O
2 O
, O
Apple B-Organization
’ O
s O
official O
iOS B-System
helper O
app O
for O
managing O
Apple B-Organization
devices O
. O
Following O
simple O
best O
practices O
, O
like O
strictly O
downloading O
applications O
or O
any O
files O
from O
trusted O
sources O
and O
being O
wary O
of O
unsolicited O
messages O
, O
can O
also O
prevent O
similar O
attacks O
from O
compromising O
devices O
. O
Indicators O
of O
Compromise O
SHA256 O
Package O
App O
label O
332e68d865009d627343b89a5744843e3fde4ae870193f36b82980363439a425 B-Indicator
ufD.wykyx.vlhvh B-Indicator
SEX O
kr O
porn O
403401aa71df1830d294b78de0e5e867ee3738568369c48ffafe1b15f3145588 B-Indicator
ufD.wyjyx.vahvh B-Indicator
佐川急便 O
466dafa82a4460dcad722d2ad9b8ca332e9a896fc59f06e16ebe981ad3838a6b B-Indicator
com.dhp.ozqh B-Indicator
Facebook B-Organization
5022495104c280286e65184e3164f3f248356d065ad76acef48ee2ce244ffdc8 B-Indicator
ufD.wyjyx.vahvh B-Indicator
Anshin O
Scan O
a0f3df39d20c4eaa410a61a527507dbc6b17c7f974f76e13181e98225bda0511 B-Indicator
com.aqyh.xolo B-Indicator
佐川急便 O
cb412b9a26c1e51ece7a0e6f98f085e1c27aa0251172bf0a361eb5d1165307f7 B-Indicator
jp.co.sagawa.SagawaOfficialApp B-Indicator
佐川急便 O
Malicious O
URLs O
: O
hxxp B-Indicator
: I-Indicator
//38 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
27 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
99 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
11/xvideo/ I-Indicator
hxxp B-Indicator
: I-Indicator
//apple-icloud I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
qwe-japan I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//apple-icloud I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
qwq-japan I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com/ I-Indicator
hxxp B-Indicator
: I-Indicator
//apple-icloud I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
zqo-japan I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com/ I-Indicator
hxxp B-Indicator
: I-Indicator
//files.spamo I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
jp/佐川急便.apk I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-qae I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-qaf I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-qau I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-qaw I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqe I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqo I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqp I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqq I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqu I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//mailsa-wqw I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qae I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qaq I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qaq I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com/aa I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qar I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qat I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//nttdocomo-qaw I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//sagawa-reg I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com/ I-Indicator
hxxp B-Indicator
: I-Indicator
//www I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
711231 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//www I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
759383 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//www I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
923525 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//www I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
923915 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
hxxp B-Indicator
: I-Indicator
//www I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
975685 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
Malicious O
Twitter B-Organization
accounts O
: O
https B-Indicator
: I-Indicator
//twitter.com/lucky88755 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/lucky98745 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/lucky876543 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/luckyone1232 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/sadwqewqeqw I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/gyugyu87418490 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/fdgoer343 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/sdfghuio342 I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/asdqweqweqeqw I-Indicator
https B-Indicator
: I-Indicator
//twitter.com/ukenivor3 I-Indicator
Malicious O
Instagram B-Organization
account O
: O
https B-Indicator
: I-Indicator
//www.instagram.com/freedomguidepeople1830/ I-Indicator
Malicious O
Tumblr B-Organization
accounts O
: O
https B-Indicator
: I-Indicator
//mainsheetgyam.tumblr.com/ I-Indicator
https B-Indicator
: I-Indicator
//hormonaljgrj.tumblr.com/ I-Indicator
https B-Indicator
: I-Indicator
//globalanab.tumblr.com/ I-Indicator
C O
& O
C O
addresses O
: O
104 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
160 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
191 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
190:8822 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
204 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
87:28833 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
204 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
87:28844 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
204 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
87:28855 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
122:28833 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
122:28844 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
122:28855 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
132:28833 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
132:28844 I-Indicator
61 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
230 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
132:28855 I-Indicator
GoldenCup B-Malware
: O
New O
Cyber O
Threat O
Targeting O
World O
Cup O
Fans O
As O
the O
World O
Cup O
launches O
, O
so O
does O
a O
new O
threat O
Officials O
from O
the O
Israeli B-Organization
Defense I-Organization
Force I-Organization
recently O
uncovered O
an O
Android B-System
Spyware O
campaign O
targeting O
Israeli O
soldiers O
and O
orchestrated O
by O
" O
Hamas B-Organization
. O
'' O
The O
latest O
samples O
attributed O
to O
this O
campaign O
were O
discovered O
by O
security O
researchers O
from O
ClearSky B-Organization
. O
In O
our O
research O
, O
we O
focus O
on O
the O
most O
recent O
sample O
, O
an O
application O
dubbed O
as O
" O
Golden B-Malware
Cup I-Malware
'' O
, O
launched O
just O
before O
the O
start O
of O
World O
Cup O
2018 O
. O
Distribution O
/ O
Infection O
When O
this O
campaign O
started O
at O
the O
start O
of O
2018 O
, O
the O
malware O
( O
" O
GlanceLove B-Malware
'' O
, O
" O
WinkChat B-Malware
'' O
) O
was O
distributed O
by O
the O
perpetrators O
mainly O
via O
fake O
Facebook B-System
profiles O
, O
attempting O
to O
seduce O
IDF O
soldiers O
to O
socialize O
on O
a O
different O
platform O
( O
their O
malware O
) O
. O
As O
this O
approach O
was O
not O
a O
great O
success O
, O
their O
last O
attempt O
was O
to O
quickly O
create O
a O
World O
Cup O
app O
and O
this O
time O
distribute O
it O
to O
Israeli O
citizens O
, O
not O
just O
soldiers O
. O
The O
official O
“ O
Golden B-Malware
Cup I-Malware
” O
Facebook B-System
page O
. O
The O
short O
URL O
redirects O
to O
the O
application O
page O
at O
Google B-System
Play I-System
. O
The O
official O
“ O
Golden B-Malware
Cup I-Malware
” O
Facebook B-System
page O
. O
The O
short O
URL O
redirects O
to O
the O
application O
page O
at O
Google B-System
Play I-System
. O
We O
assume O
it O
was O
rushed O
because O
, O
unlike O
GlanceLove B-Malware
, O
it O
lacked O
any O
real O
obfuscation O
. O
Even O
the O
C O
& O
C O
server O
side O
was O
mostly O
exposed O
with O
the O
file O
listing O
available O
for O
everyone O
to O
traverse O
through O
it O
. O
It O
contained O
approximately O
8GB O
of O
stolen O
data O
. O
A O
recent O
whois O
of O
“ O
goldncup.com B-Indicator
” O
. O
Creation O
date O
is O
a O
week O
before O
the O
start O
of O
the O
tournament O
. O
A O
recent O
whois O
of O
“ O
goldncup.com B-Indicator
” O
. O
Creation O
date O
is O
a O
week O
before O
the O
start O
of O
the O
tournament O
. O
How O
it O
Works O
In O
order O
to O
get O
into O
the O
Google B-System
Play I-System
Store O
, O
the O
malware O
uses O
a O
phased O
approach O
which O
is O
quite O
a O
common O
practice O
for O
malware O
authors O
these O
days O
. O
The O
original O
app O
looks O
innocent O
, O
with O
most O
of O
its O
code O
aimed O
at O
implementing O
the O
real O
features O
that O
the O
app O
claims O
to O
provide O
. O
In O
addition O
, O
it O
collects O
identifiers O
and O
some O
data O
from O
the O
device O
. O
After O
getting O
a O
command O
from O
the O
C O
& O
C O
, O
the O
app O
is O
able O
to O
download O
a O
malicious O
payload O
in O
the O
form O
of O
a O
.dex O
file O
that O
is O
being O
dynamically O
loaded O
adding O
the O
additional O
malicious O
capabilities O
. O
In O
this O
way O
, O
the O
malware O
authors O
can O
submit O
their O
app O
and O
add O
the O
malicious O
capabilities O
only O
after O
their O
app O
is O
live O
on O
the O
Play B-System
Store I-System
. O
Communication O
with O
the O
C O
& O
C O
In O
order O
to O
communicate O
with O
its O
C O
& O
C O
, O
the O
app O
uses O
the O
MQTT O
( O
Message O
Queuing O
Telemetry O
Transport O
) O
protocol O
, O
which O
is O
transported O
over O
TCP B-Indicator
port I-Indicator
1883 I-Indicator
. O
Initiating O
the O
MQTT O
client O
. O
Initiating O
the O
MQTT O
client O
. O
Initiating O
the O
MQTT O
client O
. O
The O
app O
connects O
to O
the O
MQTT O
broker O
with O
hardcoded O
username O
and O
password O
and O
a O
unique O
device O
identifier O
generated O
for O
each O
device O
. O
The O
MQTT O
connection O
to O
broker O
The O
MQTT O
connection O
to O
broker O
The O
MQTT O
communication O
is O
used O
primarily O
to O
update O
the O
device O
state O
and O
get O
commands O
from O
the O
C O
& O
C O
. O
It O
uses O
different O
topics O
that O
include O
the O
unique O
device O
identifier O
, O
which O
side O
is O
sending O
the O
message O
, O
and O
whether O
it O
is O
information O
message O
or O
command O
. O
HTTP O
Communication O
In O
addition O
to O
the O
MQTT O
communication O
, O
the O
app O
also O
uses O
plain O
text O
HTTP O
communication O
in O
order O
to O
download O
the O
.dex O
file O
and O
upload O
collected O
data O
. O
All O
of O
the O
files O
that O
are O
being O
uploaded O
or O
downloaded O
are O
zip O
files O
encrypted O
by O
AES O
with O
ECB O
mode O
. O
The O
key O
for O
each O
file O
is O
generated O
randomly O
and O
stored O
in O
the O
encrypted O
file O
with O
a O
fixed O
offset O
. O
In O
order O
to O
upload O
the O
file O
, O
the O
app O
uses O
a O
basic O
REST O
communication O
with O
the O
server O
, O
checking O
if O
the O
file O
exists O
and O
uploading O
it O
if O
it O
isn O
’ O
t O
. O
The O
path O
that O
is O
used O
for O
the O
uploads O
is O
: O
http B-Indicator
: I-Indicator
// I-Indicator
/apps/d/p/op.php I-Indicator
The O
communication O
looks O
like O
this O
: O
First O
Phase O
The O
first O
phase O
of O
the O
app O
’ O
s O
attack O
flow O
collects O
device O
information O
and O
a O
list O
of O
apps O
installed O
on O
the O
device O
. O
These O
are O
then O
uploaded O
to O
the O
C O
& O
C O
HTTP O
server O
. O
The O
collection O
of O
basic O
device O
information O
. O
The O
collection O
of O
basic O
device O
information O
. O
In O
addition O
, O
at O
this O
stage O
the O
app O
can O
process O
one O
of O
these O
commands O
: O
• O
Collect O
device O
info O
• O
Install O
app O
• O
Is O
online O
? O
• O
Change O
server O
domain O
Out O
of O
these O
, O
the O
most O
interesting O
command O
is O
the O
“ O
install O
app O
” O
command O
that O
downloads O
an O
encrypted O
zip O
file O
containing O
the O
second O
phase O
dex O
file O
, O
unpacks O
and O
loads O
it O
. O
Second O
Phase O
The O
second O
phase O
dex O
file O
contains O
3 O
main O
services O
that O
are O
being O
used O
: O
• O
ConnManager O
- O
handles O
connections O
to O
the O
C O
& O
C O
• O
ReceiverManager O
- O
waits O
for O
incoming O
calls O
/ O
app O
installations O
• O
TaskManager O
- O
manages O
the O
data O
collection O
tasks O
The O
C O
& O
C O
server O
address O
is O
different O
than O
the O
one O
that O
is O
used O
by O
the O
first O
phase O
, O
so O
the O
app O
reconnects O
to O
the O
new O
server O
as O
well O
as O
starts O
the O
periodic O
data O
collector O
tasks O
. O
By O
analyzing O
the O
TaskManager O
class O
we O
can O
see O
the O
new O
commands O
that O
are O
supported O
at O
this O
stage O
: O
As O
can O
be O
seen O
in O
the O
code O
snippet O
above O
, O
there O
are O
quite O
a O
lot O
of O
data O
collection O
tasks O
that O
are O
now O
available O
: O
Collect O
device O
info O
Track O
location O
Upload O
contacts O
information O
Upload O
sent O
and O
received O
SMS O
messages O
Upload O
images O
Upload O
video O
files O
Send O
recursive O
dirlist O
of O
the O
external O
storage O
Upload O
specific O
files O
Record O
audio O
using O
the O
microphone O
Record O
calls O
Use O
the O
camera O
to O
capture O
bursts O
of O
snapshots O
Those O
tasks O
can O
either O
run O
periodically O
, O
on O
event O
( O
such O
as O
incoming O
call O
) O
or O
when O
getting O
a O
command O
from O
the O
C O
& O
C O
server O
. O
Mitigations O
Stay O
protected O
from O
mobile O
malware O
by O
taking O
these O
precautions O
: O
Do O
not O
download O
apps O
from O
unfamiliar O
sites O
Only O
install O
apps O
from O
trusted O
sources O
Pay O
close O
attention O
to O
the O
permissions O
requested O
by O
apps O
Install O
a O
suitable O
mobile O
security O
app O
, O
such O
as O
SEP O
Mobile O
or O
Norton O
, O
to O
protect O
your O
device O
and O
data O
Keep O
your O
operating O
system O
up O
to O
date O
Make O
frequent O
backups O
of O
important O
data O
Indicators O
of O
Compromise O
( O
IoCs O
) O
Package O
names O
: O
anew.football.cup.world.com.worldcup B-Indicator
com.coder.glancelove B-Indicator
com.winkchat I-Indicator
APK O
SHA2 O
: O
166f3a863bb2b66bda9c76dccf9529d5237f6394721f46635b053870eb2fcc5a B-Indicator
b45defca452a640b303288131eb64c485f442aae0682a3c56489d24d59439b47 B-Indicator
d9601735d674a9e55546fde0bffde235bc5f2546504b31799d874e8c31d5b6e9 B-Indicator
2ce54d93510126fca83031f9521e40cd8460ae564d3d927e17bd63fb4cb20edc B-Indicator
67b1a1e7b505ac510322b9d4f4fc1e8a569d6d644582b588faccfeeaa4922cb7 B-Indicator
1664cb343ee830fa94725fed143b119f7e2351307ed0ce04724b23469b9002f2 B-Indicator
Loaded O
DEX O
SHA2 O
: O
afaf446a337bf93301b1d72855ccdd76112595f6e4369d977bea6f9721edf37e B-Indicator
Domain/IP O
: O
goldncup B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
glancelove B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
autoandroidup B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
website I-Indicator
mobilestoreupdate B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
website I-Indicator
updatemobapp B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
website I-Indicator
107 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
175 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
144 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
26 I-Indicator
192 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
64 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
114 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
147 I-Indicator
Red B-Malware
Alert I-Malware
2.0 I-Malware
: O
Android B-System
Trojan O
targets O
security-seekers O
A O
malicious O
, O
counterfeit O
version O
of O
a O
VPN B-System
client O
for O
mobile O
devices O
targets O
security-minded O
victims O
with O
a O
RAT O
. O
Written O
by O
Jagadeesh O
Chandraiah O
JULY O
23 O
, O
2018 O
SophosLabs B-Organization
has O
uncovered O
a O
mobile O
malware O
distribution O
campaign O
that O
uses O
advertising O
placement O
to O
distribute O
the O
Red B-Malware
Alert I-Malware
Trojan I-Malware
, O
linking O
counterfeit O
branding O
of O
well-known O
apps O
to O
Web O
pages O
that O
deliver O
an O
updated O
, O
2.0 O
version O
of O
this O
bank O
credential O
thief O
. O
The O
group O
distributing O
this O
family O
of O
malware O
decorates O
it O
in O
the O
branding O
and O
logos O
of O
well-known O
social O
media O
or O
media O
player O
apps O
, O
system O
update O
patches O
, O
or O
( O
in O
its O
most O
recent O
campaign O
) O
VPN B-System
client O
apps O
in O
an O
attempt O
to O
lure O
users O
into O
downloading O
, O
installing O
, O
and O
elevating O
the O
privileges O
of O
a O
Trojanized O
app O
hosted O
on O
a O
site O
not O
affiliated O
with O
any O
reputable O
app O
market O
or O
store O
. O
Aside O
from O
the O
inescapable O
irony O
of O
disguising O
a O
security-reducing O
Trojan O
as O
an O
ostensibly O
security-enhancing O
app O
, O
and O
the O
righteous O
affront O
to O
the O
whole O
concept O
of O
a O
VPN O
’ O
s O
purpose O
a O
Trojan O
so O
disguised O
inspires O
, O
this O
represents O
an O
escalation O
in O
the O
variety O
of O
app O
types O
targeted O
by O
this O
campaign O
of O
bankbots O
in O
disguise O
. O
Red B-Malware
Alert I-Malware
Plays O
Dress-Up O
In O
the O
wild O
, O
we O
found O
Web O
pages O
designed O
to O
( O
vaguely O
) O
resemble O
legitimate O
app O
market O
pages O
, O
hosting O
files O
for O
download O
that O
have O
been O
disguised O
as O
a O
legitimate O
mobile O
application O
of O
moderately O
broad O
appeal O
, O
such O
as O
a O
media O
player O
or O
social O
media O
app O
. O
But O
the O
categories O
targeted O
by O
this O
group O
seem O
to O
be O
broadening O
with O
the O
inclusion O
of O
VPN B-System
software O
. O
The O
Web O
page O
shown O
here O
on O
the O
left O
is O
hosted O
on O
a O
domain O
that O
seems O
apt O
: O
free-vpn B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
download I-Indicator
. O
Investigation O
of O
this O
domain O
led O
to O
additional O
domains O
that O
appear O
to O
have O
been O
registered O
for O
use O
with O
the O
campaign O
, O
but O
are O
not O
in O
use O
yet O
. O
( O
You O
can O
find O
additional O
IoCs O
at O
the O
end O
of O
this O
article O
) O
As O
you O
can O
see O
, O
the O
Web O
page O
uses O
a O
similar O
colour O
scheme O
as O
, O
and O
the O
icon O
design O
from O
, O
a O
legitimate O
VPN O
application O
( O
VPN O
Proxy O
Master O
) O
found O
on O
the O
Google B-System
Play I-System
store I-System
. O
The O
fake O
doesn O
’ O
t O
quite O
nail O
the O
app O
name O
. O
In O
addition O
to O
“ O
Free B-System
VPN I-System
Master I-System
Android I-System
, O
” O
we O
’ O
ve O
observed O
Red B-Malware
Alert I-Malware
2.0 I-Malware
Trojans O
in O
the O
wild O
disguising O
themselves O
using O
names O
like O
: O
Flash B-System
Player I-System
or O
Update B-System
Flash I-System
Player I-System
Android B-System
Update I-System
or O
Android B-System
Antivirus I-System
Chrome B-System
Update I-System
or O
Google B-System
Update I-System
Update B-System
Google I-System
Market I-System
WhatsApp B-System
Viber B-System
OneCoin B-System
Wallet B-System
Pornhub O
Tactic O
FlashLight O
or O
PROFlashLight O
Finanzonline O
The O
vast O
majority O
of O
in-the-wild O
Red B-Malware
Alert I-Malware
2.0 I-Malware
samples I-Malware
falsely O
present O
themselves O
as O
Adobe B-System
Flash I-System
player I-System
for O
Android B-System
, O
a O
utility O
that O
Adobe B-Organization
stopped O
supporting O
years O
ago O
. O
Our O
logs O
show O
a O
number O
of O
simultaneous B-Malware
Red I-Malware
Alert I-Malware
2.0 I-Malware
campaigns I-Malware
in O
operation O
, O
many O
( O
but O
not O
all O
) O
hosted O
on O
dynamic O
DNS O
domains O
. O
The O
Red B-Malware
Alert I-Malware
Payload I-Malware
Once O
installed O
, O
the O
malware O
requests O
Device O
Administrator O
privileges O
. O
If O
the O
malware O
obtains O
device O
administrator O
rights O
, O
it O
will O
be O
able O
to O
lock O
the O
screen O
by O
itself O
, O
expire O
the O
password O
, O
and O
resist O
being O
uninstalled O
through O
normal O
methods O
. O
Device O
admin O
request O
from O
app O
that O
says O
it O
is O
WhatsApp O
The O
app O
then O
stays O
in O
the O
background O
listening O
to O
commands O
from O
the O
cybercrooks O
. O
Within O
some O
of O
the O
first O
of O
those O
commands O
, O
the O
bot O
typically O
receives O
a O
list O
of O
banks O
it O
will O
target O
. O
The O
Trojan O
works O
by O
creating O
an O
overlay O
whenever O
the O
user O
launches O
the O
banking O
application O
. O
Currently O
Running O
Applications O
Banking O
Trojans O
that O
rely O
on O
the O
overlay O
mechanism O
to O
steal O
information O
need O
to O
know O
what O
application O
is O
in O
the O
foreground O
. O
They O
do O
this O
not O
only O
to O
identify O
whether O
the O
use O
of O
a O
particular O
app O
may O
permit O
them O
to O
harvest O
another O
credential O
, O
but O
also O
because O
each O
targeted O
app O
needs O
to O
have O
an O
overlay O
mapped O
to O
its O
design O
, O
so O
the O
Trojan O
can O
intercept O
and O
steal O
user O
data O
. O
This O
quest O
to O
determine O
the O
currently O
running O
application O
is O
a O
hallmark O
of O
overlay O
malware O
, O
so O
we O
thought O
we O
’ O
d O
take O
a O
closer O
look O
at O
how O
it O
’ O
s O
done O
. O
To O
prevent O
this O
, O
Android B-System
’ O
s O
engineers O
regularly O
release O
updates O
that O
contain O
bug O
fixes O
designed O
to O
prevent O
apps O
from O
getting O
the O
list O
of O
currently O
running O
apps O
without O
explicit O
permission O
. O
With O
every O
Android B-System
update O
, O
the O
malware O
authors O
are O
forced O
to O
come O
up O
with O
new O
tricks O
. O
This O
particular O
case O
is O
not O
an O
exception O
. O
The O
author O
( O
s O
) O
of O
this O
malware O
wrote O
separate O
subroutines O
that O
identify O
the O
operating O
system O
version O
and O
fire O
off O
methods O
to O
obtain O
a O
list O
of O
currently O
running O
applications O
known O
to O
work O
on O
that O
particular O
version O
of O
Android B-System
. O
First O
, O
they O
use O
the O
built-in O
toolbox O
commands O
to O
determine O
what O
apps O
are O
running O
. O
If O
that O
doesn O
’ O
t O
work O
, O
they O
try O
to O
use O
queryUsageStats O
: O
When O
the O
malware O
invokes O
queryUsageStats O
, O
it O
asks O
for O
the O
list O
of O
applications O
that O
ran O
in O
the O
last O
1 O
million O
milliseconds O
( O
16 O
minutes O
and O
40 O
seconds O
) O
. O
String O
Resources O
Used O
to O
Store O
App O
Data O
Red B-Malware
Alert I-Malware
2.0 I-Malware
stores O
its O
data O
in O
an O
atypical O
location O
( O
inside O
the O
Strings.xml B-Indicator
file I-Indicator
embedded O
in O
the O
app O
) O
to O
fetch O
its O
critical O
data O
, O
such O
as O
the O
C2 O
address O
. O
The O
com.dsufabunfzs.dowiflubs O
strings O
in O
the O
screenshot O
above O
refer O
to O
the O
internal O
name O
this O
particular O
malware O
was O
given O
, O
which O
in O
this O
case O
was O
randomized O
into O
alphabet O
salad O
. O
It O
’ O
s O
been O
SophosLabs O
’ O
observation O
that O
Red B-Malware
Alert I-Malware
Trojans I-Malware
usually O
have O
a O
randomized O
internal O
name O
like O
this O
. O
The O
strings O
section O
of O
the O
app O
contains O
embedded O
command-and-control O
IP O
addresses O
, O
ports O
, O
and O
domain O
names O
in O
plaintext O
. O
It O
is O
an O
invaluable O
source O
of O
intelligence O
about O
a O
given O
campaign O
.. O
The O
following O
snippet O
shows O
the O
location O
within O
the O
Trojan O
where O
it O
uses O
SQLite O
database O
commands O
to O
store O
and O
recall O
command-and-control O
addresses O
: O
Backdoor O
Commands O
The O
Red B-Malware
Alert I-Malware
code I-Malware
also O
contains O
an O
embedded O
list O
of O
commands O
the O
botmaster O
can O
send O
to O
the O
bot O
. O
The O
malware O
can O
execute O
a O
variety O
of O
arbitrary O
commands O
, O
including O
( O
for O
example O
) O
intercepting O
or O
sending O
text O
messages O
without O
the O
user O
’ O
s O
knowledge O
, O
obtaining O
a O
copy O
of O
the O
victim O
’ O
s O
Address B-System
Book I-System
, O
or O
call O
or O
text O
message O
logs O
, O
or O
sending O
phone O
network O
feature O
codes O
( O
also O
known O
as O
USSD O
codes O
) O
. O
C2 O
and O
Targeted O
Banks O
As O
described O
earlier O
, O
the O
C2 O
domain O
is O
kept O
in O
the O
app O
’ O
s O
resources O
. O
During O
the O
app O
execution O
, O
the O
malware O
contacts O
C2 O
domain O
for O
further O
instructions O
. O
Most O
of O
the O
network O
traffic O
we O
’ O
ve O
observed O
is O
HTTP B-Indicator
. O
The O
C2 O
address O
, O
as O
stored O
in O
samples O
we O
’ O
ve O
seen O
, O
comprise O
both O
an O
IP O
address O
and O
port O
number O
; O
So O
far O
, O
all O
the O
samples O
we O
’ O
ve O
tested O
attempted O
to O
contact O
an O
IP O
address O
on O
port B-Indicator
7878/tcp I-Indicator
. O
If O
the O
main O
C2 O
domain O
is O
not O
responsive O
, O
the O
bot O
fetches O
a O
backup O
C2 O
domain O
from O
a O
Twitter B-Organization
account O
. O
Static O
analysis O
of O
the O
code O
reveals O
that O
the O
malware O
downloads O
the O
overlay O
template O
to O
use O
against O
any O
of O
the O
bank O
( O
s O
) O
it O
is O
targeting O
. O
The O
malware O
also O
sends O
regular O
telemetry O
back O
to O
its O
C2 O
server O
about O
the O
infected O
device O
in O
the O
form O
of O
an O
HTTP B-Indicator
POST O
to O
its O
C2 O
server O
. O
It O
uses O
the O
base O
Dalvik O
User-Agent O
string O
for O
the O
device O
it O
’ O
s O
running O
on O
. O
The O
content O
of O
the O
HTTP B-Indicator
POST O
data O
is O
telemetry O
data O
in O
a O
json O
format O
about O
the O
device O
the O
malware O
is O
running O
on O
. O
The O
list O
of O
banks O
targeted O
by O
Red B-Malware
Alert I-Malware
2.0 I-Malware
includes O
NatWest O
, O
Barclays B-Organization
, O
Westpac O
, O
and O
Citibank O
. O
Red B-Malware
Alert I-Malware
2.0 I-Malware
is O
a O
banking O
bot O
that O
is O
currently O
very O
active O
online O
, O
and O
presents O
a O
risk O
to O
Android O
devices O
. O
We O
expect O
to O
see O
more O
diversification O
in O
the O
social O
engineering O
lures O
this O
threat O
group O
employs O
as O
time O
goes O
on O
. O
So O
far O
, O
legitimate O
app O
stores O
appear O
to O
be O
this O
malware O
’ O
s O
Achilles O
heel O
; O
disabling O
the O
installation O
of O
third-party O
apps O
has O
been O
an O
effective O
prevention O
measure O
. O
Stick O
to O
Google B-System
Play I-System
and O
use O
VPN O
software O
from O
reputable O
vendors O
. O
Sophos B-Organization
detects O
all O
the O
samples O
of O
this O
Trojan O
family O
as O
Andr/Banker-GWC O
and O
Andr/Spybot-A O
. O
In O
the O
wild O
, O
these O
are O
only O
distributed O
as O
a O
direct O
download O
from O
unofficial O
Web O
pages O
( O
“ O
third-party O
” O
app O
) O
and O
not O
through O
legitimate O
app O
stores O
. O
Red B-Malware
Alert I-Malware
2.0 I-Malware
IoCs O
list O
C2 O
addresses O
103.239.30.126:7878 B-Indicator
146.185.241.29:7878 B-Indicator
146.185.241.42:7878 B-Indicator
185.126.200.3:7878 B-Indicator
185.126.200.12:7878 B-Indicator
185.126.200.15:7878 B-Indicator
185.126.200.18:7878 B-Indicator
185.165.28.15:7878 B-Indicator
185.243.243.241:7878 B-Indicator
185.243.243.244:7878 B-Indicator
185.243.243.245:7878 B-Indicator
Domains O
Malware O
source O
Web O
hosts O
on O
167.99.176.61 B-Indicator
: O
free-androidvpn.date B-Indicator
free-androidvpn.download O
free-androidvpn.online O
free-vpn.date B-Indicator
free-vpn.download O
free-vpn.online O
Hashes O
22fcfce096392f085218c3a78dd0fa4be9e67ed725bce42b965a27725f671cf O
55292a4dde8727faad1c40c914cf1be9dfdcf4e67b515aa593bcd8d86e824372 B-Indicator
be92a751e5abbcd24151b509dbb4feb98ea46f367a99d6f86ed4a7c162461e31 B-Indicator
5c4d666cef84abc2a1ffd3b1060ef28fa3c6c3bb4fad1fa26db99350b41bea4c B-Indicator
06081ab7faa729e33b9397a0e47548e75cbec3d43c50e6368e81d737552150a5 B-Indicator
753999cb19a4346042f973e30cf1158c44f2335ab65859d3bfa16bca4098e2ef B-Indicator
As O
a O
result O
of O
a O
lot O
of O
hard O
work O
done O
by O
our O
security O
research O
teams O
, O
we O
revealed O
today O
a O
new O
and O
alarming O
malware O
campaign O
. O
The O
attack O
campaign O
, O
named O
Gooligan B-Malware
, O
breached O
the O
security O
of O
over O
one O
million O
Google B-Organization
accounts O
. O
The O
number O
continues O
to O
rise O
at O
an O
additional O
13,000 O
breached O
devices O
each O
day O
. O
Our O
research O
exposes O
how O
the O
malware O
roots O
infected O
devices O
and O
steals O
authentication O
tokens O
that O
can O
be O
used O
to O
access O
data O
from O
Google B-System
Play I-System
, O
Gmail B-System
, O
Google B-System
Photos I-System
, O
Google B-System
Docs I-System
, O
G B-System
Suite I-System
, O
Google B-System
Drive I-System
, O
and O
more O
. O
Gooligan B-Malware
is O
a O
new O
variant O
of O
the O
Android O
malware O
campaign O
found O
by O
our O
researchers O
in O
the O
SnapPea B-Malware
app O
last O
year O
. O
Check B-Organization
Point I-Organization
reached O
out O
to O
the O
Google B-Organization
Security I-Organization
team O
immediately O
with O
information O
on O
this O
campaign O
. O
Our O
researchers O
are O
working O
closely O
with O
Google B-Organization
to O
investigate O
the O
source O
of O
the O
Gooligan B-Malware
campaign I-Malware
. O
“ O
We O
’ O
re O
appreciative O
of O
both O
Check B-Organization
Point I-Organization
’ O
s O
research O
and O
their O
partnership O
as O
we O
’ O
ve O
worked O
together O
to O
understand O
these O
issues O
, O
” O
said O
Adrian O
Ludwig O
, O
Google B-Organization
’ O
s O
director O
of O
Android B-System
security O
. O
“ O
As O
part O
of O
our O
ongoing O
efforts O
to O
protect O
users O
from O
the O
Ghost B-Malware
Push I-Malware
family I-Malware
of O
malware O
, O
we O
’ O
ve O
taken O
numerous O
steps O
to O
protect O
our O
users O
and O
improve O
the O
security O
of O
the O
Android B-System
ecosystem O
overall. O
” O
We O
are O
very O
encouraged O
by O
the O
statement O
Google B-Organization
shared O
with O
us O
addressing O
the O
issue O
. O
We O
have O
chosen O
to O
join O
forces O
to O
continue O
the O
investigation O
around O
Gooligan B-Malware
. O
Google B-Organization
also O
stated O
that O
they O
are O
taking O
numerous O
steps O
including O
proactively O
notifying O
affected O
accounts O
, O
revoking O
affected O
tokens O
and O
deploying O
SafetyNet O
improvements O
to O
protect O
users O
from O
these O
apps O
in O
the O
future O
. O
Who O
is O
affected O
? O
Gooligan B-Malware
potentially O
affects O
devices O
on O
Android B-System
4 I-System
( I-System
Jelly I-System
Bean I-System
, I-System
KitKat I-System
) I-System
and I-System
5 I-System
( I-System
Lollipop I-System
) I-System
, O
which O
is O
over O
74 O
% O
of O
in-market O
devices O
today O
. O
About O
57 O
% O
of O
these O
devices O
are O
located O
in O
Asia O
and O
about O
9 O
% O
are O
in O
Europe O
. O
In O
our O
research O
we O
identified O
tens O
of O
fake O
applications O
that O
were O
infected O
with O
this O
malware O
. O
If O
you O
’ O
ve O
downloaded O
one O
of O
the O
apps O
listed O
in O
Appendix O
A O
, O
below O
, O
you O
might O
be O
infected O
. O
You O
may O
review O
your O
application O
list O
in O
“ O
Settings O
- O
> O
Apps O
” O
, O
if O
you O
find O
one O
of O
this O
applications O
, O
please O
consider O
downloading O
an O
antivirus O
product O
such O
as O
Check B-Organization
Point I-Organization
ZoneAlarm B-System
to O
check O
if O
you O
are O
indeed O
infected O
. O
We O
have O
noticed O
that O
hundreds O
of O
the O
email O
addresses O
are O
associated O
with O
enterprise O
accounts O
worldwide O
. O
How O
do O
you O
know O
if O
your O
Google B-Organization
account O
is O
breached O
? O
You O
can O
check O
if O
your O
account O
is O
compromised O
by O
accessing O
the O
following O
web O
site O
that O
we O
created O
: O
https B-Indicator
: I-Indicator
//gooligan.checkpoint.com/ I-Indicator
. O
If O
your O
account O
has O
been O
breached O
, O
the O
following O
steps O
are O
required O
: O
A O
clean O
installation O
of O
an O
operating O
system O
on O
your O
mobile O
device O
is O
required O
( O
a O
process O
called O
“ O
flashing O
” O
) O
. O
As O
this O
is O
a O
complex O
process O
, O
we O
recommend O
powering O
off O
your O
device O
and O
approaching O
a O
certified O
technician O
, O
or O
your O
mobile O
service O
provider O
, O
to O
request O
that O
your O
device O
be O
“ O
re-flashed. O
” O
Change O
your O
Google B-Organization
account O
passwords O
immediately O
after O
this O
process O
. O
How O
do O
Android O
devices O
become O
infected O
? O
We O
found O
traces O
of O
the O
Gooligan B-Malware
malware O
code O
in O
dozens O
of O
legitimate-looking O
apps O
on O
third-party O
Android B-System
app O
stores O
. O
These O
stores O
are O
an O
attractive O
alternative O
to O
Google B-System
Play I-System
because O
many O
of O
their O
apps O
are O
free O
, O
or O
offer O
free O
versions O
of O
paid O
apps O
. O
However O
, O
the O
security O
of O
these O
stores O
and O
the O
apps O
they O
sell O
aren O
’ O
t O
always O
verified O
. O
Gooligan-infected B-Malware
apps O
can O
also O
be O
installed O
using O
phishing O
scams O
where O
attackers O
broadcast O
links O
to O
infected O
apps O
to O
unsuspecting O
users O
via O
SMS O
or O
other O
messaging O
services O
. O
How O
did O
Gooligan B-Malware
emerge O
? O
Our O
researchers O
first O
encountered O
Gooligan B-Malware
’ O
s O
code O
in O
the O
malicious O
SnapPea B-Malware
app O
last O
year O
. O
At O
the O
time O
this O
malware O
was O
reported O
by O
several O
security O
vendors O
, O
and O
attributed O
to O
different O
malware O
families O
like O
Ghostpush B-Malware
, O
MonkeyTest B-Malware
, O
and O
Xinyinhe B-Malware
. O
By O
late O
2015 O
, O
the O
malware O
’ O
s O
creators O
had O
gone O
mostly O
silent O
until O
the O
summer O
of O
2016 O
when O
the O
malware O
reappeared O
with O
a O
more O
complex O
architecture O
that O
injects O
malicious O
code O
into O
Android B-System
system O
processes O
. O
The O
change O
in O
the O
way O
the O
malware O
works O
today O
may O
be O
to O
help O
finance O
the O
campaign O
through O
fraudulent O
ad O
activity O
. O
The O
malware O
simulates O
clicks O
on O
app O
advertisements O
provided O
by O
legitimate O
ad O
networks O
and O
forces O
the O
app O
to O
install O
on O
a O
device O
. O
An O
attacker O
is O
paid O
by O
the O
network O
when O
one O
of O
these O
apps O
is O
installed O
successfully O
. O
Logs O
collected O
by O
Check B-Organization
Point I-Organization
researchers O
show O
that O
every O
day O
Gooligan B-Malware
installs O
at O
least O
30,000 O
apps O
fraudulently O
on O
breached O
devices O
or O
over O
2 O
million O
apps O
since O
the O
campaign O
began O
. O
How O
does O
Gooligan B-Malware
work O
? O
The O
infection O
begins O
when O
a O
user O
downloads O
and O
installs O
a O
Gooligan-infected B-Malware
app O
on O
a O
vulnerable O
Android O
device O
. O
Our O
research O
team O
has O
found O
infected O
apps O
on O
third-party O
app O
stores O
, O
but O
they O
could O
also O
be O
downloaded O
by O
Android B-System
users O
directly O
by O
tapping O
malicious O
links O
in O
phishing O
attack O
messages O
. O
After O
an O
infected O
app O
is O
installed O
, O
it O
sends O
data O
about O
the O
device O
to O
the O
campaign O
’ O
s O
Command O
and O
Control O
( O
C O
& O
C O
) O
server O
. O
Gooligan B-Malware
then O
downloads O
a O
rootkit O
from O
the O
C O
& O
C O
server O
that O
takes O
advantage O
of O
multiple O
Android B-System
4 I-System
and I-System
5 I-System
exploits O
including O
the O
well-known O
VROOT B-Vulnerability
( O
CVE-2013-6282 B-Vulnerability
) O
and O
Towelroot B-Vulnerability
( O
CVE-2014-3153 B-Vulnerability
) O
. O
These O
exploits O
still O
plague O
many O
devices O
today O
because O
security O
patches O
that O
fix O
them O
may O
not O
be O
available O
for O
some O
versions O
of O
Android B-System
, O
or O
the O
patches O
were O
never O
installed O
by O
the O
user O
. O
If O
rooting O
is O
successful O
, O
the O
attacker O
has O
full O
control O
of O
the O
device O
and O
can O
execute O
privileged O
commands O
remotely O
. O
After O
achieving O
root O
access O
, O
Gooligan B-Malware
downloads O
a O
new O
, O
malicious O
module O
from O
the O
C O
& O
C O
server O
and O
installs O
it O
on O
the O
infected O
device O
. O
This O
module O
injects O
code O
into O
running O
Google B-System
Play I-System
or O
GMS B-System
( I-System
Google I-System
Mobile I-System
Services I-System
) I-System
to O
mimic O
user O
behavior O
so O
Gooligan B-Malware
can O
avoid O
detection O
, O
a O
technique O
first O
seen O
with O
the O
mobile O
malware O
HummingBad B-Malware
. O
The O
module O
allows O
Gooligan B-Malware
to O
: O
Steal O
a O
user O
’ O
s O
Google B-Organization
email O
account O
and O
authentication O
token O
information O
Install O
apps O
from O
Google B-System
Play I-System
and O
rate O
them O
to O
raise O
their O
reputation O
Install O
adware O
to O
generate O
revenue O
Ad O
servers O
, O
which O
don O
’ O
t O
know O
whether O
an O
app O
using O
its O
service O
is O
malicious O
or O
not O
, O
send O
Gooligan B-Malware
the O
names O
of O
the O
apps O
to O
download O
from O
Google B-System
Play I-System
. O
After O
an O
app O
is O
installed O
, O
the O
ad O
service O
pays O
the O
attacker O
. O
Then O
the O
malware O
leaves O
a O
positive O
review O
and O
a O
high O
rating O
on O
Google B-System
Play I-System
using O
content O
it O
receives O
from O
the O
C O
& O
C O
server O
. O
Our O
research O
team O
was O
able O
to O
identify O
several O
instances O
of O
this O
activity O
by O
cross-referencing O
data O
from O
breached O
devices O
with O
Google B-System
Play I-System
app O
reviews O
. O
This O
is O
another O
reminder O
of O
why O
users O
shouldn O
’ O
t O
rely O
on O
ratings O
alone O
to O
decide O
whether O
to O
trust O
an O
app O
. O
Similar O
to O
HummingBad B-Malware
, O
the O
malware O
also O
fakes O
device O
identification O
information O
, O
such O
as O
IMEI O
and O
IMSI O
, O
to O
download O
an O
app O
twice O
while O
seeming O
like O
the O
installation O
is O
happening O
on O
a O
different O
device O
, O
thereby O
doubling O
the O
potential O
revenue O
. O
What O
are O
Google B-Organization
authorization O
tokens O
? O
A O
Google B-Organization
authorization O
token O
is O
a O
way O
to O
access O
the O
Google B-Organization
account O
and O
the O
related O
services O
of O
a O
user O
. O
It O
is O
issued O
by O
Google B-Organization
once O
a O
user O
successfully O
logged O
into O
this O
account O
. O
When O
an O
authorization O
token O
is O
stolen O
by O
a O
hacker O
, O
they O
can O
use O
this O
token O
to O
access O
all O
the O
Google B-Organization
services O
related O
to O
the O
user O
, O
including O
Google B-System
Play I-System
, O
Gmail B-System
, O
Google B-System
Docs I-System
, O
Google B-System
Drive I-System
, O
and O
Google B-System
Photos I-System
. O
While O
Google B-Organization
implemented O
multiple O
mechanisms O
, O
like O
two-factor-authentication O
, O
to O
prevent O
hackers O
from O
compromising O
Google B-Organization
accounts O
, O
a O
stolen O
authorization O
token O
bypasses O
this O
mechanism O
and O
allows O
hackers O
the O
desired O
access O
as O
the O
user O
is O
perceived O
as O
already O
logged O
in O
. O
Conclusion O
Gooligan B-Malware
has O
breached O
over O
a O
million O
Google B-Organization
accounts O
. O
We O
believe O
that O
it O
is O
the O
largest O
Google B-Malware
account O
breach O
to O
date O
, O
and O
we O
are O
working O
with O
Google B-Organization
to O
continue O
the O
investigation O
. O
We O
encourage O
Android B-System
users O
to O
validate O
whether O
their O
accounts O
have O
been O
breached O
. O
Hacking B-Organization
Team I-Organization
Spying O
Tool O
Listens O
to O
Calls O
By O
: O
Trend B-Organization
Micro I-Organization
July O
21 O
, O
2015 O
Following O
news O
that O
iOS B-System
devices O
are O
at O
risk O
of O
spyware O
related O
to O
the O
Hacking B-Organization
Team I-Organization
, O
the O
saga O
continues O
into O
the O
Android B-System
sphere O
. O
We O
found O
that O
among O
the O
leaked O
files O
is O
the O
code O
for O
Hacking O
Team O
’ O
s O
open-source O
malware O
suite O
RCSAndroid B-Malware
( O
Remote B-Malware
Control I-Malware
System I-Malware
Android I-Malware
) O
, O
which O
was O
sold O
by O
the O
company O
as O
a O
tool O
for O
monitoring O
targets O
. O
( O
Researchers O
have O
been O
aware O
of O
this O
suite O
as O
early O
as O
2014 O
. O
) O
The O
RCSAndroid B-Malware
code O
can O
be O
considered O
one O
of O
the O
most O
professionally O
developed O
and O
sophisticated O
Android B-System
malware O
ever O
exposed O
. O
The O
leak O
of O
its O
code O
provides O
cybercriminals O
with O
a O
new O
weaponized O
resource O
for O
enhancing O
their O
surveillance O
operations O
. O
Based O
on O
the O
leaked O
code O
, O
the O
RCSAndroid B-Malware
app O
can O
do O
the O
following O
intrusive O
routines O
to O
spy O
on O
targets O
: O
Capture O
screenshots O
using O
the O
“ O
screencap O
” O
command O
and O
framebuffer O
direct O
reading O
Monitor O
clipboard O
content O
Collect O
passwords O
for O
Wi-Fi O
networks O
and O
online O
acco O
; O
.unts O
, O
including O
Skype B-System
, O
Facebook B-System
, O
Twitter B-System
, O
Google B-System
, O
WhatsApp B-System
, O
Mail B-System
, O
and O
LinkedIn B-System
Record O
using O
the O
microphone O
Collect O
SMS O
, O
MMS O
, O
and O
Gmail B-System
messages O
Record O
location O
Gather O
device O
information O
Capture O
photos O
using O
the O
front O
and O
back O
cameras O
Collect O
contacts O
and O
decode O
messages O
from O
IM O
accounts O
, O
including O
Facebook B-System
Messenger I-System
, O
WhatsApp B-System
, O
Skype B-System
, O
Viber B-System
, O
Line B-System
, O
WeChat B-System
, O
Hangouts B-System
, O
Telegram B-System
, O
and O
BlackBerry B-System
Messenger I-System
. O
Capture O
real-time O
voice O
calls O
in O
any O
network O
or O
app O
by O
hooking O
into O
the O
“ O
mediaserver O
” O
system O
service O
RCSAndroid B-Malware
in O
the O
Wild O
Our O
analysis O
reveals O
that O
this O
RCSAndroid B-Malware
( O
AndroidOS_RCSAgent.HRX B-Indicator
) O
has O
been O
in O
the O
wild O
since O
2012 O
. O
Traces O
of O
its O
previous O
uses O
in O
the O
wild O
were O
found O
inside O
the O
configuration O
file O
: O
It O
was O
configured O
to O
use O
a O
Command-and-control O
( O
C O
& O
C O
) O
server O
in O
the O
United O
States O
; O
however O
, O
the O
server O
was O
bought O
from O
a O
host O
service O
provider O
and O
is O
now O
unavailable O
. O
It O
was O
configured O
to O
activate O
via O
SMS O
sent O
from O
a O
Czech O
Republic O
number O
. O
Attackers O
can O
send O
SMS O
with O
certain O
messages O
to O
activate O
the O
agent O
and O
trigger O
corresponding O
action O
. O
This O
can O
also O
define O
what O
kind O
of O
evidences O
to O
collect O
. O
Based O
on O
emails O
leaked O
in O
the O
dump O
, O
a O
number O
of O
Czech O
firms O
appear O
to O
be O
in O
business O
with O
the O
Hacking O
team O
, O
including O
a O
major O
IT O
partner O
in O
the O
Olympic O
Games O
. O
Dropping O
Cluster O
Bombs O
RCSAndroid B-Malware
is O
a O
threat O
that O
works O
like O
a O
cluster O
bomb O
in O
that O
it O
deploys O
multiple O
dangerous O
exploits O
and O
uses O
various O
techniques O
to O
easily O
infect O
Android B-System
devices O
. O
While O
analyzing O
the O
code O
, O
we O
found O
that O
the O
whole O
system O
consists O
of O
four O
critical O
components O
, O
as O
follows O
: O
penetration O
solutions O
, O
ways O
to O
get O
inside O
the O
device O
, O
either O
via O
SMS/email O
or O
a O
legitimate O
app O
low-level O
native O
code O
, O
advanced O
exploits O
and O
spy O
tools O
beyond O
Android B-System
’ O
s O
security O
framework O
high-level O
Java O
agent O
– O
the O
app O
’ O
s O
malicious O
APK O
command-and-control O
( O
C O
& O
C O
) O
servers O
, O
used O
to O
remotely O
send/receive O
malicious O
commands O
Attackers O
use O
two O
methods O
to O
get O
targets O
to O
download O
RCSAndroid B-Malware
. O
The O
first O
method O
is O
to O
send O
a O
specially O
crafted O
URL O
to O
the O
target O
via O
SMS O
or O
email O
. O
The O
URL O
will O
trigger O
exploits O
for O
arbitrary B-Vulnerability
memory I-Vulnerability
read I-Vulnerability
( I-Vulnerability
CVE-2012-2825 I-Vulnerability
) I-Vulnerability
and O
heap B-Vulnerability
buffer I-Vulnerability
overflow I-Vulnerability
( I-Vulnerability
CVE-2012-2871 I-Vulnerability
) I-Vulnerability
vulnerabilities O
in O
the O
default O
browsers O
of O
Android B-System
versions I-System
4.0 I-System
Ice I-System
Cream I-System
Sandwich I-System
to O
4.3 B-System
Jelly I-System
Bean I-System
, O
allowing O
another O
local O
privilege O
escalation O
exploit O
to O
execute O
. O
When O
root O
privilege O
is O
gained O
, O
a O
shell O
backdoor O
and O
malicious O
RCSAndroid B-Malware
agent O
APK O
file O
will O
be O
installed O
The O
second O
method O
is O
to O
use O
a O
stealthy O
backdoor O
app O
such O
as O
ANDROIDOS_HTBENEWS.A B-Malware
, O
which O
was O
designed O
to O
bypass O
Google B-System
Play I-System
. O
The O
role O
of O
ANDROIDOS_HTBENEWS.A B-Malware
and O
the O
malicious O
APK O
mentioned O
in O
the O
first O
method O
is O
to O
exploit O
a O
local B-Vulnerability
privilege I-Vulnerability
escalation I-Vulnerability
vulnerability I-Vulnerability
in O
Android O
devices O
. O
Hacking O
Team O
has O
been O
known O
to O
use O
both O
CVE-2014-3153 B-Vulnerability
and O
CVE-2013-6282 B-Vulnerability
in O
their O
attacks O
. O
The O
said O
exploits O
will O
root O
the O
device O
and O
install O
a O
shell O
backdoor O
. O
The O
shell O
backdoor O
then O
installs O
the O
RCSAndroid B-Malware
agent O
. O
This O
agent O
has O
two O
core O
modules O
, O
the O
Evidence O
Collector O
and O
the O
Event O
Action O
Trigger O
. O
The O
Evidence O
Collector O
module O
is O
responsible O
for O
the O
spying O
routines O
outlined O
above O
. O
One O
of O
its O
most O
notable O
routines O
is O
capturing O
voice O
calls O
in O
real O
time O
by O
hooking O
into O
the O
“ O
mediaserver O
” O
system O
service O
. O
The O
basic O
idea O
is O
to O
hook O
the O
voice O
call O
process O
in O
mediaserver O
. O
Take O
voice O
call O
playback O
process O
for O
example O
. O
The O
mediaserver O
will O
first O
builds O
a O
new O
unique O
track O
, O
start O
to O
play O
the O
track O
, O
loop O
play O
all O
audio O
buffer O
, O
then O
finally O
stop O
the O
playback O
. O
The O
raw O
wave O
audio O
buffer O
frame O
can O
be O
dumped O
in O
the O
getNextBuffer O
( O
) O
function O
. O
With O
the O
help O
of O
the O
open-source O
Android B-System
Dynamic O
Binary O
Instrumentation O
Toolkit O
and O
root O
privilege O
, O
it O
is O
possible O
to O
intercept O
any O
function O
execution O
. O
The O
Event O
Action O
Trigger O
module O
triggers O
malicious O
actions O
based O
on O
certain O
events O
. O
These O
events O
can O
be O
based O
on O
time O
, O
charging O
or O
battery O
status O
, O
location O
, O
connectivity O
, O
running O
apps O
, O
focused O
app O
, O
SIM O
card O
status O
, O
SMS O
received O
with O
keywords O
, O
and O
screen O
turning O
on O
. O
According O
to O
the O
configuration O
pattern O
, O
these O
actions O
are O
registered O
to O
certain O
events O
: O
Sync O
configuration O
data O
, O
upgrade O
modules O
, O
and O
download O
new O
payload O
( O
This O
uses O
transport O
protocol O
ZProtocol O
encrypted O
by O
AES/CBC/PKCS5Padding O
algorithm O
to O
communicate O
with O
the O
C O
& O
C O
server O
. O
) O
Upload O
and O
purge O
collected O
evidence O
Destroy O
device O
by O
resetting O
locking O
password O
Execute O
shell O
commands O
Send O
SMS O
with O
defined O
content O
or O
location O
Disable O
network O
Disable O
root O
Uninstall O
bot O
To O
avoid O
detection O
and O
removal O
of O
the O
agent O
app O
in O
the O
device O
memory O
, O
the O
RCSAndroid B-Malware
suite O
also O
detects O
emulators O
or O
sandboxes O
, O
obfuscates O
code O
using O
DexGuard B-System
, O
uses O
ELF O
string O
obfuscator O
, O
and O
adjusts O
the O
OOM O
( O
out-of-memory O
) O
value O
. O
Interestingly O
, O
one O
unused O
feature O
of O
the O
app O
is O
its O
ability O
to O
manipulate O
data O
in O
the O
Android B-System
package O
manager O
to O
add O
and O
remove O
permissions O
and O
components O
as O
well O
as O
hide O
the O
app O
icon O
. O
Recommendations O
Popular O
mobile O
platforms O
like O
Android B-System
are O
common O
targets O
for O
organized O
or O
commercialized O
monitoring O
operations O
. O
Attackers O
know O
that O
rooting O
devices O
via O
malware O
exploits O
is O
an O
effective O
means O
to O
control O
devices O
and O
gather O
information O
from O
them O
. O
In O
a O
root O
broken O
device O
, O
security O
is O
a O
fairy O
tale O
. O
Take O
note O
of O
the O
following O
best O
practices O
to O
prevent O
this O
threat O
from O
getting O
in O
your O
device O
: O
Disable O
app O
installations O
from O
unknown O
, O
third-party O
sources O
. O
Constantly O
update O
your O
Android B-System
devices O
to O
the O
latest O
version O
to O
help O
prevent O
exploits O
, O
especially O
in O
the O
case O
of O
RCSAndroid B-Malware
which O
can O
affect O
only O
up O
to O
version O
4.4.4 B-System
KitKat I-System
. O
Note O
, O
however O
, O
that O
based O
on O
the O
leak O
mail O
from O
a O
customer O
inquiry O
, O
Hacking B-Organization
Team I-Organization
was O
in O
the O
process O
of O
developing O
exploits O
for O
Android B-System
5.0 I-System
Lollipop I-System
. O
Install O
a O
mobile O
security O
solution O
to O
secure O
your O
device O
from O
threats O
. O
The O
leaked O
RCSAndroid B-Malware
code I-Malware
is O
a O
commercial O
weapon O
now O
in O
the O
wild O
. O
Mobile O
users O
are O
called O
on O
to O
be O
on O
top O
of O
this O
news O
and O
be O
on O
guard O
for O
signs O
of O
monitoring O
. O
Some O
indicators O
may O
come O
in O
the O
form O
of O
peculiar O
behavior O
such O
as O
unexpected O
rebooting O
, O
finding O
unfamiliar O
apps O
installed O
, O
or O
instant O
messaging O
apps O
suddenly O
freezing O
. O
Should O
a O
device O
become O
infected O
, O
this O
backdoor O
can O
not O
be O
removed O
without O
root O
privilege O
. O
Users O
may O
be O
required O
the O
help O
of O
their O
device O
manufacturer O
to O
get O
support O
for O
firmware O
flashing O
. O
Trend B-Organization
Micro I-Organization
offers O
security O
for O
Android B-System
mobile O
devices O
through O
Mobile B-System
Security I-System
for I-System
Android™ I-System
to O
protect O
against O
these O
types O
of O
attacks O
. O
Find O
out O
more O
about O
the O
7 O
Android B-System
Security O
Hacks O
You O
Need O
to O
Do O
Right O
Now O
to O
keep O
your O
mobile O
data O
safe O
. O
Update O
as O
of O
July O
23 O
, O
2015 O
1:00 O
AM O
PDT O
( O
UTC-7 O
) O
We O
have O
added O
a O
link O
to O
a O
previous O
report O
discussing O
this O
threat O
. O
Timeline O
of O
posts O
related O
to O
the O
Hacking O
Team O
DATE O
UPDATE O
July O
5 O
The O
Italian O
company O
Hacking B-Organization
Team I-Organization
was O
hacked O
, O
with O
more O
than O
400GB O
of O
confidential O
company O
data O
made O
available O
to O
the O
public O
. O
July O
7 O
Three O
exploits O
– O
two O
for O
Flash B-System
Player I-System
and O
one O
for O
the O
Windows B-System
kernel—were O
initially O
found O
in O
the O
information O
dump O
. O
One O
of O
these O
[ O
CVE-2015-5119 B-Vulnerability
] O
was O
a O
Flash O
zero-day O
. O
The O
Windows B-Vulnerability
kernel I-Vulnerability
vulnerability I-Vulnerability
( O
CVE-2015-2387 B-Vulnerability
) O
existed O
in O
the O
open O
type O
font O
manager O
module O
( O
ATMFD.dll B-Indicator
) O
and O
can O
be O
exploited O
to O
bypass O
the O
sandbox O
mitigation O
mechanism O
. O
The O
Flash B-System
zero-day O
exploit O
( O
CVE-2015-5119 B-Vulnerability
) O
was O
added O
into O
the O
Angler B-Malware
Exploit I-Malware
Kit I-Malware
and O
Nuclear B-Malware
Exploit I-Malware
Pack I-Malware
. O
It O
was O
also O
used O
in O
limited O
attacks O
in O
Korea O
and O
Japan O
. O
July O
11 O
Two O
new O
Flash B-Vulnerability
zero-day I-Vulnerability
vulnerabilities I-Vulnerability
, O
CVE-2015-5122 B-Vulnerability
and O
CVE-2015-5123 B-Vulnerability
, O
were O
found O
in O
the O
hacking O
team O
dump O
. O
July O
13 O
Further O
analysis O
of O
the O
hacking O
team O
dump O
revealed O
that O
the O
company O
used O
UEFI B-Malware
BIOS I-Malware
rootkit I-Malware
to O
keep O
their O
Remote B-Malware
Control I-Malware
System I-Malware
( I-Malware
RCS I-Malware
) I-Malware
agent O
installed O
in O
their O
targets O
’ O
systems O
. O
July O
14 O
A O
new O
zero-day B-Vulnerability
vulnerability I-Vulnerability
( O
CVE-2015-2425 B-Vulnerability
) O
was O
found O
in O
Internet B-System
Explorer I-System
. O
July O
16 O
On O
the O
mobile O
front O
, O
a O
fake O
news O
app O
designed O
to O
bypass O
Google B-System
Play I-System
was O
discovered O
. O
July O
20 O
A O
new O
zero-day B-Vulnerability
vulnerability I-Vulnerability
( O
CVE-2015-2426 B-Vulnerability
) O
was O
found O
in O
Windows B-System
, O
which O
Microsoft B-Organization
fixed O
in O
an O
out-of-band O
patch O
. O
July O
21 O
Analysis O
of O
the O
RCSAndroid B-Malware
spying O
tool O
revealed O
that O
Hacking O
Team O
can O
listen O
to O
calls O
and O
roots O
devices O
to O
get O
in O
. O
July O
28 O
A O
recent O
campaign O
compromised O
Taiwan O
and O
Hong O
Kong O
sites O
to O
deliver O
Flash B-System
exploits O
related O
to O
Hacking B-Organization
Team I-Organization
. O
Android B-System
users O
warned O
of O
malware O
attack O
spreading O
via O
SMS O
FEB O
16 O
, O
2016 O
Security O
researchers O
are O
warning O
owners O
of O
Android B-System
smartphones O
about O
a O
new O
malware O
attack O
, O
spreading O
via O
SMS O
text O
messages O
. O
As O
the O
team O
at O
Scandinavian O
security O
group O
CSIS B-Organization
describes O
, O
malware O
known O
as O
MazarBOT B-Malware
is O
being O
distributed O
via O
SMS O
in O
Denmark O
and O
is O
likely O
to O
also O
be O
encountered O
in O
other O
countries O
. O
Victims O
’ O
first O
encounter O
with O
the O
malware O
reportedly O
comes O
via O
an O
unsolicited O
text O
message O
that O
their O
Android B-System
smartphone I-System
receives O
. O
The O
txt O
message O
uses O
social O
engineering O
to O
dupe O
unsuspecting O
users O
into O
clicking O
on O
a O
link O
to O
a O
downloadable O
Android B-System
application O
. O
CSIS B-Organization
provided O
a O
( O
sanitised O
) O
version O
of O
a O
typical O
message O
to O
warn O
users O
what O
to O
look O
out O
for O
: O
“ O
You O
have O
received O
a O
multimedia O
message O
from O
+ O
[ O
country O
code O
] O
[ O
sender O
number O
] O
Follow O
the O
link O
http B-Indicator
: I-Indicator
//www.mmsforyou I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net/mms.apk I-Indicator
to O
view O
the O
message O
” O
Once O
the O
APK O
package O
is O
downloaded O
, O
potential O
victims O
are O
urged O
to O
grant O
the O
malicious O
app O
a O
wide O
range O
of O
permissions O
on O
their O
Android O
device O
: O
App O
permissions O
SEND_SMS O
RECEIVE_BOOT_COMPLETED O
INTERNET O
SYSTEM_ALERT_WINDOW O
WRITE_SMS O
ACCESS_NETWORK_STATE O
WAKE_LOCK O
GET_TASKS O
CALL_PHONE O
RECEIVE_SMS O
READ_PHONE_STATE O
READ_SMS O
ERASE_PHONE O
Once O
installed O
, O
MazarBOT B-Malware
downloads O
a O
copy O
of O
Tor B-System
onto O
users O
’ O
Android B-System
smartphones O
and O
uses O
it O
to O
connect O
anonymously O
to O
the O
net O
before O
sending O
a O
text O
message O
containing O
the O
victim O
’ O
s O
location O
to O
an O
Iranian O
mobile O
phone O
number O
. O
With O
the O
malware O
now O
in O
place O
, O
a O
number O
of O
actions O
can O
be O
performed O
, O
including O
allowing O
attackers O
to O
secretly O
monitor O
and O
control O
smartphones O
via O
a O
backdoor O
, O
send O
messages O
to O
premium-rate O
numbers O
, O
and O
intercept O
two-factor O
authentication O
codes O
sent O
by O
online O
banking O
apps O
and O
the O
like O
. O
In O
fact O
, O
with O
full O
access O
to O
the O
compromised O
Android B-System
smartphone I-System
, O
the O
opportunities O
for O
criminals O
to O
wreak O
havoc O
are O
significant O
– O
such O
as O
erasing O
infected O
phones O
or O
launching O
man-in-the-middle O
( O
MITM O
) O
attacks O
. O
In O
its O
analysis O
, O
CSIS B-Organization
notes O
that O
MazarBOT B-Malware
was O
reported O
by O
Recorded B-Organization
Future I-Organization
last O
November O
as O
being O
actively O
sold O
in O
Russian O
underground O
forums O
and O
intriguingly O
, O
the O
malware O
will O
not O
activate O
on O
Android B-System
devices O
configured O
with O
Russian O
language O
settings O
. O
This O
, O
in O
itself O
, O
does O
not O
prove O
that O
the O
perpetrators O
of O
the O
malware O
campaign O
are O
based O
in O
Russia O
, O
but O
it O
certainly O
sounds O
as O
if O
that O
is O
a O
strong O
possibility O
. O
Malware O
authors O
in O
the O
past O
have O
often O
coded O
a O
“ O
safety O
net O
” O
into O
their O
malware O
to O
prevent O
them O
from O
accidentally O
infecting O
their O
own O
computers O
and O
devices O
. O
For O
more O
detailed O
information O
about O
the O
threat O
, O
check O
out O
the O
blog O
post O
from O
CSIS B-Organization
. O
And O
, O
of O
course O
, O
remember O
to O
always O
be O
wary O
of O
unsolicited O
, O
unusual O
text O
messages O
and O
installing O
apps O
from O
third-party O
sources O
on O
your O
Android B-System
smartphone I-System
. O
Coronavirus B-System
Update I-System
App I-System
Leads O
to O
Project B-Malware
Spy I-Malware
Android B-System
and O
iOS B-System
Spyware O
We O
discovered O
a O
cyberespionage O
campaign O
we O
have O
named O
Project B-Malware
Spy I-Malware
infecting O
Android B-System
and O
iOS B-System
devices O
with O
spyware O
by O
using O
the O
coronavirus O
disease O
( O
Covid-19 O
) O
as O
a O
lure O
. O
By O
: O
Tony O
Bao O
, O
Junzhi O
Lu O
April O
14 O
, O
2020 O
We O
discovered O
a O
potential O
cyberespionage O
campaign O
, O
which O
we O
have O
named O
Project B-Malware
Spy I-Malware
, O
that O
infects O
Android B-System
and O
iOS B-System
devices O
with O
spyware O
( O
detected O
by O
Trend B-Organization
Micro I-Organization
as O
AndroidOS_ProjectSpy.HRX B-Indicator
and O
IOS_ProjectSpy.A B-Indicator
, O
respectively O
) O
. O
Project B-Malware
Spy I-Malware
uses O
the O
ongoing O
coronavirus O
pandemic O
as O
a O
lure O
, O
posing O
as O
an O
app O
called O
Coronavirus O
Updates O
. O
We O
also O
found O
similarities O
in O
two O
older O
samples O
disguised O
as O
a O
Google B-Organization
service O
and O
, O
subsequently O
, O
as O
a O
music O
app O
after O
further O
investigation O
. O
However O
, O
we O
have O
noted O
a O
significantly O
small O
number O
of O
downloads O
of O
the O
app O
in O
Pakistan O
, O
India O
, O
Afghanistan O
, O
Bangladesh O
, O
Iran O
, O
Saudi O
Arabia O
, O
Austria O
, O
Romania O
, O
Grenada O
, O
and O
Russia O
. O
Project B-Malware
Spy I-Malware
routine O
At O
the O
end O
of O
March O
2020 O
, O
we O
came O
across O
an O
app O
masquerading O
as O
a O
coronavirus O
update O
app O
, O
which O
we O
named O
Project B-Malware
Spy I-Malware
based O
on O
the O
login O
page O
of O
its O
backend O
server O
. O
This O
app O
carries O
a O
number O
of O
the O
capabilities O
: O
Upload O
GSM B-System
, O
WhatsApp B-System
, O
Telegram B-System
, O
Facebook B-System
, O
and O
Threema B-System
messages O
Upload O
voice O
notes O
, O
contacts O
stored O
, O
accounts O
, O
call O
logs O
, O
location O
information O
, O
and O
images O
Upload O
the O
expanded O
list O
of O
collected O
device O
information O
( O
e.g. O
, O
IMEI O
, O
product O
, O
board O
, O
manufacturer O
, O
tag O
, O
host O
, O
Android B-System
version O
, O
application O
version O
, O
name O
, O
model O
brand O
, O
user O
, O
serial O
, O
hardware O
, O
bootloader O
, O
and O
device O
ID O
) O
Upload O
SIM O
information O
( O
e.g. O
, O
IMSI O
, O
operator O
code O
, O
country O
, O
MCC-mobile O
country O
, O
SIM O
serial O
, O
operator O
name O
, O
and O
mobile O
number O
) O
Upload O
wifi O
information O
( O
e.g. O
, O
SSID O
, O
wifi O
speed O
, O
and O
MAC O
address O
) O
Upload O
other O
information O
( O
e.g. O
, O
display O
, O
date O
, O
time O
, O
fingerprint O
, O
created O
at O
, O
and O
updated O
at O
) O
The O
app O
is O
capable O
of O
stealing O
messages O
from O
popular O
messaging O
apps O
by O
abusing O
the O
notification O
permissions O
to O
read O
the O
notification O
content O
and O
saving O
it O
to O
the O
database O
. O
It O
requests O
permission O
to O
access O
the O
additional O
storage O
. O
Project B-Malware
Spy I-Malware
’ O
s O
earlier O
versions O
Searching O
for O
the O
domain O
in O
our O
sample O
database O
, O
we O
found O
that O
the O
coronavirus O
update O
app O
appears O
to O
be O
the O
latest O
version O
of O
another O
sample O
that O
we O
detected O
in O
May O
2019 O
. O
The O
first O
version O
of O
Project B-Malware
Spy I-Malware
( O
detected O
by O
Trend B-Organization
Micro I-Organization
as O
AndroidOS_SpyAgent.HRXB B-Indicator
) O
had O
the O
following O
capabilities O
: O
Collect O
device O
and O
system O
information O
( O
i.e. O
, O
IMEI O
, O
device O
ID O
, O
manufacturer O
, O
model O
and O
phone O
number O
) O
, O
location O
information O
, O
contacts O
stored O
, O
and O
call O
logs O
Collect O
and O
send O
SMS O
Take O
pictures O
via O
the O
camera O
Upload O
recorded O
MP4 O
files O
Monitor O
calls O
Searching O
further O
, O
we O
also O
found O
another O
sample O
that O
could O
be O
the O
second O
version O
of O
Project O
Spy O
. O
This O
version O
appeared O
as O
Wabi O
Music O
, O
and O
copied O
a O
popular O
video-sharing O
social O
networking O
service O
as O
its O
backend O
login O
page O
. O
In O
this O
second O
version O
, O
the O
developer O
’ O
s O
name O
listed O
was O
“ O
concipit1248 O
” O
in O
Google B-System
Play I-System
, O
and O
may O
have O
been O
active O
between O
May O
2019 O
to O
February O
2020 O
. O
This O
app O
appears O
to O
have O
become O
unavailable O
on O
Google B-System
Play I-System
in O
March O
2020 O
. O
The O
second O
Project B-Malware
Spy I-Malware
version O
has O
similar O
capabilities O
to O
the O
first O
version O
, O
with O
the O
addition O
of O
the O
following O
: O
Stealing O
notification O
messages O
sent O
from O
WhatsApp B-System
, O
Facebook B-System
, O
and O
Telegram B-System
Abandoning O
the O
FTP O
mode O
of O
uploading O
the O
recorded O
images O
Aside O
from O
changing O
the O
app O
’ O
s O
supposed O
function O
and O
look O
, O
the O
second O
and O
third O
versions O
’ O
codes O
had O
little O
differences O
. O
Potentially O
malicious O
iOS B-System
connection O
Using O
the O
codes O
and O
“ O
Concipit1248 O
” O
to O
check O
for O
more O
versions O
, O
we O
found O
two O
other O
apps O
in O
the O
App B-System
Store I-System
. O
Further O
analysis O
of O
the O
iOS O
app O
“ O
Concipit1248 O
” O
showed O
that O
the O
server O
used O
, O
spy B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cashnow I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ee I-Indicator
, O
is O
the O
same O
one O
used O
in O
the O
Android B-System
version O
of O
Project B-System
Spy I-System
. O
However O
, O
although O
the O
“ O
Concipit1248 O
” O
app O
requested O
permissions O
to O
open O
the O
device O
camera O
and O
read O
photos O
, O
the O
code O
only O
can O
upload O
a O
self-contained O
PNG O
file O
to O
a O
remote O
sever O
. O
This O
may O
imply O
the O
“ O
Concipit1248 O
” O
app O
is O
still O
incubating O
. O
The O
other O
iOS B-System
app O
“ O
Concipit O
Shop O
” O
from O
the O
same O
developer O
appeared O
normal O
and O
was O
last O
updated O
on O
November O
2019 O
. O
Apple B-Organization
has O
confirmed O
that O
the O
iOS B-System
apps O
are O
not O
functioning O
based O
on O
analysis O
of O
the O
codes O
, O
and O
stated O
that O
the O
sandbox O
is O
able O
to O
detect O
and O
block O
these O
malicious O
behaviors O
. O
Conclusion O
The O
“ O
Corona O
Updates O
” O
app O
had O
relatively O
low O
downloads O
in O
Pakistan O
, O
India O
, O
Afghanistan O
, O
Bangladesh O
, O
Iran O
, O
Saudi O
Arabia O
, O
Austria O
, O
Romania O
, O
Grenada O
, O
and O
Russia O
. O
Perhaps O
the O
app O
’ O
s O
false O
capabilities O
also O
fueled O
the O
low O
number O
of O
downloads O
. O
It O
also O
appears O
the O
apps O
may O
still O
be O
in O
development O
or O
incubation O
, O
maybe O
waiting O
for O
a O
“ O
right O
time O
” O
to O
inject O
the O
malicious O
codes O
. O
It O
’ O
s O
also O
possible O
that O
the O
apps O
are O
being O
used O
to O
test O
other O
possible O
techniques O
. O
A O
possible O
indication O
for O
timing O
might O
be O
when O
the O
app O
reaches O
a O
specific O
number O
of O
downloads O
or O
infected O
devices O
. O
The O
coding O
style O
suggests O
that O
the O
cybercriminals O
behind O
this O
campaign O
are O
amateurs O
. O
The O
incomplete O
iOS B-System
codes O
used O
in O
this O
campaign O
may O
have O
been O
bought O
while O
other O
capabilities O
appear O
to O
have O
been O
added O
. O
This O
may O
also O
explain O
the O
timing O
in O
between O
the O
apps O
becoming O
fully O
functional O
and O
“ O
incubation. O
” O
As O
this O
is O
a O
group O
we O
have O
not O
observed O
before O
, O
we O
will O
continue O
monitoring O
this O
campaign O
for O
further O
developments O
. O
Users O
are O
cautioned O
to O
research O
and O
check O
reviews O
before O
they O
download O
apps O
. O
Observe O
and O
look O
at O
the O
app O
’ O
s O
display O
and O
text O
, O
stated O
functions O
, O
reviews O
from O
other O
users O
, O
and O
requested O
permissions O
before O
downloading O
. O
Make O
sure O
that O
all O
other O
apps O
installed O
and O
the O
device O
operating O
systems O
are O
updated O
to O
the O
latest O
version O
. O
Indicators O
of O
Compromise O
( O
IoCs O
) O
SHA256 O
Detection O
e394e53e53cd9047d6cff184ac333ef7698a34b777ae3aac82c2c669ef661dfe B-Indicator
AndroidOS_SpyAgent.HRXB B-Indicator
e8d4713e43241ab09d40c2ae8814302f77de76650ccf3e7db83b3ac8ad41f9fa B-Indicator
AndroidOS_ProjectSpy.HRX O
29b0d86ae68d83f9578c3f36041df943195bc55a7f3f1d45a9c23f145d75af9d B-Indicator
AndroidOS_ProjectSpy.HRX O
3a15e7b8f4e35e006329811a6a2bf291d449884a120332f24c7e3ca58d0fbbdb B-Indicator
IOS_ProjectSpy.A B-Indicator
URLs O
cashnow B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ee I-Indicator
Backend O
server B-Indicator
ftp I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
XXXX I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
Backend O
server B-Indicator
spy I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cashnow I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ee I-Indicator
Backend O
server B-Indicator
xyz I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cashnow I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ee I-Indicator
Backend O
server O
October O
8 O
, O
2020 O
Sophisticated O
new O
Android B-System
malware O
marks O
the O
latest O
evolution O
of O
mobile O
ransomware O
Attackers O
are O
persistent O
and O
motivated O
to O
continuously O
evolve O
– O
and O
no O
platform O
is O
immune O
. O
That O
is O
why O
Microsoft B-Organization
has O
been O
working O
to O
extend O
its O
industry-leading O
endpoint O
protection O
capabilities O
beyond O
Windows B-System
. O
The O
addition O
of O
mobile O
threat O
defense O
into O
these O
capabilities O
means O
that O
Microsoft B-System
Defender I-System
for O
Endpoint O
( O
previously O
Microsoft B-System
Defender I-System
Advanced I-System
Threat I-System
Protection I-System
) O
now O
delivers O
protection O
on O
all O
major O
platforms O
. O
Microsoft B-Organization
’ O
s O
mobile O
threat O
defense O
capabilities O
further O
enrich O
the O
visibility O
that O
organizations O
have O
on O
threats O
in O
their O
networks O
, O
as O
well O
as O
provide O
more O
tools O
to O
detect O
and O
respond O
to O
threats O
across O
domains O
and O
across O
platforms O
. O
Like O
all O
of O
Microsoft B-Organization
’ O
s O
security O
solutions O
, O
these O
new O
capabilities O
are O
likewise O
backed O
by O
a O
global O
network O
of O
threat O
researchers O
and O
security O
experts O
whose O
deep O
understanding O
of O
the O
threat O
landscape O
guide O
the O
continuous O
innovation O
of O
security O
features O
and O
ensure O
that O
customers O
are O
protected O
from O
ever-evolving O
threats O
. O
For O
example O
, O
we O
found O
a O
piece O
of O
a O
particularly O
sophisticated O
Android B-System
ransomware O
with O
novel O
techniques O
and O
behavior O
, O
exemplifying O
the O
rapid O
evolution O
of O
mobile O
threats O
that O
we O
have O
also O
observed O
on O
other O
platforms O
. O
The O
mobile O
ransomware O
, O
detected O
by O
Microsoft B-System
Defender I-System
for O
Endpoint O
as O
AndroidOS/MalLocker.B B-Indicator
, O
is O
the O
latest O
variant O
of O
a O
ransomware O
family O
that O
’ O
s O
been O
in O
the O
wild O
for O
a O
while O
but O
has O
been O
evolving O
non-stop O
. O
This O
ransomware O
family O
is O
known O
for O
being O
hosted O
on O
arbitrary O
websites O
and O
circulated O
on O
online O
forums O
using O
various O
social O
engineering O
lures O
, O
including O
masquerading O
as O
popular O
apps O
, O
cracked O
games O
, O
or O
video O
players O
. O
The O
new O
variant O
caught O
our O
attention O
because O
it O
’ O
s O
an O
advanced O
malware O
with O
unmistakable O
malicious O
characteristic O
and O
behavior O
and O
yet O
manages O
to O
evade O
many O
available O
protections O
, O
registering O
a O
low O
detection O
rate O
against O
security O
solutions O
. O
As O
with O
most O
Android B-System
ransomware O
, O
this O
new O
threat O
doesn O
’ O
t O
actually O
block O
access O
to O
files O
by O
encrypting O
them O
. O
Instead O
, O
it O
blocks O
access O
to O
devices O
by O
displaying O
a O
screen O
that O
appears O
over O
every O
other O
window O
, O
such O
that O
the O
user O
can O
’ O
t O
do O
anything O
else O
. O
The O
said O
screen O
is O
the O
ransom O
note O
, O
which O
contains O
threats O
and O
instructions O
to O
pay O
the O
ransom O
. O
What O
’ O
s O
innovative O
about O
this O
ransomware O
is O
how O
it O
displays O
its O
ransom O
note O
. O
In O
this O
blog O
, O
we O
’ O
ll O
detail O
the O
innovative O
ways O
in O
which O
this O
ransomware O
surfaces O
its O
ransom O
note O
using O
Android B-System
features O
we O
haven O
’ O
t O
seen O
leveraged O
by O
malware O
before O
, O
as O
well O
as O
incorporating O
an O
open-source O
machine O
learning O
module O
designed O
for O
context-aware O
cropping O
of O
its O
ransom O
note O
. O
New O
scheme O
, O
same O
goal O
In O
the O
past O
, O
Android B-System
ransomware O
used O
a O
special O
permission O
called O
“ O
SYSTEM_ALERT_WINDOW O
” O
to O
display O
their O
ransom O
note O
. O
Apps O
that O
have O
this O
permission O
can O
draw O
a O
window O
that O
belongs O
to O
the O
system O
group O
and O
can O
’ O
t O
be O
dismissed O
. O
No O
matter O
what O
button O
is O
pressed O
, O
the O
window O
stays O
on O
top O
of O
all O
other O
windows O
. O
The O
notification O
was O
intended O
to O
be O
used O
for O
system O
alerts O
or O
errors O
, O
but O
Android B-System
threats O
misused O
it O
to O
force O
the O
attacker-controlled O
UI O
to O
fully O
occupy O
the O
screen O
, O
blocking O
access O
to O
the O
device O
. O
Attackers O
create O
this O
scenario O
to O
persuade O
users O
to O
pay O
the O
ransom O
so O
they O
can O
gain O
back O
access O
to O
the O
device O
. O
To O
catch O
these O
threats O
, O
security O
solutions O
used O
heuristics O
that O
focused O
on O
detecting O
this O
behavior O
. O
Google B-Organization
later O
implemented O
platform-level O
changes O
that O
practically O
eliminated O
this O
attack O
surface O
. O
These O
changes O
include O
: O
Removing O
the O
SYSTEM_ALERT_WINDOW O
error O
and O
alert O
window O
types O
, O
and O
introducing O
a O
few O
other O
types O
as O
replacement O
Elevating O
the O
permission O
status O
of O
SYSTEM_ALERT_WINDOW O
to O
special O
permission O
by O
putting O
it O
into O
the O
“ O
above O
dangerous O
” O
category O
, O
which O
means O
that O
users O
have O
to O
go O
through O
many O
screens O
to O
approve O
apps O
that O
ask O
for O
permission O
, O
instead O
of O
just O
one O
click O
Introducing O
an O
overlay O
kill O
switch O
on O
Android B-System
8.0 I-System
and O
later O
that O
users O
can O
activate O
anytime O
to O
deactivate O
a O
system O
alert O
window O
To O
adapt O
, O
Android B-System
malware O
evolved O
to O
misusing O
other O
features O
, O
but O
these O
aren O
’ O
t O
as O
effective O
. O
For O
example O
, O
some O
strains O
of O
ransomware O
abuse O
accessibility O
features O
, O
a O
method O
that O
could O
easily O
alarm O
users O
because O
accessibility O
is O
a O
special O
permission O
that O
requires O
users O
to O
go O
through O
several O
screens O
and O
accept O
a O
warning O
that O
the O
app O
will O
be O
able O
to O
monitor O
activity O
via O
accessibility O
services O
. O
Other O
ransomware O
families O
use O
infinite O
loops O
of O
drawing O
non-system O
windows B-System
, O
but O
in O
between O
drawing O
and O
redrawing O
, O
it O
’ O
s O
possible O
for O
users O
to O
go O
to O
settings O
and O
uninstall O
the O
offending O
app O
. O
The O
new O
Android B-Malware
ransomware O
variant O
overcomes O
these O
barriers O
by O
evolving O
further O
than O
any O
Android B-Malware
malware O
we O
’ O
ve O
seen O
before O
. O
To O
surface O
its O
ransom O
note O
, O
it O
uses O
a O
series O
of O
techniques O
that O
take O
advantage O
of O
the O
following O
components O
on O
Android B-System
: O
The O
“ O
call O
” O
notification O
, O
among O
several O
categories O
of O
notifications O
that O
Android B-System
supports O
, O
which O
requires O
immediate O
user O
attention O
. O
The O
“ O
onUserLeaveHint O
( O
) O
” O
callback O
method O
of O
the O
Android B-System
Activity I-System
( O
i.e. O
, O
the O
typical O
GUI O
screen O
the O
user O
sees O
) O
is O
called O
as O
part O
of O
the O
activity O
lifecycle O
when O
the O
activity O
is O
about O
to O
go O
into O
the O
background O
as O
a O
result O
of O
user O
choice O
, O
for O
example O
, O
when O
the O
user O
presses O
the O
Home O
key O
. O
The O
malware O
connects O
the O
dots O
and O
uses O
these O
two O
components O
to O
create O
a O
special O
type O
of O
notification O
that O
triggers O
the O
ransom O
screen O
via O
the O
callback O
. O
As O
the O
code O
snippet O
shows O
, O
the O
malware O
creates O
a O
notification O
builder O
and O
then O
does O
the O
following O
: O
setCategory O
( O
“ O
call O
” O
) O
– O
This O
means O
that O
the O
notification O
is O
built O
as O
a O
very O
important O
notification O
that O
needs O
special O
privilege O
. O
setFullScreenIntent O
( O
) O
– O
This O
API O
wires O
the O
notification O
to O
a O
GUI O
so O
that O
it O
pops O
up O
when O
the O
user O
taps O
on O
it O
. O
At O
this O
stage O
, O
half O
the O
job O
is O
done O
for O
the O
malware O
. O
However O
, O
the O
malware O
wouldn O
’ O
t O
want O
to O
depend O
on O
user O
interaction O
to O
trigger O
the O
ransomware O
screen O
, O
so O
, O
it O
adds O
another O
functionality O
of O
Android B-System
callback O
: O
As O
the O
code O
snippet O
shows O
, O
the O
malware O
overrides O
the O
onUserLeaveHint O
( O
) O
callback O
function O
of O
Activity O
class O
. O
The O
function O
onUserLeaveHint O
( O
) O
is O
called O
whenever O
the O
malware O
screen O
is O
pushed O
to O
background O
, O
causing O
the O
in-call O
Activity O
to O
be O
automatically O
brought O
to O
the O
foreground O
. O
Recall O
that O
the O
malware O
hooked O
the O
RansomActivity O
intent O
with O
the O
notification O
that O
was O
created O
as O
a O
“ O
call O
” O
type O
notification O
. O
This O
creates O
a O
chain O
of O
events O
that O
triggers O
the O
automatic O
pop-up O
of O
the O
ransomware O
screen O
without O
doing O
infinite O
redraw O
or O
posing O
as O
system O
window O
. O
Machine O
learning O
module O
indicates O
continuous O
evolution O
As O
mentioned O
, O
this O
ransomware O
is O
the O
latest O
variant O
of O
a O
malware O
family O
that O
has O
undergone O
several O
stages O
of O
evolution O
. O
The O
knowledge O
graph O
below O
shows O
the O
various O
techniques O
this O
ransomware O
family O
has O
been O
seen O
using O
, O
including O
abusing O
the O
system O
alert O
window O
, O
abusing O
accessibility O
features O
, O
and O
, O
more O
recently O
, O
abusing O
notification O
services O
. O
This O
ransomware O
family O
’ O
s O
long O
history O
tells O
us O
that O
its O
evolution O
is O
far O
from O
over O
. O
We O
expect O
it O
to O
churn O
out O
new O
variants O
with O
even O
more O
sophisticated O
techniques O
. O
In O
fact O
, O
recent O
variants O
contain O
code O
forked O
from O
an O
open-source O
machine O
learning O
module O
used O
by O
developers O
to O
automatically O
resize O
and O
crop O
images O
based O
on O
screen O
size O
, O
a O
valuable O
function O
given O
the O
variety O
of O
Android B-System
devices O
. O
The O
frozen O
TinyML B-System
model O
is O
useful O
for O
making O
sure O
images O
fit O
the O
screen O
without O
distortion O
. O
In O
the O
case O
of O
this O
ransomware O
, O
using O
the O
model O
would O
ensure O
that O
its O
ransom O
note—typically O
fake O
police O
notice O
or O
explicit O
images O
supposedly O
found O
on O
the O
device—would O
appear O
less O
contrived O
and O
more O
believable O
, O
increasing O
the O
chances O
of O
the O
user O
paying O
for O
the O
ransom O
. O
The O
library O
that O
uses O
tinyML B-System
is O
not O
yet O
wired O
to O
the O
malware O
’ O
s O
functionalities O
, O
but O
its O
presence O
in O
the O
malware O
code O
indicates O
the O
intention O
to O
do O
so O
in O
future O
variants O
. O
We O
will O
continue O
to O
monitor O
this O
ransomware O
family O
to O
ensure O
customers O
are O
protected O
and O
to O
share O
our O
findings O
and O
insights O
to O
the O
community O
for O
broad O
protection O
against O
these O
evolving O
mobile O
threats O
. O
Protecting O
organizations O
from O
threats O
across O
domains O
and O
platforms O
Mobile O
threats O
continue O
to O
rapidly O
evolve O
, O
with O
attackers O
continuously O
attempting O
to O
sidestep O
technological O
barriers O
and O
creatively O
find O
ways O
to O
accomplish O
their O
goal O
, O
whether O
financial O
gain O
or O
finding O
an O
entry O
point O
to O
broader O
network O
compromise O
. O
This O
new O
mobile O
ransomware O
variant O
is O
an O
important O
discovery O
because O
the O
malware O
exhibits O
behaviors O
that O
have O
not O
been O
seen O
before O
and O
could O
open O
doors O
for O
other O
malware O
to O
follow O
. O
It O
reinforces O
the O
need O
for O
comprehensive O
defense O
powered O
by O
broad O
visibility O
into O
attack O
surfaces O
as O
well O
as O
domain O
experts O
who O
track O
the O
threat O
landscape O
and O
uncover O
notable O
threats O
that O
might O
be O
hiding O
amidst O
massive O
threat O
data O
and O
signals O
. O
Microsoft B-System
Defender I-System
for O
Endpoint O
on O
Android B-System
, O
now O
generally O
available O
, O
extends O
Microsoft B-Organization
’ O
s O
industry-leading O
endpoint O
protection O
to O
Android B-System
. O
It O
detects O
this O
ransomware O
( O
AndroidOS/MalLocker.B B-Indicator
) O
, O
as O
well O
as O
other O
malicious O
apps O
and O
files O
using O
cloud-based O
protection O
powered O
by O
deep O
learning O
and O
heuristics O
, O
in O
addition O
to O
content-based O
detection O
. O
It O
also O
protects O
users O
and O
organizations O
from O
other O
mobile O
threats O
, O
such O
as O
mobile O
phishing O
, O
unsafe O
network O
connections O
, O
and O
unauthorized O
access O
to O
sensitive O
data O
. O
Learn O
more O
about O
our O
mobile O
threat O
defense O
capabilities O
in O
Microsoft B-System
Defender I-System
for O
Endpoint O
on O
Android B-System
. O
Malware O
, O
phishing O
, O
and O
other O
threats O
detected O
by O
Microsoft B-System
Defender I-System
for O
Endpoint O
are O
reported O
to O
the O
Microsoft B-Organization
Defender I-Organization
Security I-Organization
Center I-Organization
, O
allowing O
SecOps O
to O
investigate O
mobile O
threats O
along O
with O
endpoint O
signals O
from O
Windows B-System
and O
other O
platforms O
using O
Microsoft B-System
Defender I-System
for O
Endpoint O
’ O
s O
rich O
set O
of O
tools O
for O
detection O
, O
investigation O
, O
and O
response O
. O
Threat O
data O
from O
endpoints O
are O
combined O
with O
signals O
from O
email O
and O
data O
, O
identities O
, O
and O
apps O
in O
Microsoft B-System
365 I-System
Defender I-System
( O
previously O
Microsoft B-System
Threat I-System
Protection I-System
) O
, O
which O
orchestrates O
detection O
, O
prevention O
, O
investigation O
, O
and O
response O
across O
domains O
, O
providing O
coordinated O
defense O
. O
Microsoft B-System
Defender I-System
for O
Endpoint O
on O
Android B-System
further O
enriches O
organizations O
’ O
visibility O
into O
malicious O
activity O
, O
empowering O
them O
to O
comprehensively O
prevent O
, O
detect O
, O
and O
respond O
to O
against O
attack O
sprawl O
and O
cross-domain O
incidents O
. O
Technical O
analysis O
Obfuscation O
On O
top O
of O
recreating O
ransomware O
behavior O
in O
ways O
we O
haven O
’ O
t O
seen O
before O
, O
the O
Android B-System
malware O
variant O
uses O
a O
new O
obfuscation O
technique O
unique O
to O
the O
Android B-System
platform O
. O
One O
of O
the O
tell-tale O
signs O
of O
an O
obfuscated O
malware O
is O
the O
absence O
of O
code O
that O
defines O
the O
classes O
declared O
in O
the O
manifest O
file O
. O
The O
classes.dex O
has O
implementation O
for O
only O
two O
classes O
: O
The O
main O
application O
class O
gCHotRrgEruDv O
, O
which O
is O
involved O
when O
the O
application O
opens O
A O
helper O
class O
that O
has O
definition O
for O
custom O
encryption O
and O
decryption O
This O
means O
that O
there O
’ O
s O
no O
code O
corresponding O
to O
the O
services O
declared O
in O
the O
manifest O
file O
: O
Main O
Activity O
, O
Broadcast O
Receivers O
, O
and O
Background O
. O
How O
does O
the O
malware O
work O
without O
code O
for O
these O
key O
components O
? O
As O
is O
characteristic O
for O
obfuscated O
threats O
, O
the O
malware O
has O
encrypted O
binary O
code O
stored O
in O
the O
Assets O
folder O
: O
When O
the O
malware O
runs O
for O
the O
first O
time O
, O
the O
static O
block O
of O
the O
main O
class O
is O
run O
. O
The O
code O
is O
heavily O
obfuscated O
and O
made O
unreadable O
through O
name O
mangling O
and O
use O
of O
meaningless O
variable O
names O
: O
Decryption O
with O
a O
twist O
The O
malware O
uses O
an O
interesting O
decryption O
routine O
: O
the O
string O
values O
passed O
to O
the O
decryption O
function O
do O
not O
correspond O
to O
the O
decrypted O
value O
, O
they O
correspond O
to O
junk O
code O
to O
simply O
hinder O
analysis O
. O
On O
Android B-System
, O
an O
Intent O
is O
a O
software O
mechanism O
that O
allows O
users O
to O
coordinate O
the O
functions O
of O
different O
Activities O
to O
achieve O
a O
task O
. O
It O
’ O
s O
a O
messaging O
object O
that O
can O
be O
used O
to O
request O
an O
action O
from O
another O
app O
component O
. O
The O
Intent O
object O
carries O
a O
string O
value O
as O
“ O
action O
” O
parameter O
. O
The O
malware O
creates O
an O
Intent O
inside O
the O
decryption O
function O
using O
the O
string O
value O
passed O
as O
the O
name O
for O
the O
Intent O
. O
It O
then O
decrypts O
a O
hardcoded O
encrypted O
value O
and O
sets O
the O
“ O
action O
” O
parameter O
of O
the O
Intent O
using O
the O
setAction O
API O
. O
Once O
this O
Intent O
object O
is O
generated O
with O
the O
action O
value O
pointing O
to O
the O
decrypted O
content O
, O
the O
decryption O
function O
returns O
the O
Intent O
object O
to O
the O
callee O
. O
The O
callee O
then O
invokes O
the O
getAction O
method O
to O
get O
the O
decrypted O
content O
. O
Payload O
deployment O
Once O
the O
static O
block O
execution O
is O
complete O
, O
the O
Android B-System
Lifecycle I-System
callback O
transfers O
the O
control O
to O
the O
OnCreate O
method O
of O
the O
main O
class O
. O
Malware O
code O
showing O
onCreate O
method O
Figure O
9. O
onCreate O
method O
of O
the O
main O
class O
decrypting O
the O
payload O
Next O
, O
the O
malware-defined O
function O
decryptAssetToDex O
( O
a O
meaningful O
name O
we O
assigned O
during O
analysis O
) O
receives O
the O
string O
“ O
CuffGmrQRT B-Indicator
” O
as O
the O
first O
argument O
, O
which O
is O
the O
name O
of O
the O
encrypted O
file O
stored O
in O
the O
Assets O
folder O
. O
Malware O
code O
showing O
decryption O
of O
assets O
Figure O
10 O
. O
Decrypting O
the O
assets O
After O
being O
decrypted O
, O
the O
asset O
turns O
into O
the O
.dex O
file O
. O
This O
is O
a O
notable O
behavior O
that O
is O
characteristic O
of O
this O
ransomware O
family O
. O
Comparison O
of O
code O
of O
Asset O
file O
before O
and O
after O
decryption O
Figure O
11 O
. O
Asset O
file O
before O
and O
after O
decryption O
Once O
the O
encrypted O
executable O
is O
decrypted O
and O
dropped O
in O
the O
storage O
, O
the O
malware O
has O
the O
definitions O
for O
all O
the O
components O
it O
declared O
in O
the O
manifest O
file O
. O
It O
then O
starts O
the O
final O
detonator O
function O
to O
load O
the O
dropped O
.dex O
file O
into O
memory O
and O
triggers O
the O
main O
payload O
. O
Malware O
code O
showing O
loading O
of O
decrypted O
dex O
file O
Figure O
12 O
. O
Loading O
the O
decrypted O
.dex O
file O
into O
memory O
and O
triggering O
the O
main O
payload O
Main O
payload O
When O
the O
main O
payload O
is O
loaded O
into O
memory O
, O
the O
initial O
detonator O
hands O
over O
the O
control O
to O
the O
main O
payload O
by O
invoking O
the O
method O
XoqF O
( O
which O
we O
renamed O
to O
triggerInfection O
during O
analysis O
) O
from O
the O
gvmthHtyN O
class O
( O
renamed O
to O
PayloadEntry O
) O
. O
Malware O
code O
showing O
handover O
from O
initial O
module O
to O
main O
payload O
Figure O
13 O
. O
Handover O
from O
initial O
module O
to O
the O
main O
payload O
As O
mentioned O
, O
the O
initial O
handover O
component O
called O
triggerInfection O
with O
an O
instance O
of O
appObj O
and O
a O
method O
that O
returns O
the O
value O
for O
the O
variable O
config O
. O
Malware O
code O
showing O
definition O
of O
populateConfigMap O
Figure O
14 O
. O
Definition O
of O
populateConfigMap O
, O
which O
loads O
the O
map O
with O
values O
Correlating O
the O
last O
two O
steps O
, O
one O
can O
observe O
that O
the O
malware O
payload O
receives O
the O
configuration O
for O
the O
following O
properties O
: O
number O
– O
The O
default O
number O
to O
be O
send O
to O
the O
server O
( O
in O
case O
the O
number O
is O
not O
available O
from O
the O
device O
) O
api O
– O
The O
API O
key O
url O
– O
The O
URL O
to O
be O
used O
in O
WebView O
to O
display O
on O
the O
ransom O
note O
The O
malware O
saves O
this O
configuration O
to O
the O
shared O
preferences O
of O
the O
app O
data O
and O
then O
it O
sets O
up O
all O
the O
Broadcast O
Receivers O
. O
This O
action O
registers O
code O
components O
to O
get O
notified O
when O
certain O
system O
events O
happen O
. O
This O
is O
done O
in O
the O
function O
initComponents O
. O
Malware O
code O
showing O
initializing O
broadcast O
receiver O
Figure O
15 O
. O
Initializing O
the O
BroadcastReceiver O
against O
system O
events O
From O
this O
point O
on O
, O
the O
malware O
execution O
is O
driven O
by O
callback O
functions O
that O
are O
triggered O
on O
system O
events O
like O
connectivity O
change O
, O
unlocking O
the O
phone O
, O
elapsed O
time O
interval O
, O
and O
others O
. O
Lookout B-Organization
researchers O
have O
identified O
a O
new O
, O
highly O
targeted O
surveillanceware O
family O
known O
as O
Desert B-Malware
Scorpion I-Malware
in O
the O
Google B-System
Play I-System
Store I-System
. O
Lookout B-Organization
notified O
Google B-Organization
of O
the O
finding O
and O
Google B-Organization
removed O
the O
app O
immediately O
while O
also O
taking O
action O
on O
it O
in O
Google B-System
Play I-System
Protect I-System
. O
The O
app O
ties O
together O
two O
malware O
families O
- O
Desert B-Malware
Scorpion I-Malware
and O
another O
targeted O
surveillanceware O
family O
named O
FrozenCell B-Malware
- O
that O
we O
believe O
are O
being O
developed O
by O
a O
single O
, O
evolving O
surveillanceware O
actor O
called O
APT-C-23 B-Malware
targeting O
individuals O
in O
the O
Middle O
East O
. O
We O
've O
seen O
this O
actor O
rely O
heavily O
on O
phishing O
campaigns O
to O
trick O
victims O
into O
downloading O
their O
malicious O
apps O
, O
specifically O
on O
Facebook B-System
. O
Even O
sophisticated O
actors O
are O
using O
lower O
cost O
, O
less O
technologically O
impressive O
means O
like O
phishing O
to O
spread O
their O
malware O
because O
it O
's O
cheap O
and O
very O
effective O
, O
especially O
on O
mobile O
devices O
where O
there O
are O
more O
ways O
to O
interact O
with O
a O
victim O
( O
messaging O
apps O
, O
social O
media O
apps O
, O
etc O
. O
) O
, O
and O
less O
screen O
real O
estate O
for O
victims O
to O
identify O
potential O
indicators O
of O
a O
threat O
. O
Lookout B-Organization
customers O
are O
protected O
against O
this O
threat O
and O
additionally O
we O
have O
included O
a O
list O
of O
IOCs O
at O
the O
end O
of O
this O
report O
. O
The O
potential O
actor O
and O
who O
they O
target O
Our O
current O
analysis O
strongly O
suggests O
Desert B-Malware
Scorpion I-Malware
is O
being O
deployed O
in O
targeted O
attacks O
against O
Middle O
Eastern O
individuals O
of O
interest O
specifically O
those O
in O
Palestine O
and O
has O
also O
been O
highlighted O
by O
other O
researchers O
. O
We O
have O
been O
able O
to O
tie O
the O
malware O
to O
a O
long-running O
Facebook B-Organization
profile O
that O
we O
observed O
promoting O
the O
first O
stage O
of O
this O
family O
, O
a O
malicious O
chat O
application O
called O
Dardesh B-Malware
via O
links O
to O
Google B-System
Play I-System
. O
The O
Lookout B-Organization
Threat I-Organization
Intelligence I-Organization
team O
identified O
that O
this O
same O
Facebook B-Organization
profile O
has O
also O
posted O
Google B-System
Drive I-System
links O
to O
Android B-System
malware O
belonging O
to O
the O
FrozenCell B-Malware
family O
attributed O
to O
APT-C-27 B-Indicator
. O
These O
factors O
, O
in O
combination O
with O
the O
fact O
that O
the O
command O
and O
control O
infrastructure O
used O
by O
Frozen B-Malware
Cell I-Malware
and O
Desert B-Malware
Scorpion I-Malware
resides O
in O
similar O
IP O
blocks O
, O
supports O
the O
theory O
that O
the O
same O
actor O
is O
responsible O
for O
operating O
, O
if O
not O
developing O
, O
both O
families O
. O
What O
it O
does O
The O
surveillance O
functionality O
of O
Desert B-Malware
Scorpion I-Malware
resides O
in O
a O
second O
stage O
payload O
that O
can O
only O
be O
downloaded O
if O
the O
victim O
has O
downloaded O
, O
installed O
, O
and O
interacted O
with O
the O
first-stage O
chat O
application O
. O
The O
chat O
application O
acts O
as O
a O
dropper O
for O
this O
second-stage O
payload O
app O
. O
At O
the O
time O
of O
writing O
Lookout B-Organization
has O
observed O
two O
updates O
to O
the O
Dardesh B-Malware
application O
, O
the O
first O
on O
February O
26 O
and O
the O
second O
on O
March O
28 O
. O
The O
malicious O
capabilities O
observed O
in O
the O
second O
stage O
include O
the O
following O
: O
Upload O
attacker-specified O
files O
to O
C2 O
servers O
Get O
list O
of O
installed O
applications O
Get O
device O
metadata O
Inspect O
itself O
to O
get O
a O
list O
of O
launchable O
activities O
Retrieves O
PDF O
, O
txt O
, O
doc O
, O
xls O
, O
xlsx O
, O
ppt O
, O
pptx O
files O
found O
on O
external O
storage O
Send O
SMS O
Retrieve O
text O
messages O
Track O
device O
location O
Handle O
limited O
attacker O
commands O
via O
out O
of O
band O
text O
messages O
Record O
surrounding O
audio O
Record O
calls O
Record O
video O
Retrieve O
account O
information O
such O
as O
email O
addresses O
Retrieve O
contacts O
Removes O
copies O
of O
itself O
if O
any O
additional O
APKs O
are O
downloaded O
to O
external O
storage O
. O
Call O
an O
attacker-specified O
number O
Uninstall O
apps O
Check O
if O
a O
device O
is O
rooted O
Hide O
its O
icon O
Retrieve O
list O
of O
files O
on O
external O
storage O
If O
running O
on O
a O
Huawei O
device O
it O
will O
attempt O
to O
add O
itself O
to O
the O
protected O
list O
of O
apps O
able O
to O
run O
with O
the O
screen O
off O
Encrypts O
some O
exfiltrated O
data O
Desert B-Malware
Scorpion I-Malware
's O
second O
stage O
masquerades O
as O
a O
generic O
" O
settings O
'' O
application O
. O
Curiously O
, O
several O
of O
these O
have O
included O
the O
world O
" O
Fateh O
'' O
in O
their O
package O
name O
, O
which O
may O
be O
referring O
to O
the O
Fatah B-Organization
political O
party O
. O
Such O
references O
would O
be O
in O
line O
with O
FrozenCell B-Malware
's O
phishing O
tactics O
in O
which O
they O
used O
file O
names O
to O
lure O
people O
associated O
with O
the O
political O
party O
to O
open O
malicious O
documents O
. O
Desert B-Malware
Scorpion I-Malware
's O
second O
stage O
is O
capable O
of O
installing O
another O
non-malicious O
application O
( O
included O
in O
the O
second O
stage O
) O
which O
is O
highly O
specific O
to O
the O
Fatah B-Organization
political O
party O
and O
supports O
the O
targeting O
theory O
. O
The O
Lookout B-Organization
Threat I-Organization
Intelligence I-Organization
team O
is O
increasingly O
seeing O
the O
same O
tradecraft O
, O
tactics O
, O
and O
procedures O
that O
APT-C-23 B-Malware
favors O
being O
used O
by O
other O
actors O
. O
The O
approach O
of O
separating O
malicious O
functionality O
out O
into O
separate O
stages O
that O
are O
later O
downloaded O
during O
execution O
and O
not O
present O
in O
the O
initial O
app O
published O
to O
the O
Google B-System
Play I-System
Store I-System
, O
combined O
with O
social O
engineering O
delivered O
via O
social O
media O
platforms O
like O
Facebook B-Organization
, O
requires O
minimal O
investment O
in O
comparison O
to O
premium O
tooling O
like O
Pegasus B-Malware
or O
FinFisher B-Malware
. O
As O
we O
've O
seen O
with O
actors O
like O
Dark B-Malware
Caracal I-Malware
, O
this O
low O
cost O
, O
low O
sophistication O
approach O
that O
relies O
heavily O
upon O
social O
engineering O
has O
still O
been O
shown O
to O
be O
highly O
successful O
for O
those O
operating O
such O
campaigns O
. O
Given O
previous O
operational O
security O
errors O
from O
this O
actor O
in O
the O
past O
which O
resulted O
in O
exfiltrated O
content O
being O
publicly O
accessible O
Lookout B-Organization
Threat I-Organization
Intelligence I-Organization
is O
continuing O
to O
map O
out O
infrastructure O
and O
closely O
monitor O
their O
continued O
evolution O
. O
Virulent B-Malware
Android B-System
malware O
returns O
, O
gets O
> O
2 O
million O
downloads O
on O
Google B-System
Play I-System
HummingWhale B-Malware
is O
back O
with O
new O
tricks O
, O
including O
a O
way O
to O
gin O
user O
ratings O
. O
DAN O
GOODIN O
- O
1/23/2017 O
, O
4:39 O
PM O
A O
virulent B-Malware
family O
of O
malware O
that O
infected O
more O
than O
10 O
million O
Android B-System
devices O
last O
year O
has O
made O
a O
comeback O
, O
this O
time O
hiding O
inside O
Google B-System
Play I-System
apps O
that O
have O
been O
downloaded O
by O
as O
many O
as O
12 O
million O
unsuspecting O
users O
. O
HummingWhale B-Malware
, O
as O
the O
professionally O
developed O
malware O
has O
been O
dubbed O
, O
is O
a O
variant O
of O
HummingBad B-Malware
, O
the O
name O
given O
to O
a O
family O
of O
malicious O
apps O
researchers O
documented O
in O
July O
invading O
non-Google O
app O
markets O
. O
HummingBad B-Malware
attempted O
to O
override O
security O
protections O
by O
exploiting O
unpatched B-Vulnerability
vulnerabilities I-Vulnerability
that O
gave O
the O
malware O
root O
privileges O
in O
older O
versions O
of O
Android B-System
. O
Before O
Google B-Organization
shut O
it O
down O
, O
it O
installed O
more O
than O
50,000 O
fraudulent O
apps O
each O
day O
, O
displayed O
20 O
million O
malicious O
advertisements O
, O
and O
generated O
more O
than O
$ O
300,000 O
per O
month O
in O
revenue O
. O
Of O
the O
10 O
million O
people O
who O
downloaded O
HummingBad-contaminated B-Malware
apps O
, O
an O
estimated O
286,000 O
of O
them O
were O
located O
in O
the O
US O
. O
HummingWhale B-Malware
, O
by O
contrast O
, O
managed O
to O
sneak O
its O
way O
into O
about O
20 O
Google B-System
Play I-System
apps O
that O
were O
downloaded O
from O
2 O
million O
to O
12 O
million O
times O
, O
according O
to O
researchers O
from O
Check B-Organization
Point I-Organization
, O
the O
security O
company O
that O
has O
been O
closely O
following O
the O
malware O
family O
for O
almost O
a O
year O
. O
Rather O
than O
rooting O
devices O
, O
the O
latest O
variant O
includes O
new O
virtual O
machine O
techniques O
that O
allow O
the O
malware O
to O
perform O
ad O
fraud O
better O
than O
ever O
, O
company O
researchers O
said O
in O
a O
blog O
post O
published O
Monday O
. O
" O
Users O
must O
realize O
that O
they O
can O
no O
longer O
trust O
in O
installing O
only O
apps O
with O
a O
high O
reputation O
from O
official O
app O
stores O
as O
their O
sole O
defense O
, O
'' O
the O
researchers O
wrote O
in O
an O
e-mail O
to O
Ars B-Organization
. O
" O
This O
malware O
employs O
several O
tactics O
to O
keep O
its O
activity O
hidden O
, O
meaning O
users O
might O
be O
unaware O
of O
its O
existence O
on O
their O
device O
. O
'' O
As O
was O
the O
case O
with O
HummingBad B-Malware
, O
the O
purpose O
of O
HummingWhale B-Malware
is O
to O
generate O
revenue O
by O
displaying O
fraudulent O
ads O
and O
automatically O
installing O
apps O
. O
When O
users O
try O
to O
close O
the O
ads O
, O
the O
new O
functionality O
causes O
already O
downloaded O
apps O
to O
run O
in O
a O
virtual O
machine O
. O
That O
creates O
a O
fake O
ID O
that O
allows O
the O
perpetrators O
to O
generate O
referral O
revenues O
. O
Use O
of O
the O
virtual O
machine O
brings O
many O
technical O
benefits O
to O
the O
operators O
, O
chief O
among O
them O
allowing O
the O
malware O
to O
install O
apps O
without O
requiring O
users O
to O
approve O
a O
list O
of O
elevated O
permissions O
. O
Advertisement O
The O
VM O
also O
disguises O
the O
malicious O
activity O
, O
making O
it O
easier O
for O
the O
apps O
to O
infiltrate O
Google B-System
Play I-System
. O
It O
has O
the O
added O
benefit O
of O
installing O
a O
nearly O
unlimited O
number O
of O
fraudulent O
apps O
without O
overloading O
the O
infected O
device O
. O
Until O
now O
, O
Android B-System
malware O
that O
wanted O
advanced O
capabilities O
typically O
had O
to O
trick O
users O
into O
approving O
sometimes O
scary-sounding O
permissions O
or O
exploit O
rooting O
vulnerabilities O
. O
Ginning O
the O
ratings O
FURTHER O
READING O
1 O
million O
Google B-Organization
accounts O
compromised O
by O
Android B-System
malware O
called O
Gooligan B-Malware
To O
implement O
the O
VM O
feature O
, O
the O
malicious O
APK O
installation O
dropper O
used O
by O
HummingWhale B-Malware
uses O
DroidPlugin B-Malware
, O
an O
extension O
originally O
developed O
by O
developers O
from O
China-based O
company O
Qihoo B-Organization
360 I-Organization
, O
Check B-Organization
Point I-Organization
said O
. O
HummingWhale B-Malware
has O
also O
been O
observed O
hiding O
the O
original O
malicious O
app O
once O
it O
's O
installed O
and O
trying O
to O
improve O
its O
Google B-System
Play I-System
reputation O
by O
automatically O
generating O
posts O
disguised O
as O
positive O
user O
comments O
and O
ratings O
. O
Gooligan B-Malware
, O
a O
family O
of O
Android B-System
malware O
that O
came O
to O
light O
in O
November O
after O
it O
compromised O
more O
than O
1 O
million O
Google B-Organization
accounts O
, O
contained O
similar O
abilities O
to O
tamper O
with O
Google B-System
Play I-System
ratings O
. O
People O
who O
want O
to O
know O
if O
their O
Android B-System
devices O
are O
infected O
can O
download O
the O
Check B-Organization
Point I-Organization
app O
here O
. O
A O
separate O
app O
from O
Check B-Organization
Point I-Organization
competitor O
Lookout B-Organization
also O
detects O
the O
threat O
as O
a O
variant O
of O
the O
Shedun B-Malware
malware O
family O
. O
More O
technically O
inclined O
people O
can O
detect O
infections O
by O
seeing O
if O
a O
device O
connects O
to O
a O
control O
server O
located O
at O
app.blinkingcamera.com B-Indicator
. O
Package O
names O
for O
infected O
apps O
typically O
contain O
a O
common O
naming O
structure O
that O
includes O
com.XXXXXXXXX.camera B-Indicator
, O
for O
example O
com.bird.sky.whale.camera B-Indicator
( O
app O
name O
: O
Whale B-System
Camera I-System
) O
, O
com.color.rainbow.camera B-Indicator
( O
Rainbow B-System
Camera I-System
) O
, O
and O
com.fishing.when.orangecamera B-Indicator
( O
Orange B-System
Camera I-System
) O
. O
Google B-Organization
officials O
removed O
the O
malicious O
apps O
from O
the O
Play B-System
market I-System
after O
receiving O
a O
private O
report O
of O
their O
existence O
. O
A O
company O
representative O
declined O
to O
comment O
for O
this O
post O
. O
BusyGasper B-Malware
– O
the O
unfriendly O
spy O
29 O
AUG O
2018 O
In O
early O
2018 O
our O
mobile O
intruder-detection O
technology O
was O
triggered O
by O
a O
suspicious O
Android B-System
sample O
that O
, O
as O
it O
turned O
out O
, O
belonged O
to O
an O
unknown O
spyware O
family O
. O
Further O
investigation O
showed O
that O
the O
malware O
, O
which O
we O
named O
BusyGasper B-Malware
, O
is O
not O
all O
that O
sophisticated O
, O
but O
demonstrates O
some O
unusual O
features O
for O
this O
type O
of O
threat O
. O
From O
a O
technical O
point O
of O
view O
, O
the O
sample O
is O
a O
unique O
spy O
implant O
with O
stand-out O
features O
such O
as O
device O
sensors O
listeners O
, O
including O
motion O
detectors O
that O
have O
been O
implemented O
with O
a O
degree O
of O
originality O
. O
It O
has O
an O
incredibly O
wide-ranging O
protocol O
– O
about O
100 O
commands O
– O
and O
an O
ability O
to O
bypass O
the O
Doze O
battery O
saver O
. O
As O
a O
modern O
Android O
spyware O
it O
is O
also O
capable O
of O
exfiltrating O
data O
from O
messaging O
applications O
( O
WhatsApp B-System
, O
Viber B-System
, O
Facebook B-System
) O
. O
Moreover O
, O
BusyGasper B-Malware
boasts O
some O
keylogging O
tools O
– O
the O
malware O
processes O
every O
user O
tap O
, O
gathering O
its O
coordinates O
and O
calculating O
characters O
by O
matching O
given O
values O
with O
hardcoded O
ones O
. O
The O
sample O
has O
a O
multicomponent O
structure O
and O
can O
download O
a O
payload O
or O
updates O
from O
its O
C O
& O
C O
server O
, O
which O
happens O
to O
be O
an O
FTP O
server O
belonging O
to O
the O
free O
Russian O
web O
hosting O
service O
Ucoz O
. O
It O
is O
noteworthy O
that O
BusyGasper B-Malware
supports O
the O
IRC O
protocol O
which O
is O
rarely O
seen O
among O
Android B-System
malware O
. O
In O
addition O
, O
the O
malware O
can O
log O
in O
to O
the O
attacker O
’ O
s O
email O
inbox O
, O
parse O
emails O
in O
a O
special O
folder O
for O
commands O
and O
save O
any O
payloads O
to O
a O
device O
from O
email O
attachments O
. O
This O
particular O
operation O
has O
been O
active O
since O
approximately O
May O
2016 O
up O
to O
the O
present O
time O
. O
Infection O
vector O
and O
victims O
While O
looking O
for O
the O
infection O
vector O
, O
we O
found O
no O
evidence O
of O
spear O
phishing O
or O
any O
of O
the O
other O
common O
vectors O
. O
But O
some O
clues O
, O
such O
as O
the O
existence O
of O
a O
hidden O
menu O
for O
operator O
control O
, O
point O
to O
a O
manual O
installation O
method O
– O
the O
attackers O
used O
physical O
access O
to O
a O
victim O
’ O
s O
device O
to O
install O
the O
malware O
. O
This O
would O
explain O
the O
number O
of O
victims O
– O
there O
are O
less O
than O
10 O
of O
them O
and O
according O
to O
our O
detection O
statistics O
, O
they O
are O
all O
located O
in O
the O
Russia O
. O
Intrigued O
, O
we O
continued O
our O
search O
and O
found O
more O
interesting O
clues O
that O
could O
reveal O
some O
detailed O
information O
about O
the O
owners O
of O
the O
infected O
devices O
. O
Several O
TXT O
files O
with O
commands O
on O
the O
attacker O
’ O
s O
FTP O
server O
contain O
a O
victim O
identifier O
in O
the O
names O
that O
was O
probably O
added O
by O
the O
criminals O
: O
CMDS10114-Sun1.txt B-Indicator
CMDS10134-Ju_ASUS.txt B-Indicator
CMDS10134-Tad.txt B-Indicator
CMDS10166-Jana.txt B-Indicator
CMDS10187-Sun2.txt B-Indicator
CMDS10194-SlavaAl.txt B-Indicator
CMDS10209-Nikusha.txt B-Indicator
Some O
of O
them O
sound O
like O
Russian O
names O
: O
Jana O
, O
SlavaAl O
, O
Nikusha O
. O
As O
we O
know O
from O
the O
FTP O
dump O
analysis O
, O
there O
was O
a O
firmware O
component O
from O
ASUS B-Organization
firmware O
, O
indicating O
the O
attacker O
’ O
s O
interest O
in O
ASUS B-Organization
devices O
, O
which O
explains O
the O
victim O
file O
name O
that O
mentions O
“ O
ASUS O
” O
. O
Information O
gathered O
from O
the O
email O
account O
provides O
a O
lot O
of O
the O
victims O
’ O
personal O
data O
, O
including O
messages O
from O
IM O
applications O
. O
Gathered O
file O
Type O
Description O
lock O
Text O
Implant O
log O
ldata O
sqlite3 O
Location O
data O
based O
on O
network O
( O
cell_id O
) O
gdata O
sqlite3 O
Location O
data O
based O
on O
GPS O
coordinates O
sdata B-Indicator
sqlite3 I-Indicator
SMS O
messages O
f.db B-Indicator
sqlite3 I-Indicator
Facebook B-System
messages O
v.db B-Indicator
sqlite3 I-Indicator
Viber B-System
messages O
w.db B-Indicator
sqlite3 I-Indicator
WhatsApp B-System
messages O
Among O
the O
other O
data O
gathered O
were O
SMS O
banking O
messages O
that O
revealed O
an O
account O
with O
a O
balance O
of O
more O
than O
US O
$ O
10,000.But O
as O
far O
as O
we O
know O
, O
the O
attacker O
behind O
this O
campaign O
is O
not O
interested O
in O
stealing O
the O
victims O
’ O
money O
. O
We O
found O
no O
similarities O
to O
commercial O
spyware O
products O
or O
to O
other O
known O
spyware O
variants O
, O
which O
suggests O
BusyGasper B-Malware
is O
self-developed O
and O
used O
by O
a O
single O
threat O
actor O
. O
At O
the O
same O
time O
, O
the O
lack O
of O
encryption O
, O
use O
of O
a O
public O
FTP O
server O
and O
the O
low O
opsec O
level O
could O
indicate O
that O
less O
skilled O
attackers O
are O
behind O
the O
malware O
. O
Technical O
details O
Here O
is O
the O
meta O
information O
for O
the O
observed O
samples O
, O
certificates O
and O
hardcoded O
version O
stamps O
: O
Certificate O
MD5 O
Module O
Version O
Serial O
Number O
: O
0x76607c02 B-Indicator
Issuer O
: O
CN=Ron O
Validity O
: O
from O
= O
Tue O
Aug O
30 O
13:01:30 O
MSK O
2016 O
to O
= O
Sat O
Aug O
24 O
13:01:30 O
MSK O
2041 O
Subject O
: O
CN=Ron O
9e005144ea1a583531f86663a5f14607 B-Indicator
1 O
– O
18abe28730c53de6d9e4786c7765c3d8 B-Indicator
2 O
2.0 O
Serial O
Number O
: O
0x6a0d1fec B-Indicator
Issuer O
: O
CN=Sun O
Validity O
: O
from O
= O
Mon O
May O
16 O
17:42:40 O
MSK O
2016 O
to O
= O
Fri O
May O
10 O
17:42:40 O
MSK O
2041 O
Subject O
: O
CN=Sun O
9ffc350ef94ef840728564846f2802b0 B-Indicator
2 O
v2.51sun O
6c246bbb40b7c6e75c60a55c0da9e2f2 B-Indicator
2 O
v2.96s O
7c8a12e56e3e03938788b26b84b80bd6 B-Indicator
2 O
v3.09s O
bde7847487125084f9e03f2b6b05adc3 B-Indicator
2 O
v3.12s O
2560942bb50ee6e6f55afc495d238a12 B-Indicator
2 O
v3.18s O
It O
’ O
s O
interesting O
that O
the O
issuer O
“ O
Sun O
” O
matches O
the O
“ O
Sun1 O
” O
and O
“ O
Sun2 O
” O
identifiers O
of O
infected O
devices O
from O
the O
FTP O
server O
, O
suggesting O
they O
may O
be O
test O
devices O
. O
The O
analyzed O
implant O
has O
a O
complex O
structure O
, O
and O
for O
now O
we O
have O
observed O
two O
modules O
. O
First O
( O
start O
) O
module O
The O
first O
module O
, O
which O
was O
installed O
on O
the O
targeted O
device O
, O
could O
be O
controlled O
over O
the O
IRC O
protocol O
and O
enable O
deployment O
of O
other O
components O
by O
downloading O
a O
payload O
from O
the O
FTP O
server O
: O
@ O
install O
command O
As O
can O
be O
seen O
from O
the O
screenshot O
above O
, O
a O
new O
component O
was O
copied O
in O
the O
system O
path O
, O
though O
that O
sort O
of O
operation O
is O
impossible O
without O
root O
privileges O
. O
At O
the O
time O
of O
writing O
we O
had O
no O
evidence O
of O
an O
exploit O
being O
used O
to O
obtain O
root O
privileges O
, O
though O
it O
is O
possible O
that O
the O
attackers O
used O
some O
unseen O
component O
to O
implement O
this O
feature O
. O
Here O
is O
a O
full O
list O
of O
possible O
commands O
that O
can O
be O
executed O
by O
the O
first O
module O
: O
Command O
name O
Description O
@ O
stop O
Stop O
IRC O
@ O
quit O
System.exit B-Indicator
( I-Indicator
0 I-Indicator
) I-Indicator
@ O
start O
Start O
IRC O
@ O
server O
Set O
IRC O
server O
( O
default O
value O
is O
“ O
irc.freenode.net B-Indicator
” O
) O
, O
port O
is O
always O
6667 O
@ O
boss O
Set O
IRC O
command O
and O
control O
nickname O
( O
default O
value O
is O
“ O
ISeency O
” O
) O
@ O
nick O
Set O
IRC O
client O
nickname O
@ O
screen O
Report O
every O
time O
when O
screen O
is O
on O
( O
enable/disable O
) O
@ O
root O
Use O
root O
features O
( O
enable/disable O
) O
@ O
timer O
Set O
period O
of O
IRCService O
start O
@ O
hide O
Hide O
implant O
icon O
@ O
unhide O
Unhide O
implant O
icon O
@ O
run O
Execute O
specified O
shell O
@ O
broadcast O
Send O
command O
to O
the O
second O
module O
@ O
echo O
Write O
specified O
message O
to O
log O
@ O
install O
Download O
and O
copy O
specified O
component O
to O
the O
system O
path O
The O
implant O
uses O
a O
complex O
intent-based O
communication O
mechanism O
between O
its O
components O
to O
broadcast O
commands O
: O
Approximate O
graph O
of O
relationships O
between O
BusyGasper O
components O
Second O
( O
main O
) O
module O
This O
module O
writes O
a O
log O
of O
the O
command O
execution O
history O
to O
the O
file O
named O
“ O
lock O
” O
, O
which O
is O
later O
exfiltrated O
. O
Below O
is O
a O
fragment O
of O
such O
a O
log O
: O
Log O
with O
specified O
command O
Log O
files O
can O
be O
uploaded O
to O
the O
FTP O
server O
and O
sent O
to O
the O
attacker O
’ O
s O
email O
inbox O
. O
It O
’ O
s O
even O
possible O
to O
send O
log O
messages O
via O
SMS O
to O
the O
attacker O
’ O
s O
number O
. O
As O
the O
screenshot O
above O
shows O
, O
the O
malware O
has O
its O
own O
command O
syntax O
that O
represents O
a O
combination O
of O
characters O
while O
the O
“ O
# O
” O
symbol O
is O
a O
delimiter O
. O
A O
full O
list O
of O
all O
possible O
commands O
with O
descriptions O
can O
be O
found O
in O
Appendix O
II O
below O
. O
The O
malware O
has O
all O
the O
popular O
capabilities O
of O
modern O
spyware O
. O
Below O
is O
a O
description O
of O
the O
most O
noteworthy O
: O
The O
implant O
is O
able O
to O
spy O
on O
all O
available O
device O
sensors O
and O
to O
log O
registered O
events O
. O
Moreover O
, O
there O
is O
a O
special O
handler O
for O
the O
accelerometer O
that O
is O
able O
to O
calculate O
and O
log O
the O
device O
’ O
s O
speed O
: O
This O
feature O
is O
used O
in O
particular O
by O
the O
command O
“ O
tk0 O
” O
that O
mutes O
the O
device O
, O
disables O
keyguard O
, O
turns O
off O
the O
brightness O
, O
uses O
wakelock O
and O
listens O
to O
device O
sensors O
. O
This O
allows O
it O
to O
silently O
execute O
any O
backdoor O
activity O
without O
the O
user O
knowing O
that O
the O
device O
is O
in O
an O
active O
state O
. O
As O
soon O
as O
the O
user O
picks O
up O
the O
device O
, O
the O
implant O
will O
detect O
a O
motion O
event O
and O
execute O
the O
“ O
tk1 O
” O
and O
“ O
input O
keyevent O
3 O
” O
commands O
. O
“ O
tk1 O
” O
will O
disable O
all O
the O
effects O
of O
the O
“ O
tk0 O
” O
command O
, O
while O
“ O
input O
keyevent O
3 O
” O
is O
the O
shell O
command O
that O
simulates O
the O
pressing O
of O
the O
‘ O
home O
’ O
button O
so O
all O
the O
current O
activities O
will O
be O
minimized O
and O
the O
user O
won O
’ O
t O
suspect O
anything O
. O
Location O
services O
to O
enable O
( O
GPS/network O
) O
tracking O
: O
The O
email O
command O
and O
control O
protocol O
. O
The O
implant O
can O
log O
in O
to O
the O
attackers O
email O
inbox O
, O
parse O
emails O
for O
commands O
in O
a O
special O
“ O
Cmd O
” O
folder O
and O
save O
any O
payloads O
to O
a O
device O
from O
email O
attachments O
. O
Accessing O
the O
“ O
Cmd O
” O
folder O
in O
the O
attacker O
’ O
s O
email O
box O
Moreover O
, O
it O
can O
send O
a O
specified O
file O
or O
all O
the O
gathered O
data O
from O
the O
victim O
device O
via O
email O
. O
Emergency O
SMS O
commands O
. O
If O
an O
incoming O
SMS O
contains O
one O
of O
the O
following O
magic O
strings O
: O
” O
2736428734″ B-Indicator
or O
” O
7238742800″ B-Indicator
the O
malware O
will O
execute O
multiple O
initial O
commands O
: O
Keylogger O
implementation O
Keylogging O
is O
implemented O
in O
an O
original O
manner O
. O
Immediately O
after O
activation O
, O
the O
malware O
creates O
a O
textView O
element O
in O
a O
new O
window O
with O
the O
following O
layout O
parameters O
: O
All O
these O
parameters O
ensure O
the O
element O
is O
hidden O
from O
the O
user O
. O
Then O
it O
adds O
onTouchListener O
to O
this O
textView O
and O
is O
able O
to O
process O
every O
user O
tap O
. O
Interestingly O
, O
there O
is O
an O
allowlist O
of O
tapped O
activities O
: O
ui.ConversationActivity O
ui.ConversationListActivity O
SemcInCallScreen O
Quadrapop O
SocialPhonebookActivity O
The O
listener O
can O
operate O
with O
only O
coordinates O
, O
so O
it O
calculates O
pressed O
characters O
by O
matching O
given O
values O
with O
hardcoded O
ones O
: O
Additionally O
, O
if O
there O
is O
a O
predefined O
command O
, O
the O
keylogger O
can O
make O
a O
screenshot O
of O
the O
tapped O
display O
area O
: O
Manual O
access O
and O
operator O
menu O
There O
is O
a O
hidden O
menu O
( O
Activity O
) O
for O
controlling O
implant O
features O
that O
looks O
like O
it O
was O
created O
for O
manual O
operator O
control O
. O
To O
activate O
this O
menu O
the O
operator O
needs O
to O
call O
the O
hardcoded O
number O
“ O
9909 O
” O
from O
the O
infected O
device O
: O
A O
hidden O
menu O
then O
instantly O
appears O
on O
the O
device O
display O
: O
The O
operator O
can O
use O
this O
interface O
to O
type O
any O
command O
for O
execution O
. O
It O
also O
shows O
a O
current O
malware O
log O
. O
Infrastructure O
FTP O
server O
The O
attackers O
used O
ftp B-Indicator
: I-Indicator
//213.174.157 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
151/ I-Indicator
as O
a O
command O
and O
control O
server O
. O
The O
IP O
belongs O
to O
the O
free O
Russian O
web O
hosting O
service O
Ucoz O
. O
Files O
Description O
CMDS O
* O
.txt O
Text O
files O
with O
commands O
to O
execute O
supersu.apk B-Indicator
SuperSU O
( O
eu.chainfire.supersu B-Indicator
, O
https B-Indicator
: I-Indicator
//play.google.com/store/apps/details I-Indicator
? I-Indicator
id=eu.chainfire.supersu I-Indicator
) O
tool O
246.us B-Indicator
us.x B-Indicator
SuperSU O
ELF O
binaries O
supersu.cfg B-Indicator
supersu.cfg.ju B-Indicator
supersu.cfg.old B-Indicator
SuperSU O
configs O
with O
spyware O
implant O
mention O
bb.txt B-Indicator
BusyBox O
v1.26.2 O
ELF O
file O
bdata.xml B-Indicator
Config O
file O
for O
excluding O
malware O
components O
from O
Android B-System
battery O
saver O
feature O
Doze O
bdatas.apk B-Indicator
Main O
implant O
module O
com.android.network.irc.apk B-Indicator
Start O
implant O
module O
MobileManagerService.apk B-Indicator
ASUS B-Organization
firmware O
system O
component O
( O
clean O
) O
mobilemanager.apk B-Indicator
Corrupted O
archive O
privapp.txt B-Indicator
Looks O
like O
a O
list O
of O
system O
applications O
( O
including O
spyware O
components O
) O
from O
the O
infected O
device O
run-as.x B-Indicator
run-as.y B-Indicator
Run-as O
tool O
ELF O
file O
SuperSU O
config O
fragment O
for O
implant O
components O
and O
the O
busybox O
tool O
supersu.cfg B-Indicator
: O
This O
config O
allows O
the O
implant O
to O
use O
all O
root O
features O
silently O
. O
Content O
of O
bdata.xml O
file O
: O
It O
can O
be O
added O
to O
the O
/system/etc/sysconfig/ B-Indicator
path O
to O
allowlist O
specified O
implant O
components O
from O
the O
battery O
saving O
system O
. O
Email O
account O
A O
Gmail B-System
account O
with O
password O
is O
mentioned O
in O
the O
sample O
’ O
s O
code O
: O
It O
contains O
the O
victim O
’ O
s O
exfiltrated O
data O
and O
“ O
cmd O
” O
directory O
with O
commands O
for O
victim O
devices O
. O
10 O
million O
Android B-System
phones O
infected O
by O
all-powerful O
auto-rooting O
apps O
First O
detected O
in O
November O
, O
Shedun/HummingBad B-Malware
infections O
are O
surging O
. O
7/7/2016 O
, O
1:50 O
PM O
Security O
experts O
have O
documented O
a O
disturbing O
spike O
in O
a O
particularly O
virulent O
family O
of O
Android B-System
malware O
, O
with O
more O
than O
10 O
million O
handsets O
infected O
and O
more O
than O
286,000 O
of O
them O
in O
the O
US O
. O
FURTHER O
READING O
New O
type O
of O
auto-rooting O
Android B-System
adware O
is O
nearly O
impossible O
to O
remove O
Researchers O
from O
security O
firm O
Check B-Organization
Point I-Organization
Software I-Organization
said O
the O
malware O
installs O
more O
than O
50,000 O
fraudulent O
apps O
each O
day O
, O
displays O
20 O
million O
malicious O
advertisements O
, O
and O
generates O
more O
than O
$ O
300,000 O
per O
month O
in O
revenue O
. O
The O
success O
is O
largely O
the O
result O
of O
the O
malware O
's O
ability O
to O
silently O
root O
a O
large O
percentage O
of O
the O
phones O
it O
infects O
by O
exploiting O
vulnerabilities B-Vulnerability
that I-Vulnerability
remain I-Vulnerability
unfixed I-Vulnerability
in I-Vulnerability
older I-Vulnerability
versions I-Vulnerability
of I-Vulnerability
Android I-Vulnerability
. O
The O
Check B-Organization
Point I-Organization
researchers O
have O
dubbed O
the O
malware O
family O
" O
HummingBad B-Malware
, O
'' O
but O
researchers O
from O
mobile O
security O
company O
Lookout B-Organization
say O
HummingBad B-Malware
is O
in O
fact O
Shedun B-Malware
, O
a O
family O
of O
auto-rooting O
malware O
that O
came O
to O
light O
last O
November O
and O
had O
already O
infected O
a O
large O
number O
of O
devices O
. O
Update O
Jul O
11 O
2016 O
8:32 O
: O
On O
Monday O
, O
a O
Checkpoint B-Organization
representative O
disputed O
Lookout B-Organization
's O
contention O
and O
pointed O
to O
this O
blog O
post O
from O
security O
firm O
Eleven B-Organization
Paths I-Organization
as O
support O
. O
The O
blog O
post O
said O
HummingBad B-Malware
" O
uses O
a O
completely O
different O
infrastructure O
with O
little O
in O
common O
'' O
with O
Shedun I-Malware
. O
In O
an O
e-mail O
, O
a O
Lookout B-Organization
representative O
stood O
by O
its O
analysis O
and O
said O
company O
researchers O
planned O
to O
publish O
an O
in-depth O
response O
in O
the O
coming O
days O
. O
For O
the O
past O
five O
months O
, O
Check B-Organization
Point I-Organization
researchers O
have O
quietly O
observed O
the O
China-based O
advertising O
company O
behind O
HummingBad B-Malware
in O
several O
ways O
, O
including O
by O
infiltrating O
the O
command O
and O
control O
servers O
it O
uses O
. O
The O
researchers O
say O
the O
malware O
uses O
the O
unusually O
tight O
control O
it O
gains O
over O
infected O
devices O
to O
create O
windfall O
profits O
and O
steadily O
increase O
its O
numbers O
. O
HummingBad B-Malware
does O
this O
by O
silently O
installing O
promoted O
apps O
on O
infected O
phones O
, O
defrauding O
legitimate O
mobile O
advertisers O
, O
and O
creating O
fraudulent O
statistics O
inside O
the O
official O
Google B-System
Play I-System
Store I-System
. O
" O
Accessing O
these O
devices O
and O
their O
sensitive O
data O
creates O
a O
new O
and O
steady O
stream O
of O
revenue O
for O
cybercriminals O
, O
'' O
Check I-Organization
Point I-Organization
researchers O
wrote O
in O
a O
recently O
published O
report O
. O
" O
Emboldened O
by O
financial O
and O
technological O
independence O
, O
their O
skillsets O
will O
advance–putting O
end O
users O
, O
enterprises O
, O
and O
government O
agencies O
at O
risk O
. O
'' O
The O
report O
said O
HummingBad B-Malware
apps O
are O
developed O
by O
Yingmob B-Organization
, O
a O
Chinese O
mobile O
ad O
server O
company O
that O
other O
researchers O
claim O
is O
behind O
the O
Yinspector B-Malware
iOS B-System
malware O
. O
HummingBad B-Malware
sends O
notifications O
to O
Umeng O
, O
a O
tracking O
and O
analytics O
service O
attackers O
use O
to O
manage O
their O
campaign O
. O
Check B-Organization
Point I-Organization
analyzed O
Yingmob B-Organization
’ O
s O
Umeng O
account O
to O
gain O
further O
insights O
into O
the O
HummingBad B-Malware
campaign O
and O
found O
that O
beyond O
the O
10 O
million O
devices O
under O
the O
control O
of O
malicious O
apps O
, O
Yingmob B-Organization
has O
non-malicious O
apps O
installed O
on O
another O
75 O
million O
or O
so O
devices O
. O
The O
researchers O
wrote O
: O
While O
profit O
is O
powerful O
motivation O
for O
any O
attacker O
, O
Yingmob B-Organization
’ O
s O
apparent O
self-sufficiency O
and O
organizational O
structure O
make O
it O
well-positioned O
to O
expand O
into O
new O
business O
ventures O
, O
including O
productizing O
the O
access O
to O
the O
85 O
million O
Android B-System
devices O
it O
controls O
. O
This O
alone O
would O
attract O
a O
whole O
new O
audience–and O
a O
new O
stream O
of O
revenue–for O
Yingmob B-Organization
. O
Quick O
, O
easy O
access O
to O
sensitive O
data O
on O
mobile O
devices O
connected O
to O
enterprises O
and O
government O
agencies O
around O
the O
globe O
is O
extremely O
attractive O
to O
cybercriminals O
and O
hacktivists O
. O
Drive-by O
downloads O
and O
multiple O
rooting O
exploits O
The O
malware O
uses O
a O
variety O
of O
methods O
to O
infect O
devices O
. O
One O
involves O
drive-by O
downloads O
, O
possibly O
on O
booby-trapped O
porn O
sites O
. O
The O
attacks O
use O
multiple O
exploits O
in O
an O
attempt O
to O
gain O
root O
access O
on O
a O
device O
. O
When O
rooting O
fails O
, O
a O
second O
component O
delivers O
a O
fake O
system O
update O
notification O
in O
hopes O
of O
tricking O
users O
into O
granting O
HummingBad B-Malware
system-level O
permissions O
. O
Whether O
or O
not O
rooting O
succeeds O
, O
HummingBad B-Malware
downloads O
a O
large O
number O
of O
apps O
. O
In O
some O
cases O
, O
malicious O
components O
are O
dynamically O
downloaded O
onto O
a O
device O
after O
an O
infected O
app O
is O
installed O
. O
From O
there O
, O
infected O
phones O
display O
illegitimate O
ads O
and O
install O
fraudulent O
apps O
after O
certain O
events O
, O
such O
as O
rebooting O
, O
the O
screen O
turning O
on O
or O
off O
, O
a O
detection O
that O
the O
user O
is O
present O
, O
or O
a O
change O
in O
Internet O
connectivity O
. O
HummingBad B-Malware
also O
has O
the O
ability O
to O
inject O
code O
into O
Google B-System
Play I-System
to O
tamper O
with O
its O
ratings O
and O
statistics O
. O
It O
does O
this O
by O
using O
infected O
devices O
to O
imitate O
clicks O
on O
the O
install O
, O
buy O
, O
and O
accept O
buttons O
. O
Many O
of O
the O
10 O
million O
infected O
phones O
are O
running O
old O
versions O
of O
Android B-System
and O
reside O
in O
China O
( O
1.6 O
million O
) O
and O
India O
( O
1.35 O
million O
) O
. O
Still O
, O
US-based O
infected O
phones O
total O
almost O
287,000 O
. O
The O
most O
widely O
infected O
major O
Android B-System
versions O
are O
KitKat B-System
with O
50 O
percent O
, O
followed O
by O
Jelly B-System
Bean I-System
with O
40 O
percent O
. O
Lollipop B-System
has O
7 O
percent O
, O
Ice B-System
Cream I-System
Sandwich I-System
has O
2 O
percent O
, O
and O
Marshmallow B-System
has O
1 O
percent O
. O
It O
's O
often O
hard O
for O
average O
users O
to O
know O
if O
their O
phones O
have O
been O
rooted O
, O
and O
Shedun B-Malware
apps O
often O
wait O
some O
period O
of O
time O
before O
displaying O
obtrusive O
ads O
or O
installing O
apps O
. O
The O
best O
bet O
for O
Readers O
who O
want O
to O
make O
sure O
their O
phone O
is O
n't O
infected O
is O
to O
scan O
their O
phones O
using O
the O
free O
version O
of O
the O
Lookout B-Organization
Security O
and O
Antivirus O
app O
. O
Android B-System
malware O
has O
drastically O
lower O
rates O
of O
success O
when O
app O
installations O
outside O
of O
Google B-System
Play I-System
are O
barred O
. O
Readers O
should O
carefully O
think O
through O
the O
risks O
before O
changing O
this O
default O
setting O
. O
Top O
20 O
countries O
targeted O
by O
Hummingbad/Shedun B-Malware
. O
Enlarge O
/ O
Top O
20 O
countries O
targeted O
by O
Hummingbad/Shedun B-Malware
. O
Check B-Organization
Point I-Organization
Software I-Organization
Hummingbad/Shedun B-Malware
infections O
by O
Android B-System
version O
. O
Enlarge O
/ O
Hummingbad/Shedun B-Malware
infections O
by O
Android B-System
version O
. O
Check B-Organization
Point I-Organization
Software I-Organization
So O
far O
, O
HummingBad B-Malware
has O
been O
observed O
using O
its O
highly O
privileged O
status O
only O
to O
engage O
in O
click O
fraud O
, O
display O
pop-up O
ads O
, O
tamper O
with O
Google B-System
Play I-System
, O
and O
install O
additional O
apps O
that O
do O
more O
of O
the O
same O
. O
But O
there O
's O
little O
stopping O
it O
from O
doing O
much O
worse O
. O
That O
's O
because O
the O
malware O
roots O
most O
of O
the O
phones O
it O
infects O
, O
a O
process O
that O
subverts O
key O
security O
mechanisms O
built O
into O
Android B-System
. O
Under O
a O
model O
known O
as O
sandboxing O
, O
most O
Android B-System
apps O
are O
n't O
permitted O
to O
access O
passwords O
or O
other O
data O
available O
to O
most O
other O
apps O
. O
System O
applications O
with O
root O
, O
by O
contrast O
, O
have O
super-user O
permissions O
that O
allow O
them O
to O
break O
out O
of O
such O
sandboxes O
. O
From O
there O
, O
root-level O
apps O
can O
read O
or O
modify O
data O
and O
resources O
that O
would O
be O
off-limits O
to O
normal O
apps O
. O
As O
Lookout B-Organization
first O
reported O
more O
than O
eight O
months O
ago O
, O
the O
problem O
with O
Shedun/HummingBad B-Malware
and O
similar O
malicious O
app O
families O
that O
silently O
exploit O
Android B-Vulnerability
rooting I-Vulnerability
vulnerabilities I-Vulnerability
is O
that O
the O
infections O
can O
survive O
normal O
factory O
resets O
. O
Lookout B-Organization
said O
in O
its O
own O
blog O
post O
published O
Wednesday O
that O
its O
threat O
detection O
network O
has O
recently O
observed O
a O
surge O
of O
Shedun B-Malware
attacks O
, O
indicating O
the O
scourge O
wo O
n't O
be O
going O
away O
any O
time O
soon O
. O
An O
investigation O
of O
Chrysaor B-Malware
Malware O
on O
Android B-System
03 O
April O
2017 O
Google B-Organization
is O
constantly O
working O
to O
improve O
our O
systems O
that O
protect O
users O
from O
Potentially O
Harmful O
Applications O
( O
PHAs O
) O
. O
Usually O
, O
PHA O
authors O
attempt O
to O
install O
their O
harmful O
apps O
on O
as O
many O
devices O
as O
possible O
. O
However O
, O
a O
few O
PHA O
authors O
spend O
substantial O
effort O
, O
time O
, O
and O
money O
to O
create O
and O
install O
their O
harmful O
app O
on O
one O
or O
a O
very O
small O
number O
of O
devices O
. O
This O
is O
known O
as O
a O
targeted O
attack O
. O
In O
this O
blog O
post O
, O
we O
describe O
Chrysaor B-Malware
, O
a O
newly O
discovered O
family O
of O
spyware O
that O
was O
used O
in O
a O
targeted O
attack O
on O
a O
small O
number O
of O
Android B-System
devices O
, O
and O
how O
investigations O
like O
this O
help O
Google B-Organization
protect O
Android B-System
users O
from O
a O
variety O
of O
threats O
. O
What O
is O
Chrysaor B-Malware
? O
Chrysaor B-Malware
is O
spyware O
believed O
to O
be O
created O
by O
NSO B-Organization
Group I-Organization
Technologies I-Organization
, O
specializing O
in O
the O
creation O
and O
sale O
of O
software O
and O
infrastructure O
for O
targeted O
attacks O
. O
Chrysaor B-Malware
is O
believed O
to O
be O
related O
to O
the O
Pegasus B-Malware
spyware O
that O
was O
first O
identified O
on O
iOS B-System
and O
analyzed O
by O
Citizen B-Organization
Lab I-Organization
and O
Lookout B-Organization
. O
Late O
last O
year O
, O
after O
receiving O
a O
list O
of O
suspicious O
package O
names O
from O
Lookout B-Organization
, O
we O
discovered O
that O
a O
few O
dozen O
Android B-System
devices O
may O
have O
installed O
an O
application O
related O
to O
Pegasus B-Malware
, O
which O
we O
named O
Chrysaor B-Malware
. O
Although O
the O
applications O
were O
never O
available O
in O
Google B-System
Play I-System
, O
we O
immediately O
identified O
the O
scope O
of O
the O
problem O
by O
using O
Verify B-System
Apps I-System
. O
We O
gathered O
information O
from O
affected O
devices O
, O
and O
concurrently O
, O
attempted O
to O
acquire O
Chrysaor B-Malware
apps O
to O
better O
understand O
its O
impact O
on O
users O
. O
We O
've O
contacted O
the O
potentially O
affected O
users O
, O
disabled O
the O
applications O
on O
affected O
devices O
, O
and O
implemented O
changes O
in O
Verify B-System
Apps I-System
to O
protect O
all O
users O
. O
What O
is O
the O
scope O
of O
Chrysaor B-Malware
? O
Chrysaor B-Malware
was O
never O
available O
in O
Google B-System
Play I-System
and O
had O
a O
very O
low O
volume O
of O
installs O
outside O
of O
Google B-System
Play I-System
. O
Among O
the O
over O
1.4 O
billion O
devices O
protected O
by O
Verify B-System
Apps I-System
, O
we O
observed O
fewer O
than O
3 O
dozen O
installs O
of O
Chrysaor B-Malware
on O
victim O
devices O
. O
These O
devices O
were O
located O
in O
the O
following O
countries O
: O
How O
we O
protect O
you O
To O
protect O
Android B-System
devices O
and O
users O
, O
Google B-System
Play I-System
provides O
a O
complete O
set O
of O
security O
services O
that O
update O
outside O
of O
platform O
releases O
. O
Users O
do O
n't O
have O
to O
install O
any O
additional O
security O
services O
to O
keep O
their O
devices O
safe O
. O
In O
2016 O
, O
these O
services O
protected O
over O
1.4 O
billion O
devices O
, O
making O
Google B-Organization
one O
of O
the O
largest O
providers O
of O
on-device O
security O
services O
in O
the O
world O
: O
Identify O
PHAs O
using O
people O
, O
systems O
in O
the O
cloud O
, O
and O
data O
sent O
to O
us O
from O
devices O
Warn O
users O
about O
or O
blocking O
users O
from O
installing O
PHAs O
Continually O
scan O
devices O
for O
PHAs O
and O
other O
harmful O
threats O
Additionally O
, O
we O
are O
providing O
detailed O
technical O
information O
to O
help O
the O
security O
industry O
in O
our O
collective O
work O
against O
PHAs O
. O
What O
do O
I O
need O
to O
do O
? O
It O
is O
extremely O
unlikely O
you O
or O
someone O
you O
know O
was O
affected O
by O
Chrysaor B-Malware
malware O
. O
Through O
our O
investigation O
, O
we O
identified O
less O
than O
3 O
dozen O
devices O
affected O
by O
Chrysaor B-Malware
, O
we O
have O
disabled O
Chrysaor B-Malware
on O
those O
devices O
, O
and O
we O
have O
notified O
users O
of O
all O
known O
affected O
devices O
. O
Additionally O
, O
the O
improvements O
we O
made O
to O
our O
protections O
have O
been O
enabled O
for O
all O
users O
of O
our O
security O
services O
. O
To O
ensure O
you O
are O
fully O
protected O
against O
PHAs O
and O
other O
threats O
, O
we O
recommend O
these O
5 O
basic O
steps O
: O
Install O
apps O
only O
from O
reputable O
sources O
: O
Install O
apps O
from O
a O
reputable O
source O
, O
such O
as O
Google B-System
Play I-System
. O
No O
Chrysaor B-Malware
apps O
were O
on O
Google B-System
Play I-System
. O
Enable O
a O
secure O
lock O
screen O
: O
Pick O
a O
PIN O
, O
pattern O
, O
or O
password O
that O
is O
easy O
for O
you O
to O
remember O
and O
hard O
for O
others O
to O
guess O
. O
Update O
your O
device O
: O
Keep O
your O
device O
up-to-date O
with O
the O
latest O
security O
patches O
. O
Verify O
Apps O
: O
Ensure O
Verify O
Apps O
is O
enabled O
. O
Locate O
your O
device O
: O
Practice O
finding O
your O
device O
with O
Android B-System
Device I-System
Manager I-System
because O
you O
are O
far O
more O
likely O
to O
lose O
your O
device O
than O
install O
a O
PHA O
. O
How O
does O
Chrysaor B-Malware
work O
? O
To O
install O
Chrysaor B-Malware
, O
we O
believe O
an O
attacker O
coaxed O
specifically O
targeted O
individuals O
to O
download O
the O
malicious O
software O
onto O
their O
device O
. O
Once O
Chrysaor B-Malware
is O
installed O
, O
a O
remote O
operator O
is O
able O
to O
surveil O
the O
victim O
's O
activities O
on O
the O
device O
and O
within O
the O
vicinity O
, O
leveraging O
microphone O
, O
camera O
, O
data O
collection O
, O
and O
logging O
and O
tracking O
application O
activities O
on O
communication O
apps O
such O
as O
phone O
and O
SMS O
. O
One O
representative O
sample O
Chrysaor B-Malware
app O
that O
we O
analyzed O
was O
tailored O
to O
devices O
running O
Jellybean B-System
( I-System
4.3 I-System
) I-System
or O
earlier O
. O
The O
following O
is O
a O
review O
of O
scope O
and O
impact O
of O
the O
Chrysaor B-Malware
app O
named O
com.network.android B-Indicator
tailored O
for O
a O
Samsung B-Organization
device O
target O
, O
with O
SHA256 O
digest O
: O
ade8bef0ac29fa363fc9afd958af0074478aef650adeb0318517b48bd996d5d5Upon B-Indicator
installation O
, O
the O
app O
uses O
known O
framaroot O
exploits O
to O
escalate O
privileges O
and O
break O
Android B-System
's O
application O
sandbox O
. O
If O
the O
targeted O
device O
is O
not O
vulnerable O
to O
these O
exploits O
, O
then O
the O
app O
attempts O
to O
use O
a O
superuser O
binary O
pre-positioned O
at O
/system/csk B-Indicator
to O
elevate O
privileges O
. O
After O
escalating O
privileges O
, O
the O
app O
immediately O
protects O
itself O
and O
starts O
to O
collect O
data O
, O
by O
: O
Installing O
itself O
on O
the O
/system O
partition O
to O
persist O
across O
factory O
resets O
Removing O
Samsung B-Organization
's O
system O
update O
app O
( O
com.sec.android.fotaclient B-Indicator
) O
and O
disabling O
auto-updates O
to O
maintain O
persistence O
( O
sets O
Settings.System.SOFTWARE_UPDATE_AUTO_UPDATE B-Indicator
to I-Indicator
0 I-Indicator
) O
Deleting O
WAP O
push O
messages O
and O
changing O
WAP O
message O
settings O
, O
possibly O
for O
anti-forensic O
purpose O
. O
Starting O
content O
observers O
and O
the O
main O
task O
loop O
to O
receive O
remote O
commands O
and O
exfiltrate O
data O
The O
app O
uses O
six O
techniques O
to O
collect O
user O
data O
: O
Repeated O
commands O
: O
use O
alarms O
to O
periodically O
repeat O
actions O
on O
the O
device O
to O
expose O
data O
, O
including O
gathering O
location O
data O
. O
Data O
collectors O
: O
dump O
all O
existing O
content O
on O
the O
device O
into O
a O
queue O
. O
Data O
collectors O
are O
used O
in O
conjunction O
with O
repeated O
commands O
to O
collect O
user O
data O
including O
, O
SMS O
settings O
, O
SMS O
messages O
, O
Call O
logs O
, O
Browser O
History O
, O
Calendar O
, O
Contacts O
, O
Emails O
, O
and O
messages O
from O
selected O
messaging O
apps O
, O
including O
WhatsApp B-System
, O
Twitter B-System
, O
Facebook B-System
, O
Kakoa B-System
, O
Viber B-System
, O
and O
Skype B-System
by O
making O
/data/data O
directories O
of O
the O
apps O
world O
readable O
. O
Content O
observers O
: O
use O
Android B-System
's O
ContentObserver O
framework O
to O
gather O
changes O
in O
SMS B-System
, O
Calendar B-System
, O
Contacts B-System
, O
Cell B-System
info I-System
, O
Email B-System
, O
WhatsApp B-System
, O
Facebook B-System
, O
Twitter B-System
, O
Kakao B-System
, O
Viber B-System
, O
and O
Skype B-System
. O
Screenshots O
: O
captures O
an O
image O
of O
the O
current O
screen O
via O
the O
raw O
frame O
buffer O
. O
Keylogging O
: O
record O
input O
events O
by O
hooking O
IPCThreadState O
: O
:Transact O
from O
/system/lib/libbinder.so B-Indicator
, O
and O
intercepting O
android B-Indicator
: I-Indicator
:parcel I-Indicator
with O
the O
interface O
com.android.internal.view.IInputContext B-Indicator
. O
RoomTap O
: O
silently O
answers O
a O
telephone O
call O
and O
stays O
connected O
in O
the O
background O
, O
allowing O
the O
caller O
to O
hear O
conversations O
within O
the O
range O
of O
the O
phone O
's O
microphone O
. O
If O
the O
user O
unlocks O
their O
device O
, O
they O
will O
see O
a O
black O
screen O
while O
the O
app O
drops O
the O
call O
, O
resets O
call O
settings O
and O
prepares O
for O
the O
user O
to O
interact O
with O
the O
device O
normally O
. O
Finally O
, O
the O
app O
can O
remove O
itself O
through O
three O
ways O
: O
Via O
a O
command O
from O
the O
server O
Autoremove O
if O
the O
device O
has O
not O
been O
able O
to O
check O
in O
to O
the O
server O
after O
60 O
days O
Via O
an O
antidote O
file O
. O
If O
/sdcard/MemosForNotes B-Indicator
was O
present O
on O
the O
device O
, O
the O
Chrysaor B-Malware
app O
removes O
itself O
from O
the O
device O
. O
Samples O
uploaded O
to O
VirusTotal B-Organization
To O
encourage O
further O
research O
in O
the O
security O
community O
, O
we O
’ O
ve O
uploaded O
these O
sample O
Chrysaor B-Malware
apps O
to O
Virus B-Organization
Total I-Organization
. O
Package O
Name O
SHA256 O
digest O
SHA1 O
certificate O
com.network.android B-Indicator
ade8bef0ac29fa363fc9afd958af0074478aef650adeb0318517b48bd996d5d5 B-Indicator
44f6d1caa257799e57f0ecaf4e2e216178f4cb3d B-Indicator
com.network.android B-Indicator
3474625e63d0893fc8f83034e835472d95195254e1e4bdf99153b7c74eb44d86 B-Indicator
516f8f516cc0fd8db53785a48c0a86554f75c3ba B-Indicator
Additional O
digests O
with O
links O
to O
Chrysaor B-Malware
As O
a O
result O
of O
our O
investigation O
we O
have O
identified O
these O
additional O
Chrysaor-related B-Malware
apps O
. O
Package O
Name O
SHA256 O
digest O
SHA1 O
certificate O
com.network.android B-Indicator
98ca5f94638768e7b58889bb5df4584bf5b6af56b188da48c10a02648791b30c B-Indicator
516f8f516cc0fd8db53785a48c0a86554f75c3ba B-Indicator
com.network.android B-Indicator
5353212b70aa096d918e4eb6b49eb5ad8f59d9bec02d089e88802c01e707c3a1 B-Indicator
44f6d1caa257799e57f0ecaf4e2e216178f4cb3d B-Indicator
com.binary.sms.receiver B-Indicator
9fae5d148b89001555132c896879652fe1ca633d35271db34622248e048c78ae B-Indicator
7771af1ad3a3d9c0b4d9b55260bb47c2692722cf B-Indicator
com.android.copy B-Indicator
e384694d3d17cd88ec3a66c740c6398e07b8ee401320ca61e26bdf96c20485b4 B-Indicator
7771af1ad3a3d9c0b4d9b55260bb47c2692722cf B-Indicator
com.android.copy B-Indicator
12e085ab85db887438655feebd249127d813e31df766f8c7b009f9519916e389 B-Indicator
7771af1ad3a3d9c0b4d9b55260bb47c2692722cf B-Indicator
com.android.copy B-Indicator
6348104f8ef22eba5ac8ee737b192887629de987badbb1642e347d0dd01420f8 B-Indicator
31a8633c2cd67ae965524d0b2192e9f14d04d016 B-Indicator
FinFisher B-Malware
exposed O
: O
A O
researcher O
’ O
s O
tale O
of O
defeating O
traps O
, O
tricks O
, O
and O
complex O
virtual O
machines O
March O
1 O
, O
2018 O
Office B-System
365 I-System
Advanced I-System
Threat I-System
Protection I-System
( O
Office B-System
365 I-System
ATP I-System
) O
blocked O
many O
notable O
zero-day O
exploits O
in O
2017 O
. O
In O
our O
analysis O
, O
one O
activity O
group O
stood O
out O
: O
NEODYMIUM B-Malware
. O
This O
threat O
actor O
is O
remarkable O
for O
two O
reasons O
: O
Its O
access O
to O
sophisticated O
zero-day O
exploits O
for O
Microsoft B-Organization
and O
Adobe B-Organization
software O
Its O
use O
of O
an O
advanced O
piece O
of O
government-grade O
surveillance O
spyware O
FinFisher B-Malware
, O
also O
known O
as O
FinSpy B-Malware
and O
detected O
by O
Microsoft B-Organization
security O
products O
as O
Wingbird B-Malware
FinFisher B-Malware
is O
such O
a O
complex O
piece O
of O
malware O
that O
, O
like O
other O
researchers O
, O
we O
had O
to O
devise O
special O
methods O
to O
crack O
it O
. O
We O
needed O
to O
do O
this O
to O
understand O
the O
techniques O
FinFisher B-Malware
uses O
to O
compromise O
and O
persist O
on O
a O
machine O
, O
and O
to O
validate O
the O
effectiveness O
of O
Office B-System
365 I-System
ATP I-System
detonation O
sandbox O
, O
Windows B-System
Defender I-System
Advanced I-System
Threat I-System
Protection I-System
( O
Windows B-System
Defender I-System
ATP I-System
) O
generic O
detections O
, O
and O
other O
Microsoft B-Organization
security O
solutions O
. O
This O
task O
proved O
to O
be O
nontrivial O
. O
FinFisher B-Malware
is O
not O
afraid O
of O
using O
all O
kinds O
of O
tricks O
, O
ranging O
from O
junk O
instructions O
and O
“ O
spaghetti O
code O
” O
to O
multiple O
layers O
of O
virtual O
machines O
and O
several O
known O
and O
lesser-known O
anti-debug O
and O
defensive O
measures O
. O
Security O
analysts O
are O
typically O
equipped O
with O
the O
tools O
to O
defeat O
a O
good O
number O
of O
similar O
tricks O
during O
malware O
investigations O
. O
However O
, O
FinFisher B-Malware
is O
in O
a O
different O
category O
of O
malware O
for O
the O
level O
of O
its O
anti-analysis O
protection O
. O
It O
’ O
s O
a O
complicated O
puzzle O
that O
can O
be O
solved O
by O
skilled O
reverse O
engineers O
only O
with O
good O
amount O
of O
time O
, O
code O
, O
automation O
, O
and O
creativity O
. O
The O
intricate O
anti-analysis O
methods O
reveal O
how O
much O
effort O
the O
FinFisher B-Malware
authors O
exerted O
to O
keep O
the O
malware O
hidden O
and O
difficult O
to O
analyze O
. O
This O
exercise O
revealed O
tons O
of O
information O
about O
techniques O
used O
by O
FinFisher B-Malware
that O
we O
used O
to O
make O
Office B-System
365 I-System
ATP I-System
more O
resistant O
to O
sandbox O
detection O
and O
Windows B-System
Defender I-System
ATP I-System
to O
catch O
similar O
techniques O
and O
generic O
behaviors O
. O
Using O
intelligence O
from O
our O
in-depth O
investigation O
, O
Windows B-System
Defender I-System
ATP I-System
can O
raise O
alerts O
for O
malicious O
behavior O
employed O
by O
FinFisher B-Malware
( O
such O
as O
memory O
injection O
in O
persistence O
) O
in O
different O
stages O
of O
the O
attack O
kill O
chain O
. O
Machine O
learning O
in O
Windows B-System
Defender I-System
ATP I-System
further O
flags O
suspicious O
behaviors O
observed O
related O
to O
the O
manipulation O
of O
legitimate O
Windows B-System
binaries O
. O
Figure O
1 O
. O
Generic O
Windows B-System
Defender I-System
ATP I-System
detections O
trigger O
alerts O
on O
FinFisher B-Malware
behavior O
While O
our O
analysis O
has O
allowed O
us O
to O
immediately O
protect O
our O
customers O
, O
we O
’ O
d O
like O
to O
share O
our O
insights O
and O
add O
to O
the O
growing O
number O
of O
published O
analyses O
by O
other O
talented O
researchers O
( O
listed O
below O
this O
blog O
post O
) O
. O
We O
hope O
that O
this O
blog O
post O
helps O
other O
researchers O
to O
understand O
and O
analyze O
FinFisher B-Malware
samples O
and O
that O
this O
industry-wide O
information-sharing O
translate O
to O
the O
protection O
of O
as O
many O
customers O
as O
possible O
. O
Spaghetti O
and O
junk O
codes O
make O
common O
analyst O
tools O
ineffective O
In O
analyzing O
FinFisher B-Malware
, O
the O
first O
obfuscation O
problem O
that O
requires O
a O
solution O
is O
the O
removal O
of O
junk O
instructions O
and O
“ O
spaghetti O
code O
” O
, O
which O
is O
a O
technique O
that O
aims O
to O
confuse O
disassembly O
programs O
. O
Spaghetti O
code O
makes O
the O
program O
flow O
hard O
to O
read O
by O
adding O
continuous O
code O
jumps O
, O
hence O
the O
name O
. O
An O
example O
of O
FinFisher B-Malware
’ O
s O
spaghetti O
code O
is O
shown O
below O
. O
Figure O
2 O
. O
The O
spaghetti O
code O
in O
FinFisher B-Malware
dropper O
This O
problem O
is O
not O
novel O
, O
and O
in O
common O
situations O
there O
are O
known O
reversing O
plugins O
that O
may O
help O
for O
this O
task O
. O
In O
the O
case O
of O
FinFisher B-Malware
, O
however O
, O
we O
could O
not O
find O
a O
good O
existing O
interactive O
disassembler O
( O
IDA O
) O
plugin O
that O
can O
normalize O
the O
code O
flow O
. O
So O
we O
decided O
to O
write O
our O
own O
plugin O
code O
using O
IDA O
Python B-System
. O
Armed O
with O
this O
code O
, O
we O
removed O
this O
first O
layer O
of O
anti-analysis O
protection O
. O
Removing O
the O
junk O
instructions O
revealed O
a O
readable O
block O
of O
code O
. O
This O
code O
starts O
by O
allocating O
two O
chunks O
of O
memory O
: O
a O
global O
1 O
MB O
buffer O
and O
one O
64 O
KB O
buffer O
per O
thread O
. O
The O
big O
first O
buffer O
is O
used O
as O
index O
for O
multiple O
concurrent O
threads O
. O
A O
big O
chunk O
of O
data O
is O
extracted O
from O
the O
portable O
executable O
( O
PE O
) O
file O
itself O
and O
decrypted O
two O
times O
using O
a O
custom O
XOR O
algorithm O
. O
We O
determined O
that O
this O
chunk O
of O
data O
contains O
an O
array O
of O
opcode O
instructions O
ready O
to O
be O
interpreted O
by O
a O
custom O
virtual O
machine O
program O
( O
from O
this O
point O
on O
referenced O
generically O
as O
“ O
VM O
” O
) O
implemented O
by O
FinFisher B-Malware
authors O
. O
Figure O
3 O
. O
The O
stages O
of O
the O
FinFisher B-Malware
multi-layered O
protection O
mechanisms O
Stage O
0 O
: O
Dropper O
with O
custom O
virtual O
machine O
The O
main O
dropper O
implements O
the O
VM O
dispatcher O
loop O
and O
can O
use O
32 O
different O
opcodes O
handlers O
. O
Th O
64KB O
buffer O
is O
used O
as O
a O
VM O
descriptor O
data O
structure O
to O
store O
data O
and O
the O
just-in-time O
( O
JIT O
) O
generated O
code O
to O
run O
. O
The O
VM O
dispatcher O
loop O
routine O
ends O
with O
a O
JMP O
to O
another O
routine O
. O
In O
total O
, O
there O
are O
32 O
different O
routines O
, O
each O
of O
them O
implementing O
a O
different O
opcode O
and O
some O
basic O
functionality O
that O
the O
malware O
program O
may O
execute O
. O
Figure O
4 O
. O
A O
snapshot B-Malware
of O
the O
code O
that O
processes O
each O
VM O
opcode O
and O
the O
associate O
interpreter O
The O
presence O
of O
a O
VM O
and O
virtualized O
instruction O
blocks O
can O
be O
described O
in O
simpler O
terms O
: O
Essentially O
, O
the O
creators O
of O
FinFisher B-Malware
interposed O
a O
layer O
of O
dynamic O
code O
translation O
( O
the O
virtual O
machine O
) O
that O
makes O
analysis O
using O
regular O
tools O
practically O
impossible O
. O
Static O
analysis O
tools O
like O
IDA O
may O
not O
be O
useful O
in O
analyzing O
custom O
code O
that O
is O
interpreted O
and O
executed O
through O
a O
VM O
and O
a O
new O
set O
of O
instructions O
. O
On O
the O
other O
hand O
, O
dynamic O
analysis O
tools O
( O
like O
debuggers O
or O
sandbox O
) O
face O
the O
anti-debug O
and O
anti-analysis O
tricks O
hidden O
in O
the O
virtualized O
code O
itself O
that O
detects O
sandbox O
environments O
and O
alters O
the O
behavior O
of O
the O
malware O
. O
At O
this O
stage O
, O
the O
analysis O
can O
only O
continue O
by O
manually O
investigating O
the O
individual O
code O
blocks O
and O
opcode O
handlers O
, O
which O
are O
highly O
obfuscated O
( O
also O
using O
spaghetti O
code O
) O
. O
Reusing O
our O
deobfuscation O
tool O
and O
some O
other O
tricks O
, O
we O
have O
been O
able O
to O
reverse O
and O
analyze O
these O
opcodes O
and O
map O
them O
to O
a O
finite O
list O
that O
can O
be O
used O
later O
to O
automate O
the O
analysis O
process O
with O
some O
scripting O
. O
The O
opcode O
instructions O
generated O
by O
this O
custom O
VM O
are O
divided O
into O
different O
categories O
: O
Logical O
opcodes O
, O
which O
implement O
bit-logic O
operators O
( O
OR O
, O
AND O
, O
NOT O
, O
XOR O
) O
and O
mathematical O
operators O
Conditional O
branching O
opcodes O
, O
which O
implement O
a O
code O
branch O
based O
on O
conditions O
( O
equals O
to O
JC O
, O
JE O
, O
JZ O
, O
other O
similar O
branching O
opcodes O
) O
Load/Store O
opcodes O
, O
which O
write O
to O
or O
read O
from O
particular O
addresses O
of O
the O
virtual O
address O
space O
of O
the O
process O
Specialized O
opcodes O
for O
various O
purposes O
, O
like O
execute O
specialized O
machine O
instruction O
that O
are O
not O
virtualized O
We O
are O
publishing O
below O
the O
( O
hopefully O
) O
complete O
list O
of O
opcodes O
used O
by O
FinFisher B-Malware
VM O
that O
we O
found O
during O
our O
analysis O
and O
integrated O
into O
our O
de-virtualization O
script O
: O
INDEX O
MNEMONIC O
DESCRIPTION O
0x0 O
EXEC O
Execute O
machine O
code O
0x1 O
JG O
Jump O
if O
greater/Jump O
if O
not O
less O
or O
equal O
0x2 O
WRITE O
Write O
a O
value O
into O
the O
dereferenced O
internal O
VM O
value O
( O
treated O
as O
a O
pointer O
) O
0x3 O
JNO O
Jump O
if O
not O
overflow O
0x4 O
JLE O
Jump O
if O
less O
or O
equal O
( O
signed O
) O
0x5 O
MOV O
Move O
the O
value O
of O
a O
register O
into O
the O
VM O
descriptor O
( O
same O
as O
opcode O
0x1F O
) O
0x6 O
JO O
Jump O
if O
overflow O
0x7 O
PUSH O
Push O
the O
internal O
VM O
value O
to O
the O
stack O
0x8 O
ZERO O
Reset O
the O
internal O
VM O
value O
to O
0 O
( O
zero O
) O
0x9 O
JP O
Jump O
if O
parity O
even O
0xA O
WRITE O
Write O
into O
an O
address O
0xB O
ADD O
Add O
the O
value O
of O
a O
register O
to O
the O
internal O
VM O
value O
0xC O
JNS O
Jump O
if O
not O
signed O
0xD O
JL O
Jump O
if O
less O
( O
signed O
) O
0xE O
EXEC O
Execute O
machine O
code O
and O
branch O
0xF O
JBE O
Jump O
if O
below O
or O
equal O
or O
Jump O
if O
not O
above O
0x10 O
SHL O
Shift O
left O
the O
internal O
value O
the O
number O
of O
times O
specified O
into O
the O
opcodes O
0x11 O
JA O
Jump O
if O
above/Jump O
if O
not O
below O
or O
equal O
0x12 O
MOV O
Move O
the O
internal O
VM O
value O
into O
a O
register O
0x13 O
JZ O
JMP O
if O
zero O
0x14 O
ADD O
Add O
an O
immediate O
value O
to O
the O
internal O
Vm O
descriptor O
0x15 O
JB O
Jump O
if O
below O
( O
unsigned O
) O
0x16 O
JS O
Jump O
if O
signed O
0x17 O
EXEC O
Execute O
machine O
code O
( O
same O
as O
opcode O
0x0 O
) O
0x18 O
JGE O
Jump O
if O
greater O
or O
equal/Jump O
if O
not O
less O
0x19 O
DEREF O
Write O
a O
register O
value O
into O
a O
dereferenced O
pointer O
0x1A O
JMP O
Special O
obfuscated O
“ O
Jump O
if O
below O
” O
opcode O
0x1B O
* O
Resolve O
a O
pointer O
0x1C O
LOAD O
Load O
a O
value O
into O
the O
internal O
VM O
descriptor O
0x1D O
JNE O
Jump O
if O
not O
equal/Jump O
if O
not O
zero O
0x1E O
CALL O
Call O
an O
external O
function O
or O
a O
function O
located O
in O
the O
dropper O
0x1F O
MOV O
Move O
the O
value O
of O
a O
register O
into O
the O
VM O
descriptor O
0x20 O
JNB O
Jump O
if O
not O
below/Jump O
if O
above O
or O
equal/Jump O
if O
not O
carry O
0x21 O
JNP O
Jump O
if O
not O
parity/Jump O
if O
parity O
odd O
Each O
virtual O
instruction O
is O
stored O
in O
a O
special O
data O
structure O
that O
contains O
all O
the O
information O
needed O
to O
be O
properly O
read O
and O
executed O
by O
the O
VM O
. O
This O
data O
structure O
is O
24 O
bytes O
and O
is O
composed O
of O
some O
fixed O
fields O
and O
a O
variable O
portion O
that O
depends O
on O
the O
opcode O
. O
Before O
interpreting O
the O
opcode O
, O
the O
VM O
decrypts O
the O
opcode O
’ O
s O
content O
( O
through O
a O
simple O
XOR O
algorithm O
) O
, O
which O
it O
then O
relocates O
( O
if O
needed O
) O
, O
using O
the O
relocation O
fields O
. O
Here O
is O
an O
approximate O
diagram O
of O
the O
opcode O
data O
structure O
: O
Figure O
5 O
. O
A O
graphical O
representation O
of O
the O
data O
structure O
used O
to O
store O
each O
VM O
opcode O
The O
VM O
handler O
is O
completely O
able O
to O
generate O
different O
code O
blocks O
and O
deal O
with O
relocated O
code O
due O
to O
address O
space O
layout O
randomization O
( O
ASLR O
) O
. O
It O
is O
also O
able O
to O
move O
code O
execution O
into O
different O
locations O
if O
needed O
. O
For O
instance O
, O
in O
the O
case O
of O
the O
“ O
Execute O
” O
opcode O
( O
0x17 O
) O
, O
the O
32-bit O
code O
to O
run O
is O
stored O
entirely O
into O
the O
variable O
section O
with O
the O
value O
at O
offset O
5 O
specifying O
the O
number O
of O
bytes O
to O
be O
copied O
and O
executed O
. O
Otherwise O
, O
in O
the O
case O
of O
conditional O
opcodes O
, O
the O
variable O
part O
can O
contain O
the O
next O
JIT O
packet O
ID O
or O
the O
next O
relative O
virtual O
address O
( O
RVA O
) O
where O
code O
execution O
should O
continue O
. O
Of O
course O
, O
not O
all O
the O
opcodes O
are O
can O
be O
easily O
read O
and O
understood O
due O
to O
additional O
steps O
that O
the O
authors O
have O
taken O
to O
make O
analysis O
extremely O
complicated O
. O
For O
example O
, O
this O
is O
how O
opcode O
0x1A O
is O
implemented O
: O
The O
opcode O
should O
represent O
a O
JB O
( O
Jump O
if O
below O
) O
function O
, O
but O
it O
’ O
s O
implemented O
through O
set O
carry O
( O
STC O
) O
instruction O
followed O
by O
a O
JMP O
into O
the O
dispatcher O
code O
that O
will O
verify O
the O
carry O
flag O
condition O
set O
by O
STC O
. O
Figure O
6 O
. O
One O
of O
the O
obfuscation O
tricks O
included O
by O
the O
malware O
authors O
in O
a O
VM O
opcode O
dispatcher O
Even O
armed O
with O
the O
knowledge O
we O
have O
described O
so O
far O
, O
it O
still O
took O
us O
many O
hours O
to O
write O
a O
full-fledged O
opcode O
interpreter O
that O
’ O
s O
able O
to O
reconstruct O
the O
real O
code O
executed O
by O
FinFisher B-Malware
. O
Stage O
1 O
: O
Loader O
malware O
keeps O
sandbox O
and O
debuggers O
away O
The O
first O
stage O
of O
FinFisher B-Malware
running O
through O
this O
complicated O
virtual O
machine O
is O
a O
loader O
malware O
designed O
to O
probe O
the O
system O
and O
determine O
whether O
it O
’ O
s O
running O
in O
a O
sandbox O
environment O
( O
typical O
for O
cloud-based O
detonation O
solution O
like O
Office B-System
365 I-System
ATP I-System
) O
. O
The O
loader O
first O
dynamically O
rebuilds O
a O
simple O
import O
address O
table O
( O
IAT O
) O
, O
resolving O
all O
the O
API O
needed O
from O
Kernel32 O
and O
NtDll O
libraries O
. O
It O
then O
continues O
executing O
in O
a O
spawned O
new O
thread O
that O
checks O
if O
there O
are O
additional O
undesired O
modules O
inside O
its O
own O
virtual O
address O
space O
( O
for O
example O
, O
modules O
injected O
by O
certain O
security O
solutions O
) O
. O
It O
eventually O
kills O
all O
threads O
that O
belong O
to O
these O
undesired O
modules O
( O
using O
ZwQueryInformationThread O
native O
API O
with O
ThreadQuerySetWin32StartAddress O
information O
class O
) O
. O
The O
first O
anti-sandbox O
technique O
is O
the O
loader O
checking O
the O
code O
segment O
. O
If O
it O
’ O
s O
not O
0x1B O
( O
for O
32-bit O
systems O
) O
or O
0x23 O
( O
for O
32-bit O
system O
under O
Wow64 O
) O
, O
the O
loader O
exits O
. O
Next O
, O
the O
dropper O
checks O
its O
own O
parent O
process O
for O
indications O
that O
it O
is O
running O
in O
a O
sandbox O
setup O
. O
It O
calculates O
the O
MD5 O
hash O
of O
the O
lower-case O
process O
image O
name O
and O
terminates O
if O
one O
of O
the O
following O
conditions O
are O
met O
: O
The O
MD5 O
hash O
of O
the O
parent O
process O
image O
name O
is O
either O
D0C4DBFA1F3962AED583F6FCE666F8BC B-Indicator
or O
3CE30F5FED4C67053379518EACFCF879 B-Indicator
The O
parent O
process O
’ O
s O
full O
image O
path O
is O
equal O
to O
its O
own O
process O
path O
If O
these O
initial O
checks O
are O
passed O
, O
the O
loader O
builds O
a O
complete O
IAT O
by O
reading O
four O
imported O
libraries O
from O
disk O
( O
ntdll.dll B-Indicator
, O
kernel32.dll B-Indicator
, O
advapi32.dll B-Indicator
, O
and O
version.dll B-Indicator
) O
and O
remapping O
them O
in O
memory O
. O
This O
technique O
makes O
use O
of O
debuggers O
and O
software O
breakpoints O
useless O
. O
During O
this O
stage O
, O
the O
loader O
may O
also O
call O
a O
certain O
API O
using O
native O
system O
calls O
, O
which O
is O
another O
way O
to O
bypass O
breakpoints O
on O
API O
and O
security O
solutions O
using O
hooks O
. O
Figure O
7 O
. O
FinFisher B-Malware
loader O
calling O
native O
Windows B-System
API O
to O
perform O
anti-debugging O
tricks O
At O
this O
point O
, O
the O
fun O
in O
analysis O
is O
not O
over O
. O
A O
lot O
of O
additional O
anti-sandbox O
checks O
are O
performed O
in O
this O
exact O
order O
: O
Check O
that O
the O
malware O
is O
not O
executed O
under O
the O
root O
folder O
of O
a O
drive O
Check O
that O
the O
malware O
file O
is O
readable O
from O
an O
external O
source O
Check O
that O
the O
hash O
of O
base O
path O
is O
not O
3D6D62AF1A7C8053DBC8E110A530C679 B-Indicator
Check O
that O
the O
full O
malware O
path O
contains O
only O
human O
readable O
characters O
( O
“ O
a-z O
” O
, O
“ O
A-Z O
” O
, O
and O
“ O
0-9 O
” O
) O
Check O
that O
no O
node O
in O
the O
full O
path O
contains O
the O
MD5 O
string O
of O
the O
malware O
file O
Fingerprint O
the O
system O
and O
check O
the O
following O
registry O
values O
: O
HKLM\SOFTWARE\Microsoft\Cryptography\MachineGuid B-Indicator
should O
not O
be O
“ O
6ba1d002-21ed-4dbe-afb5-08cf8b81ca32 B-Indicator
” O
HKLM\SOFTWARE\Microsoft\Windows B-Indicator
NT\CurrentVersion\DigitalProductId I-Indicator
should O
not O
be O
“ O
55274-649-6478953-23109 B-Indicator
” O
, O
“ O
A22-00001 B-Indicator
” O
, O
or O
“ O
47220 B-Indicator
” O
HARDWARE\Description\System\SystemBiosDate B-Indicator
should O
not O
contain O
“ O
01/02/03 O
” O
Check O
that O
the O
mutex O
WininetStartupMutex0 O
does O
not O
already O
exist O
Check O
that O
no O
DLL O
whose O
base O
name O
has O
hash O
value O
of O
0xC9CEF3E4 B-Indicator
is O
mapped O
into O
the O
malware O
address O
space O
The O
hashes O
in O
these O
checks O
are O
most O
likely O
correspond O
to O
sandbox O
or O
security O
products O
that O
the O
FinFisher B-Malware
authors O
want O
to O
avoid O
. O
Next O
, O
the O
loader O
checks O
that O
it O
’ O
s O
not O
running O
in O
a O
virtualized O
environment O
( O
VMWare B-System
or O
Hyper-V B-System
) O
or O
under O
a O
debugger O
. O
For O
the O
hardware O
virtualization O
check O
, O
the O
loader O
obtains O
the O
hardware O
device O
list O
and O
checks O
if O
the O
MD5 O
of O
the O
vendor O
ID O
is O
equal O
to O
a O
predefined O
list O
. O
In O
our O
tests O
, O
the O
malware O
sample O
was O
able O
to O
easily O
detect O
both O
VMWare B-System
and O
Hyper-V B-System
environments O
through O
the O
detection O
of O
the O
virtualized O
peripherals O
( O
for O
example O
, O
Vmware B-Organization
has O
VEN_15AD O
as O
vendor O
ID O
, O
HyperV O
has O
VMBus O
as O
bus O
name O
) O
. O
Office B-System
365 I-System
ATP I-System
sandbox O
employs O
special O
mechanisms O
to O
avoid O
being O
detected O
by O
similar O
checks O
. O
The O
loader O
’ O
s O
anti-debugger O
code O
is O
based O
on O
the O
following O
three O
methods O
: O
The O
first O
call O
aims O
to O
destroy O
the O
debugger O
connection O
: O
NOTE O
: O
This O
call O
completely O
stops O
the O
execution O
of O
WinDbg O
and O
other O
debuggers O
The O
second O
call O
tries O
to O
detect O
the O
presence O
of O
a O
debugger O
: O
The O
final O
call O
tries O
to O
destroy O
the O
possibility O
of O
adding O
software O
breakpoint O
: O
Finally O
, O
if O
the O
loader O
is O
happy O
with O
all O
the O
checks O
done O
so O
far O
, O
based O
on O
the O
victim O
operating O
system O
( O
32 O
or O
64-bit O
) O
it O
proceeds O
to O
decrypt O
a O
set O
of O
fake O
bitmap O
resources O
( O
stage O
2 O
) O
embedded O
in O
the O
executable O
and O
prepares O
the O
execution O
of O
a O
new O
layer O
of O
VM O
decoding O
. O
Each O
bitmap O
resource O
is O
extracted O
, O
stripped O
of O
the O
first O
0x428 O
bytes O
( O
BMP O
headers O
and O
garbage O
data O
) O
, O
and O
combined O
into O
one O
file O
. O
The O
block O
is O
decrypted O
using O
a O
customized O
algorithm O
that O
uses O
a O
key O
derived O
from O
the O
original O
malware O
dropper O
’ O
s O
TimeDateStamp O
field O
multiplied O
by O
5 O
. O
Figure O
8 O
. O
The O
fake O
bitmap O
image O
embedded O
as O
resource O
The O
32-bit O
stage O
2 O
malware O
uses O
a O
customized O
loading O
mechanism O
( O
i.e. O
, O
the O
PE O
file O
has O
a O
scrambled O
IAT O
and O
relocation O
table O
) O
and O
exports O
only O
one O
function O
. O
For O
the O
64-bit O
stage O
2 O
malware O
, O
the O
code O
execution O
is O
transferred O
from O
the O
loader O
using O
a O
well-known O
technique O
called O
Heaven O
’ O
s O
Gate O
. O
In O
the O
next O
sections O
, O
for O
simplicity O
, O
we O
will O
continue O
the O
analysis O
only O
on O
the O
64-bit O
payload O
. O
Figure O
9 O
. O
Heaven O
’ O
s O
gate O
is O
still O
in O
use O
in O
2017 O
Stage O
2 O
: O
A O
second O
multi-platform O
virtual O
machine O
The O
64-bit O
stage O
2 O
malware O
implements O
another O
loader O
combined O
with O
another O
virtual O
machine O
. O
The O
architecture O
is O
quite O
similar O
to O
the O
one O
described O
previously O
, O
but O
the O
opcodes O
are O
slightly O
different O
. O
After O
reversing O
these O
opcodes O
, O
we O
were O
able O
to O
update O
our O
interpreter O
script O
to O
support O
both O
32-bit O
and O
64-bit O
virtual O
machines O
used O
by O
FinFisher B-Malware
. O
INDEX O
MNEMONIC O
DESCRIPTION O
0x0 O
JMP O
Special O
obfuscated O
conditional O
Jump O
( O
always O
taken O
or O
always O
ignored O
) O
0x1 O
JMP O
Jump O
to O
a O
function O
( O
same O
as O
opcode O
0x10 O
) O
0x2 O
CALL O
Call O
to O
the O
function O
pointed O
by O
the O
internal O
VM O
value O
0x3 O
CALL O
Optimized O
CALL O
function O
( O
like O
the O
0x1E O
opcode O
of O
the O
32-bit O
VM O
) O
0x4 O
EXEC O
Execute O
code O
and O
move O
to O
the O
next O
packet O
0x5 O
JMP O
Jump O
to O
an O
internal O
function O
0x6 O
NOP O
No O
operation O
, O
move O
to O
the O
next O
packet O
0x7 O
CALL O
Call O
an O
imported O
API O
( O
whose O
address O
is O
stored O
in O
the O
internal O
VM O
value O
) O
0x8 O
LOAD O
Load O
a O
value O
into O
the O
VM O
descriptor O
structure O
* O
0x9 O
STORE O
Store O
the O
internal O
VM O
value O
inside O
a O
register O
0xA O
WRITE O
Resolve O
a O
pointer O
and O
store O
the O
value O
of O
a O
register O
in O
its O
content O
0xB O
READ O
Move O
the O
value O
pointed O
by O
the O
VM O
internal O
value O
into O
a O
register O
0xC O
LOAD O
Load O
a O
value O
into O
the O
VM O
descriptor O
structure O
( O
not O
optimized O
) O
0xD O
CMP O
Compare O
the O
value O
pointed O
by O
the O
internal O
VM O
descriptor O
with O
a O
register O
0xE O
CMP O
Compare O
the O
value O
pointed O
by O
the O
internal O
VM O
descriptor O
with O
an O
immediate O
value O
0xF O
XCHG O
Exchange O
the O
value O
pointed O
by O
the O
internal O
VM O
descriptor O
with O
a O
register O
0x10 O
SHL O
Jump O
to O
a O
function O
( O
same O
as O
opcode O
0x1 O
) O
This O
additional O
virtual O
machine O
performs O
the O
same O
duties O
as O
the O
one O
already O
described O
but O
in O
a O
64-bit O
environment O
. O
It O
extracts O
and O
decrypts O
the O
stage O
3 O
malware O
, O
which O
is O
stored O
in O
encrypted O
resources O
such O
as O
fake O
dialog O
boxes O
. O
The O
extraction O
method O
is O
the O
same O
, O
but O
the O
encryption O
algorithm O
( O
also O
XOR O
) O
is O
much O
simpler O
. O
The O
new O
payload O
is O
decrypted O
, O
remapped O
, O
and O
executed O
in O
memory O
, O
and O
represents O
the O
installation O
and O
persistence O
stage O
of O
the O
malware O
. O
Stage O
3 O
: O
Installer O
that O
takes O
DLL O
side-loading O
to O
a O
new O
level O
Stage O
3 O
represents O
the O
setup O
program O
for O
FinFisher B-Malware
. O
It O
is O
the O
first O
plain O
stage O
that O
does O
not O
employ O
a O
VM O
or O
obfuscation O
. O
The O
code O
supports O
two O
different O
installation O
methods O
: O
setup O
in O
a O
UAC-enforced B-System
environment I-System
( O
with O
limited O
privileges O
) O
, O
or O
an O
installation O
with O
full-administrative O
privileges O
enabled O
( O
in O
cases O
where O
the O
malware O
gains O
the O
ability O
to O
run O
with O
elevated O
permissions O
) O
. O
We O
were O
a O
bit O
disappointed O
that O
we O
did O
not O
see O
traces O
of O
a O
true O
privilege B-Vulnerability
escalation I-Vulnerability
exploit I-Vulnerability
after O
all O
this O
deobfuscation O
work O
, O
but O
it O
seems O
these O
FinFisher B-Malware
samples O
were O
designed O
to O
work O
just O
using O
UAC O
bypasses O
. O
The O
setup O
code O
receives O
an O
installation O
command O
from O
the O
previous O
stage O
. O
In O
our O
test O
, O
this O
command O
was O
the O
value O
3 O
. O
The O
malware O
creates O
a O
global O
event O
named O
0x0A7F1FFAB12BB2 B-Indicator
and O
drops O
some O
files O
under O
a O
folder O
located O
in O
C B-Indicator
: I-Indicator
\ProgramData I-Indicator
or O
in O
the O
user O
application O
data O
folder O
. O
The O
name O
of O
the O
folder O
and O
the O
malware O
configuration O
are O
read O
from O
a O
customized O
configuration O
file O
stored O
in O
the O
resource O
section O
of O
the O
setup O
program O
. O
Here O
the O
list O
of O
the O
files O
potentially O
dropped O
during O
the O
installation O
stage O
: O
FILE O
NAME O
STAGE O
DESCRIPTION O
d3d9.dll B-Indicator
Stage O
4 O
Malware O
loader O
used O
for O
UAC O
environments O
with O
limited O
privileges O
; O
also O
protected O
by O
VM O
obfuscation O
aepic.dll B-Indicator
, O
sspisrv.dll B-Indicator
, O
userenv.dll B-Indicator
Stage O
4 O
Malware O
loader O
used O
in O
presence O
of O
administrative O
privileges O
; O
executed O
from O
( O
and O
injected O
into O
) O
a O
fake O
service O
; O
also O
protected O
by O
VM O
obfuscation O
msvcr90.dll B-Indicator
Stage O
5 O
Malware O
payload O
injected O
into O
the O
explorer.exe B-Indicator
or O
winlogon.exe B-Indicator
process O
; O
also O
protected O
by O
VM O
obfuscation O
.cab O
Config O
Main O
configuration O
file O
; O
encrypted O
setup.cab B-Indicator
Unknown O
Last O
section O
of O
the O
setup O
executable O
; O
content O
still O
unknown O
.7z O
Plugin O
Malware O
plugin O
used O
to O
spy O
the O
victim O
network O
communications O
wsecedit.rar B-Indicator
Stage O
6 O
Main O
malware O
executable O
After O
writing O
some O
of O
these O
files O
, O
the O
malware O
decides O
which O
kind O
of O
installation O
to O
perform O
based O
on O
the O
current O
privilege O
provided O
by O
the O
hosting O
process O
( O
for O
example O
, O
if O
a O
Microsoft B-System
Office I-System
process O
was O
used O
as O
exploit O
vector O
) O
: O
Installation O
process O
under O
UAC O
When O
running O
under O
a O
limited O
UAC O
account O
, O
the O
installer O
extracts O
d3d9.dll B-Indicator
and O
creates O
a O
persistence O
key O
under O
HKCU\Software\Microsoft\Windows\Run B-Indicator
. O
The O
malware O
sets O
a O
registry O
value O
( O
whose O
name O
is O
read O
from O
the O
configuration O
file O
) O
to O
“ O
C B-Indicator
: I-Indicator
\Windows\system32\rundll32.exe I-Indicator
c B-Indicator
: I-Indicator
\ProgramData\AuditApp\d3d9.dll I-Indicator
, I-Indicator
Control_Run B-Indicator
” O
. O
Before O
doing O
this O
, O
the O
malware O
makes O
a O
screenshot O
of O
the O
screen O
and O
displays O
it O
on O
top O
of O
all O
other O
windows B-System
for O
few O
seconds O
. O
This O
indicates O
that O
the O
authors O
are O
trying O
to O
hide O
some O
messages O
showed O
by O
the O
system O
during O
the O
setup O
process O
. O
When O
loaded O
with O
startup O
command O
2 O
, O
the O
installer O
can O
copy O
the O
original O
explorer.exe B-Indicator
file I-Indicator
inside O
its O
current O
running O
directory O
and O
rename O
d3d9.dll B-Indicator
to O
uxtheme.dll B-Indicator
. O
In O
this O
case O
the O
persistence O
is O
achieved O
by O
loading O
the O
original O
explorer.exe B-Indicator
from O
its O
startup O
location O
and O
, O
using O
DLL O
side-loading O
, O
passing O
the O
execution O
control O
to O
the O
stage O
4 O
malware O
( O
discussed O
in O
next O
section O
) O
. O
Finally O
, O
the O
malware O
spawns O
a O
thread O
that O
has O
the O
goal O
to O
load O
, O
remap O
, O
and O
relocate O
the O
stage O
5 O
malware O
. O
In O
this O
context O
, O
there O
is O
indeed O
no O
need O
to O
execute O
the O
stage O
4 O
malware O
. O
The O
msvcr90.dll B-Indicator
file I-Indicator
is O
opened O
, O
read O
, O
and O
decrypted O
, O
and O
the O
code O
execution O
control O
is O
transferred O
to O
the O
RunDll O
exported O
routine O
. O
In O
the O
case O
of O
32-bit O
systems O
, O
the O
malware O
may O
attempt O
a O
known O
UAC O
bypass O
by O
launching O
printui.exe B-Indicator
system O
process O
and O
using O
token O
manipulation O
with O
NtFilterToken O
as O
described O
in O
this O
blog O
post O
. O
Installation O
process O
with O
administrative O
privilege O
This O
installation O
method O
is O
more O
interesting O
because O
it O
reveals O
how O
the O
malware O
tries O
to O
achieve O
stealthier O
persistence O
on O
the O
machine O
. O
The O
method O
is O
a O
well-known O
trick O
used O
by O
penetration O
testers O
that O
was O
automated O
and O
generalized O
by O
FinFisher B-Malware
The O
procedure O
starts O
by O
enumerating O
the O
KnownDlls O
object O
directory O
and O
then O
scanning O
for O
section O
objects O
of O
the O
cached O
system O
DLLs O
. O
Next O
, O
the O
malware O
enumerates O
all O
.exe O
programs O
in O
the O
% O
System O
% O
folder O
and O
looks O
for O
an O
original O
signed O
Windows B-System
binary O
that O
imports O
from O
at O
least O
one O
KnownDll O
and O
from O
a O
library O
that O
is O
not O
in O
the O
KnownDll O
directory O
. O
When O
a O
suitable O
.exe O
file O
candidate O
is O
found O
, O
it O
is O
copied O
into O
the O
malware O
installation O
folder O
( O
for O
example O
, O
C B-Indicator
: I-Indicator
\ProgramData I-Indicator
) O
. O
At O
this O
point O
the O
malware O
extracts O
and O
decrypts O
a O
stub O
DLL O
from O
its O
own O
resources O
( O
ID O
101 O
) O
. O
It O
then O
calls O
a O
routine O
that O
adds O
a O
code O
section O
to O
a O
target O
module O
. O
This O
section O
will O
contain O
a O
fake O
export O
table O
mimicking O
the O
same O
export O
table O
of O
the O
original O
system O
DLL O
chosen O
. O
At O
the O
time O
of O
writing O
, O
the O
dropper O
supports O
aepic.dll B-Indicator
, O
sspisrv.dll B-Indicator
, O
ftllib.dll B-Indicator
, O
and O
userenv.dll B-Indicator
to O
host O
the O
malicious O
FinFisher B-Malware
payload O
. O
Finally O
, O
a O
new O
Windows B-System
service O
is O
created O
with O
the O
service O
path O
pointing O
to O
the O
candidate O
.exe O
located O
in O
this O
new O
directory O
together O
with O
the O
freshly O
created O
, O
benign-looking O
DLL O
. O
In O
this O
way O
, O
when O
the O
service O
runs O
during O
boot O
, O
the O
original O
Windows B-System
executable O
is O
executed O
from O
a O
different O
location O
and O
it O
will O
automatically O
load O
and O
map O
the O
malicious O
DLL O
inside O
its O
address O
space O
, O
instead O
of O
using O
the O
genuine O
system O
library O
. O
This O
routine O
is O
a O
form O
of O
generic O
and O
variable O
generator O
of O
DLL O
side-loading O
combinations O
. O
Figure O
10 O
. O
Windows B-System
Defender I-System
ATP I-System
timeline O
can O
pinpoint O
the O
service O
DLL O
side-loading O
trick O
( O
in O
this O
example O
, O
using O
fltlib.dll B-Indicator
) O
. O
In O
the O
past O
, O
we O
have O
seen O
other O
activity O
groups O
like O
LEAD O
employ O
a O
similar O
attacker O
technique O
named O
“ O
proxy-library O
” O
to O
achieve O
persistence O
, O
but O
not O
with O
this O
professionalism O
. O
The O
said O
technique O
brings O
the O
advantage O
of O
avoiding O
auto-start O
extensibility O
points O
( O
ASEP O
) O
scanners O
and O
programs O
that O
checks O
for O
binaries O
installed O
as O
service O
( O
for O
the O
latter O
, O
the O
service O
chosen O
by O
FinFisher B-Malware
will O
show O
up O
as O
a O
clean O
Windows B-System
signed O
binary O
) O
. O
The O
malware O
cleans O
the O
system O
event O
logs O
using O
OpenEventLog/ClearEventLog O
APIs O
, O
and O
then O
terminates O
the O
setup O
procedure O
with O
a O
call O
to O
StartService O
to O
run O
the O
stage O
4 O
malware O
. O
Figure O
11 O
. O
The O
DLL O
side-loaded O
stage O
4 O
malware O
mimicking O
a O
real O
export O
table O
to O
avoid O
detection O
Stage O
4 O
: O
The O
memory O
loader O
– O
Fun O
injection O
with O
GDI O
function O
hijacking O
Depending O
on O
how O
stage O
4 O
was O
launched O
, O
two O
different O
things O
may O
happen O
: O
In O
the O
low-integrity O
case O
( O
under O
UAC O
) O
the O
installer O
simply O
injects O
the O
stage O
5 O
malware O
into O
the O
bogus O
explorer.exe B-Indicator
process O
started O
earlier O
and O
terminates O
In O
the O
high-integrity O
case O
( O
with O
administrative O
privileges O
or O
after O
UAC O
bypass O
) O
, O
the O
code O
searches O
for O
the O
process O
hosting O
the O
Plug O
and O
Play O
service O
( O
usually O
svchost.exe B-Indicator
) O
loaded O
in O
memory O
and O
injects O
itself O
into O
it O
For O
the O
second O
scenario O
, O
the O
injection O
process O
works O
like O
this O
: O
The O
malware O
opens O
the O
target O
service O
process O
. O
It O
allocates O
and O
fills O
four O
chunks O
of O
memory O
inside O
the O
service O
process O
. O
One O
chunk O
contains O
the O
entire O
malware O
DLL O
code O
( O
without O
PE O
headers O
) O
. O
Another O
chunk O
is O
used O
to O
copy O
a O
basic O
Ntdll O
and O
Kernel32 O
import O
address O
table O
. O
Two O
chunks O
are O
filled O
with O
an O
asynchronous O
procedure O
call O
( O
APC O
) O
routine O
code O
and O
a O
stub O
. O
It O
opens O
the O
service O
thread O
of O
the O
service O
process O
and O
uses O
the O
ZwQueueApcThread B-Indicator
native O
API O
to O
inject O
an O
APC O
. O
The O
APC O
routine O
creates O
a O
thread O
in O
the O
context O
of O
the O
svchost.exe B-Indicator
process O
that O
will O
map O
and O
execute O
the O
stage O
5 O
malware O
into O
the O
winlogon.exe B-Indicator
process O
. O
The O
injection O
method O
used O
for O
winlogon.exe B-Indicator
is O
also O
interesting O
and O
quite O
unusual O
. O
We O
believe O
that O
this O
method O
is O
engineered O
to O
avoid O
trivial O
detection O
of O
process O
injection O
using O
the O
well-detected O
CreateRemoteThread B-Indicator
or O
ZwQueueApcThread B-Indicator
API O
. O
The O
malware O
takes O
these O
steps O
: O
Check O
if O
the O
system O
master O
boot O
record O
( O
MBR O
) O
contains O
an O
infection O
marker O
( O
0xD289C989C089 B-Indicator
8-bytes O
value O
at O
offset O
0x2C O
) O
, O
and O
, O
if O
so O
, O
terminate O
itself O
Check O
again O
if O
the O
process O
is O
attached O
to O
a O
debugger O
( O
using O
the O
techniques O
described O
previously O
) O
Read O
, O
decrypt O
, O
and O
map O
the O
stage O
5 O
malware O
( O
written O
in O
the O
previous O
stage O
in O
msvcr90.dll B-Indicator
) O
Open O
winlogon.exe B-Indicator
process O
Load O
user32.dll B-Indicator
system O
library O
and O
read O
the O
KernelCallbackTable B-Indicator
pointer O
from O
its O
own O
process O
environment O
block O
( O
PEB O
) O
( O
Note O
: O
The O
KernelCallbackTable O
points O
to O
an O
array O
of O
graphic O
functions O
used O
by O
Win32 O
kernel O
subsystem O
module O
win32k.sys B-Indicator
as O
call-back O
into O
user-mode O
. O
) O
Calculate O
the O
difference O
between O
this O
pointer O
and O
the O
User32 O
base O
address O
. O
Copy O
the O
stage O
5 O
DLL O
into O
winlogon.exe B-Indicator
Allocate O
a O
chunk O
of O
memory O
in O
winlogon.exe B-Indicator
process O
and O
copy O
the O
same O
APC O
routine O
seen O
previously O
Read O
and O
save O
the O
original O
pointer O
of O
the O
__fnDWORD O
internal O
User32 O
routine O
( O
located O
at O
offset O
+0x10 O
of O
the O
KernelCallbackTable O
) O
and O
replace O
this O
pointer O
with O
the O
address O
of O
the O
APC O
stub O
routine O
After O
this O
function O
pointer O
hijacking O
, O
when O
winlogon.exe B-Indicator
makes O
any O
graphical O
call O
( O
GDI O
) O
, O
the O
malicious O
code O
can O
execute O
without O
using O
CreateRemoteThread O
or O
similar O
triggers O
that O
are O
easily O
detectable O
. O
After O
execution O
it O
takes O
care O
of O
restoring O
the O
original O
KernelCallbackTable O
. O
Stage O
5 O
: O
The O
final O
loader O
takes O
control O
The O
stage O
5 O
malware O
is O
needed O
only O
to O
provide O
one O
more O
layer O
of O
obfuscation O
, O
through O
the O
VM O
, O
of O
the O
final O
malware O
payload O
and O
to O
set O
up O
a O
special O
Structured O
Exception O
Hander O
routine O
, O
which O
is O
inserted O
as O
Wow64PrepareForException O
in O
Ntdll O
. O
This O
special O
exception O
handler O
is O
needed O
to O
manage O
some O
memory O
buffers O
protection O
and O
special O
exceptions O
that O
are O
used O
to O
provide O
more O
stealthy O
execution O
. O
After O
the O
VM O
code O
has O
checked O
again O
the O
user O
environment O
, O
it O
proceeds O
to O
extract O
and O
execute O
the O
final O
un-obfuscated O
payload O
sample O
directly O
into O
winlogon.exe B-Indicator
( O
alternatively O
, O
into O
explorer.exe B-Indicator
) O
process O
. O
After O
the O
payload O
is O
extracted O
, O
decrypted O
, O
and O
mapped O
in O
the O
process O
memory O
, O
the O
malware O
calls O
the O
new O
DLL O
entry O
point O
, O
and O
then O
the O
RunDll O
exported O
function O
. O
The O
latter O
implements O
the O
entire O
spyware O
program O
. O
Stage O
6 O
: O
The O
payload O
is O
a O
modular O
spyware O
framework O
for O
further O
analysis O
Our O
journey O
to O
deobfuscating O
FinFisher B-Malware
has O
allowed O
us O
to O
uncover O
the O
complex O
anti-analysis O
techniques O
used O
by O
this O
malware O
, O
as O
well O
as O
to O
use O
this O
intel O
to O
protect O
our O
customers O
, O
which O
is O
our O
top O
priority O
. O
Analysis O
of O
the O
additional O
spyware O
modules O
is O
future O
work O
. O
It O
is O
evident O
that O
the O
ultimate O
goal O
of O
this O
program O
is O
to O
steal O
information O
. O
The O
malware O
architecture O
is O
modular O
, O
which O
means O
that O
it O
can O
execute O
plugins O
. O
The O
plugins O
are O
stored O
in O
its O
resource O
section O
and O
can O
be O
protected O
by O
the O
same O
VM O
. O
The O
sample O
we O
analyzed O
in O
October O
, O
for O
example O
, O
contains O
a O
plugin O
that O
is O
able O
to O
spy O
on O
internet O
connections O
, O
and O
can O
even O
divert O
some O
SSL O
connections O
and O
steal O
data O
from O
encrypted O
traffic O
. O
Some O
FinFisher B-Malware
variants O
incorporate O
an O
MBR B-Indicator
rootkit I-Indicator
, O
the O
exact O
purpose O
of O
which O
is O
not O
clear O
. O
Quite O
possibly O
, O
this O
routine O
targets O
older O
platforms O
like O
Windows B-System
7 I-System
and O
machines O
not O
taking O
advantage O
of O
hardware O
protections O
like O
UEFI O
and O
SecureBoot O
, O
available O
on O
Windows B-System
10 I-System
. O
Describing O
this O
additional O
piece O
of O
code O
in O
detail O
is O
outside O
the O
scope B-System
of O
this O
analysis O
and O
may O
require O
a O
new O
dedicated O
blog O
post O
. O
Defense O
against O
FinFisher B-Malware
Exposing O
as O
much O
of O
FinFisher B-Malware
’ O
s O
riddles O
as O
possible O
during O
this O
painstaking O
analysis O
has O
allowed O
us O
to O
ensure O
our O
customers O
are O
protected O
against O
this O
advanced O
piece O
of O
malware O
. O
Windows B-System
10 I-System
S O
devices O
are O
naturally O
protected O
against O
FinFisher B-Malware
and O
other O
threats O
thanks O
to O
the O
strong O
code O
integrity O
policies O
that O
don O
’ O
t O
allow O
unknown O
unsigned O
binaries O
to O
run O
( O
thus O
stopping O
FinFisher B-Malware
’ O
s O
PE O
installer O
) O
or O
loaded O
( O
blocking O
FinFisher B-Malware
’ O
s O
DLL O
persistence O
) O
. O
On O
Windows B-System
10 I-System
, O
similar O
code O
integrity O
policies O
can O
be O
configured O
using O
Windows B-System
Defender I-System
Application I-System
Control I-System
. O
Office B-System
365 I-System
Advanced I-System
Threat I-System
Protection I-System
secures O
mailboxes O
from O
email O
campaigns O
that O
use O
zero-day B-Vulnerability
exploits I-Vulnerability
to O
deliver O
threats O
like O
FinFisher B-Malware
. O
Office B-System
365 I-System
ATP I-System
blocks O
unsafe O
attachments O
, O
malicious O
links O
, O
and O
linked-to O
files O
using O
time-of-click O
protection O
. O
Using O
intel O
from O
this O
research O
, O
we O
have O
made O
Office B-System
365 I-System
ATP I-System
more O
resistant O
to O
FinFisher B-Malware
’ O
s O
anti-sandbox O
checks O
. O
Generic O
detections O
, O
advanced O
behavioral O
analytics O
, O
and O
machine O
learning O
technologies O
in O
Windows B-System
Defender I-System
Advanced I-System
Threat I-System
Protection I-System
detect O
FinFisher B-Malware
’ O
s O
malicious O
behavior O
throughout O
the O
attack O
kill O
chain O
and O
alert O
SecOps O
personnel O
. O
Windows B-System
Defender I-System
ATP I-System
also O
integrates O
with O
the O
Windows B-System
protection O
stack O
so O
that O
protections O
from O
Windows B-System
Defender I-System
AV I-System
and O
Windows B-System
Defender I-System
Exploit I-System
Guard I-System
are O
reported O
in O
Windows B-System
Defender I-System
ATP I-System
portal O
, O
enabling O
SecOps O
personnel O
to O
centrally O
manage O
security O
, O
and O
as O
well O
as O
promptly O
investigate O
and O
respond O
to O
hostile O
activity O
in O
the O
network O
. O
We O
hope O
that O
this O
writeup O
of O
our O
journey O
through O
all O
the O
multiple O
layers O
of O
protection O
, O
obfuscation O
, O
and O
anti-analysis O
techniques O
of O
FinFisher B-Malware
will O
be O
useful O
to O
other O
researchers O
studying O
this O
malware O
. O
We O
believe O
that O
an O
industry-wide O
collaboration O
and O
information-sharing O
is O
important O
in O
defending O
customers O
against O
this O
complex O
piece O
of O
malware O
. O
TUESDAY O
, O
APRIL O
9 O
, O
2019 O
Gustuff B-Malware
banking O
botnet O
targets O
Australia O
EXECUTIVE O
SUMMARY O
Cisco B-Organization
Talos I-Organization
has O
uncovered O
a O
new O
Android-based B-System
campaign O
targeting O
Australian O
financial O
institutions O
. O
As O
the O
investigation O
progressed O
, O
Talos B-Organization
came O
to O
understand O
that O
this O
campaign O
was O
associated O
with O
the O
" O
ChristinaMorrow O
'' O
text O
message O
spam O
scam O
previously O
spotted O
in O
Australia O
. O
Although O
this O
malware O
's O
credential-harvest O
mechanism O
is O
not O
particularly O
sophisticated O
, O
it O
does O
have O
an O
advanced O
self-preservation O
mechanism O
. O
Even O
though O
this O
is O
not O
a O
traditional O
remote O
access O
tool O
( O
RAT O
) O
, O
this O
campaign O
seems O
to O
target O
mainly O
private O
users O
. O
Aside O
from O
the O
credential O
stealing O
, O
this O
malware O
also O
includes O
features O
like O
the O
theft O
of O
users O
' O
contact O
list O
, O
collecting O
phone O
numbers O
associated O
names O
, O
and O
files O
and O
photos O
on O
the O
device O
. O
But O
that O
does O
n't O
mean O
companies O
and O
organizations O
are O
out O
of O
the O
woods O
. O
They O
should O
still O
be O
on O
the O
lookout O
for O
these O
kinds O
of O
trojans O
, O
as O
the O
attackers O
could O
target O
corporate O
accounts O
that O
contain O
large O
amounts O
of O
money O
. O
The O
information O
collected O
by O
the O
malware O
and O
the O
control O
over O
the O
victim O
's O
mobile O
device O
allows O
their O
operators O
to O
perform O
more O
complex O
social O
engineering O
attacks O
. O
A O
motivated O
attacker O
can O
use O
this O
trojan O
to O
harvest O
usernames O
and O
passwords O
and O
then O
reuse O
them O
to O
login O
into O
the O
organization O
's O
system O
where O
the O
victim O
works O
. O
This O
is O
a O
good O
example O
where O
two-factor O
authentication O
based O
on O
SMS O
would O
fail O
since O
the O
attacker O
can O
read O
the O
SMS O
. O
Corporations O
can O
protect O
themselves O
from O
these O
side-channel O
attacks O
by O
deploying O
client-based O
two-factor O
authentication O
, O
such O
as O
Duo B-System
Security I-System
. O
One O
of O
the O
most O
impressive O
features O
of O
this O
malware O
is O
its O
resilience O
. O
If O
the O
command O
and O
control O
( O
C2 O
) O
server O
is O
taken O
down O
, O
the O
malicious O
operator O
can O
still O
recover O
the O
malware O
control O
by O
sending O
SMS O
messages O
directly O
to O
the O
infected O
devices O
. O
This O
makes O
the O
taking O
down O
and O
recovery O
of O
the O
network O
much O
harder O
and O
poses O
a O
considerable O
challenge O
for O
defenders O
. O
THE O
CAMPAIGN O
The O
malware O
's O
primary O
infection O
vector O
is O
SMS O
. O
Just O
like O
the O
old-school O
mail O
worms O
that O
used O
the O
victim O
's O
address B-System
book I-System
to O
select O
the O
next O
victims O
, O
this O
banking O
trojan O
's O
activation O
cycle O
includes O
the O
exfiltration O
of O
the O
victim O
's O
address O
book O
. O
The O
trojan O
will O
receive O
instructions O
from O
the O
C2 O
to O
spread O
. O
Spread O
command O
from O
C2 O
The O
victim O
receives O
the O
command O
sendSMSMass O
. O
Usually O
, O
this O
message O
targets O
four O
or O
five O
people O
at O
a O
time O
. O
The O
body O
contains O
a O
message O
and O
URL O
. O
Again O
, O
the O
concept O
is O
that O
new O
victims O
are O
more O
likely O
to O
install O
the O
malware O
if O
the O
SMS O
comes O
from O
someone O
they O
know O
. O
When O
a O
victim O
tries O
to O
access O
the O
URL O
in O
the O
SMS O
body O
, O
the O
C2 O
will O
check O
if O
the O
mobile O
device O
meets O
the O
criteria O
to O
receive O
the O
malware O
( O
see O
infrastructure O
section O
) O
. O
If O
the O
device O
does O
not O
meet O
the O
criteria O
, O
it O
wo O
n't O
receive O
any O
data O
, O
otherwise O
, O
it O
will O
be O
redirected O
to O
a O
second O
server O
to O
receive O
a O
copy O
of O
the O
malware O
to O
install O
on O
their O
device O
. O
The O
domain O
on O
this O
campaign O
was O
registered O
on O
Jan. O
19 O
, O
2019 O
. O
However O
, O
Talos B-Organization
has O
identified O
that O
was O
used O
at O
least O
since O
November O
2018 O
. O
During O
the O
investigation O
, O
Talos B-Organization
was O
also O
able O
to O
determine O
that O
the O
same O
infrastructure O
has O
been O
used O
to O
deploy O
similar O
campaigns O
using O
different O
versions O
of O
the O
malware O
. O
Distribution O
of O
victims O
. O
Talos B-Organization
assess O
with O
high O
confidence O
that O
this O
campaign O
is O
targeting O
Australian O
financial O
institutions O
based O
on O
several O
factors O
. O
Our O
Umbrella O
telemetry O
shows O
that O
the O
majority O
of O
the O
request O
comes O
from O
Australia O
and O
the O
majority O
of O
the O
phone O
numbers O
infected O
have O
the O
international O
indicative O
for O
Australia O
. O
Finally O
, O
the O
specific O
overlays O
are O
designed O
for O
Australian O
financial O
institutions O
, O
and O
Australia O
is O
one O
of O
the O
geographic O
regions O
that O
is O
accepted O
by O
the O
C2 O
. O
DNS O
queries O
distribution O
over O
time O
The O
campaign O
does O
n't O
seem O
to O
be O
growing O
at O
a O
fast O
pace O
. O
Our O
data O
shows O
, O
on O
average O
, O
about O
three O
requests O
per O
hour O
to O
the O
drop O
host O
. O
This O
request O
is O
only O
made O
upon O
installation O
, O
but O
there O
is O
no O
guarantee O
that O
it O
will O
be O
installed O
. O
This O
data O
, O
when O
analyzed O
with O
the O
number O
of O
commands O
to O
send O
SMSs O
that O
Talos O
received O
during O
the O
investigation O
, O
lead O
us O
to O
conclude O
that O
the O
malicious O
operator O
is O
aggressively O
spreading O
the O
malware O
, O
but O
that O
does O
n't O
seem O
to O
result O
in O
the O
same O
number O
of O
new O
infections O
. O
Examples O
of O
the O
overlays O
available O
to O
the O
malware O
Above O
, O
you O
can O
see O
examples O
of O
the O
injections O
that O
distributed O
to O
the O
malware O
as O
part O
of O
this O
specific O
campaign O
. O
While O
doing O
our O
investigation O
we O
were O
able O
to O
identify O
other O
malware O
packages O
with O
different O
names O
. O
Some O
of O
these O
might O
have O
been O
used O
on O
old O
campaigns O
or O
were O
already O
prepared O
for O
new O
campaigns O
. O
MALWARE O
TECHNICAL O
DETAILS O
During O
our O
investigation O
, O
researchers O
uncovered O
a O
malware O
known O
as O
" O
Gustuff. B-Malware
'' O
. O
Given O
the O
lack O
of O
indicators O
of O
compromise O
, O
we O
decided O
to O
check O
to O
see O
if O
this O
was O
the O
same O
malware O
we O
had O
been O
researching O
. O
Our O
Threat O
Intelligence O
and O
Interdiction O
team O
found O
the O
Gustuff B-Malware
malware O
being O
advertised O
in O
the O
Exploit.in B-Indicator
forum O
as O
a O
botnet O
for O
rent O
. O
The O
seller O
, O
known O
as O
" O
bestoffer O
, O
'' O
was O
, O
at O
some O
point O
, O
expelled O
from O
the O
forum O
. O
Gustuff B-Malware
advertising O
screenshot O
The O
companies O
advertised O
in O
the O
image O
above O
were O
from O
Australia O
, O
which O
matches O
up O
with O
the O
campaign O
we O
researched O
. O
The O
screenshots O
provided O
by O
the O
author O
align O
with O
the O
advertised O
features O
and O
the O
features O
that O
we O
discovered O
while O
doing O
our O
analysis O
. O
Admin O
panel O
The O
administration O
panel O
shows O
the O
application O
configuration O
, O
which O
matches O
the O
commands O
from O
the O
C2 O
. O
Country O
selection O
The O
administration O
console O
screenshots O
also O
show O
the O
ability O
to O
filter O
the O
results O
by O
country O
. O
In O
this O
case O
, O
" O
AU O
'' O
is I-Organization
the O
code O
shown O
, O
which O
is O
Australia O
. O
Based O
on O
this O
information O
, O
Talos B-Organization
assesses O
with O
high O
confidence O
that O
the O
malware O
is O
the O
same O
and O
this O
is O
, O
in O
fact O
, O
the O
Gustuff B-Malware
malware O
. O
Design O
In O
the O
manifest O
, O
the O
malware O
requests O
a O
large O
number O
of O
permissions O
. O
However O
, O
it O
does O
n't O
request O
permissions O
like O
BIND_ADMIN O
. O
To O
perform O
some O
of O
its O
activities O
, O
the O
malware O
does O
not O
need O
high O
privileges O
inside O
the O
device O
, O
as O
we O
will O
explain O
ahead O
. O
Permissions O
in O
the O
manifest O
This O
malware O
is O
designed O
to O
avoid O
detection O
and O
analysis O
. O
It O
has O
several O
protections O
in O
place O
, O
both O
in O
the O
C2 O
and O
the O
malware O
's O
code O
. O
The O
code O
is O
not O
only O
obfuscated O
but O
also O
packed O
. O
The O
packer O
, O
besides O
making O
the O
static O
analysis O
more O
complex O
, O
will O
break O
the O
standard O
debugger O
. O
Manifest O
activity O
declaration O
Class O
list O
inside O
the O
dex O
file O
The O
main O
malware O
classes O
are O
packed O
, O
to O
a O
point O
where O
the O
class O
defined O
in O
the O
manifest O
has O
a O
handler O
for O
the O
MAIN O
category O
that O
does O
not O
exist O
in O
the O
DEX O
file O
. O
Error O
when O
trying O
to O
debug O
the O
malware O
using O
the O
Android B-System
Studio I-System
IDE I-System
. O
One O
of O
the O
side O
effects O
of O
this O
packer O
is O
the O
inability O
of O
Android B-System
Studio I-System
IDE I-System
to O
debug O
the O
code O
. O
This O
happens O
because O
the O
IDE O
executes O
the O
code O
from O
the O
Android B-System
debug I-System
bridge I-System
( O
ADB O
) O
by O
calling O
the O
activity O
declared O
in O
the O
manifest O
by O
name O
. O
Since O
the O
class O
does O
not O
exist O
at O
startup O
, O
the O
application O
does O
not O
run O
on O
the O
debugger O
. O
Although O
Talos B-Malware
analyzed O
the O
unpacked O
version O
of O
the O
code O
, O
the O
packer O
analysis O
is O
beyond O
the O
scope O
of O
this O
post O
. O
Check O
code O
for O
emulators O
As O
part O
of O
its O
defense O
, O
the O
malware O
payload O
first O
checks O
for O
emulators O
to O
prevent O
analysis O
on O
sandboxes O
. O
It O
checks O
for O
different O
kinds O
of O
emulators O
, O
including O
QEMU B-System
, O
Genymotion B-System
, O
BlueStacks B-System
and O
Bignox B-System
. O
If O
the O
malware O
determines O
that O
is O
not O
running O
on O
an O
emulator O
, O
it O
then O
performs O
additional O
checks O
to O
ensure O
that O
it O
wo O
n't O
be O
detected O
. O
Code O
to O
check O
the O
existence O
of O
SafetyNet O
Google B-System
API I-System
It O
also O
checks O
if O
the O
Android B-System
SafetyNet O
is O
active O
and O
reporting O
back O
to O
the O
C2 O
. O
This O
helps O
the O
C2 O
define O
what O
actions O
it O
can O
do O
before O
being O
detected O
on O
the O
mobile O
device O
. O
List O
of O
anti-virus O
packages O
that O
are O
checked O
The O
payload O
goes O
a O
long O
way O
to O
protect O
itself O
and O
checks O
for O
anti-virus O
software O
installed O
on O
the O
mobile O
device O
. O
The O
trojan O
uses O
the O
Android B-System
Accessibility I-System
API O
to O
intercept O
all O
interactions O
between O
the O
user O
and O
the O
mobile O
device O
. O
The O
Android B-System
developer O
documentation O
describes O
the O
accessibility O
event O
class O
as O
a O
class O
that O
" O
represents O
accessibility O
events O
that O
are O
seen O
by O
the O
system O
when O
something O
notable O
happens O
in O
the O
user O
interface O
. O
For O
example O
, O
when O
a O
button O
is O
clicked O
, O
a O
view O
is O
focused O
, O
etc O
. O
'' O
For O
each O
interaction O
, O
the O
malware O
will O
check O
if O
the O
generator O
is O
a O
package O
that O
belongs O
to O
the O
anti-virus O
list O
, O
the O
malware O
will O
abuse O
another O
feature O
of O
the O
Accessibility B-System
API I-System
. O
There O
is O
a O
function O
called O
" O
performGlobalAction O
'' O
with O
the O
description O
below O
. O
Android B-System
documentation O
describes O
that O
function O
as O
" O
a O
global O
action O
. O
Such O
an O
action O
can O
be O
performed O
at O
any O
moment O
, O
regardless O
of O
the O
current O
application O
or O
user O
location O
in O
that O
application O
. O
For O
example O
, O
going O
back O
, O
going O
home O
, O
opening O
recents O
, O
etc O
. O
'' O
The O
trojan O
calls O
this O
function O
with O
the O
action O
GLOBAL_ACTION_BACK O
, O
which O
equals O
the O
pressing O
of O
the O
back O
button O
on O
the O
device O
, O
thus O
canceling O
the O
opening O
of O
the O
anti-virus O
application O
. O
The O
same O
event O
interception O
is O
used O
to O
place O
the O
webview O
overlay O
when O
the O
user O
tries O
to O
access O
the O
targeted O
applications O
, O
allowing O
it O
to O
display O
its O
overlay O
, O
thus O
intercepting O
the O
credentials O
. O
The O
beaconing O
only O
starts O
after O
the O
application O
is O
installed O
and O
removed O
from O
the O
running O
tasks O
. O
Beaconing O
information O
The O
ID O
is O
generated O
for O
each O
installation O
of O
the O
malware O
, O
while O
the O
token O
remains O
unique O
. O
Some O
of O
the O
checks O
performed O
previously O
are O
immediately O
sent O
to O
the O
C2 O
, O
like O
the O
safetyNet O
, O
admin O
and O
defaultSMSApp O
. O
The O
beaconing O
is O
sent O
to O
the O
URL O
http B-Indicator
: I-Indicator
// I-Indicator
/api/v2/get.php I-Indicator
with O
an O
interval O
of O
60 O
seconds O
. O
Answer O
from O
the O
C2 O
The O
C2 O
will O
check O
the O
country O
field O
, O
if O
it O
's O
empty O
or O
if O
the O
country O
is O
not O
targeted O
, O
it O
will O
reply O
with O
a O
" O
Unauthorized O
'' O
answer O
. O
Otherwise O
, O
it O
will O
return O
a O
JSON O
encoded O
" O
OK O
, O
'' O
and O
if O
that O
is O
the O
case O
, O
the O
command O
to O
be O
executed O
. O
List O
of O
available O
commands O
The O
command O
names O
are O
self-explanatory O
. O
The O
command O
will O
be O
issued O
as O
an O
answer O
to O
the O
beaconing O
, O
and O
the O
result O
will O
be O
returned O
to O
the O
URL O
http B-Indicator
: I-Indicator
// I-Indicator
/api/v2/set_state.php I-Indicator
Example O
of O
the O
command O
" O
changeServer O
'' O
The O
commands O
are O
issued O
in O
a O
JSON O
format O
, O
and O
the O
obfuscation O
is O
part O
of O
the O
malware O
code O
and O
not O
added O
by O
the O
packer O
. O
It O
is O
a O
custom O
obfuscation O
partly O
based O
on O
base85 B-Indicator
encoding I-Indicator
, O
which O
is O
in O
itself O
unusual O
, O
in O
malware O
. O
Base85 B-Indicator
encoding I-Indicator
is O
usually O
used O
on O
pdf O
and O
postscript O
documentsThe O
configuration O
of O
the O
malware O
is O
stored O
in O
custom O
preferences O
files O
, O
using O
the O
same O
obfuscation O
scheme O
. O
Activation O
cycle O
As O
we O
have O
explained O
above O
, O
the O
malware O
has O
several O
defence O
mechanisms O
. O
Beside O
the O
obfuscation O
and O
the O
environment O
checks O
, O
the O
malware O
also O
has O
some O
interesting O
anti-sandbox O
mechanisms O
. O
After O
installation O
, O
the O
user O
needs O
to O
run O
the O
application O
. O
The O
user O
needs O
to O
press O
the O
" O
close O
'' O
button O
to O
finish O
the O
installation O
. O
However O
, O
this O
wo O
n't O
close O
the O
application O
, O
it O
will O
send O
it O
to O
the O
background O
, O
instead O
. O
While O
the O
application O
is O
in O
the O
background O
, O
although O
the O
service O
is O
already O
running O
, O
the O
beaconing O
will O
not O
start O
. O
The O
beaconing O
will O
only O
start O
after O
the O
application O
is O
removed O
from O
the O
background O
, O
ultimately O
stopping O
it O
. O
This O
will O
be O
the O
trigger O
for O
the O
service O
to O
start O
the O
beaconing O
. O
As O
mentioned O
previously O
, O
the O
beaconing O
is O
done O
every O
60 O
seconds O
. O
However O
, O
no O
command O
is O
received O
from O
the O
C2 O
until O
the O
inactiveTime O
field O
( O
see O
beaconing O
information O
image O
above O
) O
has O
at O
least O
the O
value O
of O
2000000 O
. O
This O
time O
resets O
every O
time O
the O
user O
performs O
some O
activity O
. O
After O
the O
checks O
, O
the O
malware O
becomes O
active O
, O
but O
first O
, O
it O
goes O
through O
seven O
steps O
, O
each O
one O
calling O
a O
different O
command O
: O
uploadPhoneNumbers O
: O
Exfiltrates O
all O
phone O
numbers O
that O
are O
in O
the O
contact O
list O
. O
Aside O
from O
the O
natural O
value O
of O
phone O
numbers O
associated O
with O
the O
names O
of O
their O
owners O
. O
Using O
the O
SMS O
has O
an O
initial O
infection O
vector O
is O
another O
possibility O
for O
the O
exfiltration O
. O
One O
of O
the O
purposes O
of O
the O
exfiltration O
of O
the O
contact O
list O
is O
to O
use O
them O
to O
attack O
other O
victims O
using O
SMS O
as O
an O
initial O
vector O
. O
checkApps O
: O
Asks O
the O
malware O
to O
see O
if O
the O
packages O
sent O
as O
parameters O
are O
installed O
. O
The O
malware O
contains O
a O
list O
of O
209 O
packages O
hardcoded O
in O
its O
source O
code O
. O
However O
, O
the O
C2 O
can O
send O
an O
updated O
list O
. O
List O
of O
packages O
received O
from O
the O
C2 O
adminNumber O
: O
Setup O
of O
the O
admin O
phone O
number O
. O
In O
our O
case O
, O
the O
administrator O
phone O
number O
belongs O
to O
a O
mobile O
network O
in O
Australia O
. O
Phone O
number O
for O
administration O
changeServer O
: O
At O
this O
point O
, O
the O
malware O
changes O
the O
C2 O
to O
a O
new O
host O
, O
even O
though O
the O
API O
and O
communication O
protocol O
continues O
to O
be O
the O
same O
. O
Change O
server O
request O
The O
URL O
's O
for O
the O
new O
server O
is O
obfuscated O
, O
preventing O
easy O
network O
identification O
. O
changeActivity O
: O
This O
command O
will O
set O
up O
the O
webview O
to O
overlay O
any O
of O
the O
target O
activities O
. O
changeActivity O
command O
The O
webview O
injects O
are O
not O
hosted O
on O
the O
C2 O
, O
they O
are O
hosted O
on O
a O
completely O
different O
server O
. O
params O
: O
This O
command O
allows O
the O
malicious O
operator O
to O
change O
configuration O
parameters O
in O
the O
malware O
. O
During O
this O
stage O
of O
the O
activation O
cycle O
, O
the O
malware O
increases O
the O
beaconing O
time O
to O
avoid O
detection O
. O
Command O
to O
change O
the O
beaconing O
changeArchive O
: O
The O
final O
command O
of O
the O
activation O
cycle O
is O
the O
download O
of O
an O
archive O
. O
This O
archive O
is O
stored O
in O
the O
same O
host O
has O
the O
webviews O
. O
The O
archive O
is O
a O
ZIP O
containing O
several O
files O
, O
which O
is O
protected O
with O
a O
password O
. O
Change O
archive O
command O
After O
this O
activation O
cycle O
, O
the O
malware O
will O
start O
the O
collection O
of O
information O
activities O
and O
dissemination O
. O
Malicious O
activity O
Once O
the O
activation O
cycle O
ends O
, O
the O
trojan O
will O
start O
its O
malicious O
activities O
. O
These O
activities O
depend O
on O
the O
device O
configuration O
. O
Depending O
if O
the O
victim O
has O
any O
of O
the O
targeted O
applications O
, O
the O
anti-virus O
installed O
or O
geographic O
location O
, O
the O
malware O
can O
harvest O
credentials O
from O
the O
targeted O
applications O
, O
exfiltrate O
all O
personal O
information O
or O
simply O
use O
the O
victim O
's O
device O
to O
send O
SMS O
to O
spread O
the O
trojan O
The O
malware O
deploys O
overlaying O
webviews O
to O
trick O
the O
user O
and O
eventually O
steal O
their O
login O
credentials O
. O
These O
are O
adapted O
to O
the O
information O
the O
malicious O
operator O
wants O
to O
retrieve O
. O
The O
first O
webview O
overlay O
is O
created O
on O
step O
6 O
of O
the O
activation O
cycle O
. O
Pin O
request O
overlay O
This O
overlay O
asks O
the O
user O
to O
provide O
their O
PIN O
to O
unlock O
the O
mobile O
device O
, O
which O
is O
immediately O
exfiltrated O
to O
the O
C2 O
. O
The O
last O
step O
of O
the O
activation O
cycle O
is O
the O
download O
of O
a O
password-protected O
ZIP O
file O
. O
This O
file O
contains O
all O
HTML O
, O
CSS O
and O
PNG O
files O
necessary O
to O
create O
overlays O
. O
Talos O
found O
189 O
logos O
from O
banks O
to O
cryptocurrency O
exchanges O
inside O
the O
archive O
, O
all O
of O
which O
could O
be O
targeted O
. O
The O
archive O
also O
contained O
all O
the O
necessary O
codes O
to O
target O
Australian O
financial O
institutions O
. O
The O
overlays O
are O
activated O
by O
the O
malicious O
operator O
using O
the O
command O
changeActivity O
, O
as O
seen O
on O
step O
5 O
of O
the O
activation O
cycle O
. O
In O
this O
case O
, O
we O
can O
see O
that O
the O
HTML O
code O
of O
the O
overlay O
is O
stored O
in O
the O
C2 O
infrastructure O
. O
However O
, O
since O
the O
archive O
that O
is O
downloaded O
into O
the O
device O
has O
all O
the O
necessary O
information O
and O
the O
malicious O
actor O
has O
access O
to O
the O
device O
via O
SMS O
, O
the O
malicious O
operator O
can O
keep O
its O
activity O
even O
without O
the O
C2 O
infrastructure O
. O
Infrastructure O
The O
infrastructure O
supporting O
this O
malware O
is O
rather O
complex O
. O
It O
is O
clear O
that O
on O
all O
stages O
there O
are O
at O
least O
two O
layers O
. O
The O
infrastructure O
has O
several O
layers O
, O
although O
not O
being O
very O
dynamic O
, O
still O
has O
several O
layers O
each O
one O
providing O
some O
level O
of O
protection O
. O
All O
the O
IP O
addresses O
belong O
to O
the O
same O
company O
Hetzner B-Organization
, O
an O
IP-hosting O
firm O
in O
Germany O
. O
COVERAGE O
Cisco B-Organization
Cloud B-System
Web I-System
Security I-System
( O
CWS O
) O
or O
Web B-System
Security I-System
Appliance I-System
( O
WSA O
) O
web O
scanning O
prevents O
access O
to O
malicious O
websites O
and O
detects O
malware O
used O
in O
these O
attacks O
. O
Email O
Security O
can O
block O
malicious O
emails O
sent O
by O
threat O
actors O
as O
part O
of O
their O
campaign O
. O
Network O
Security O
appliances O
such O
as O
Next-Generation B-System
Firewall I-System
( O
NGFW O
) O
, O
Next-Generation B-System
Intrusion I-System
Prevention I-System
System I-System
( O
NGIPS O
) O
, O
and O
Meraki B-System
MX I-System
can O
detect O
malicious O
activity O
associated O
with O
this O
threat O
. O
AMP O
Threat O
Grid O
helps O
identify O
malicious O
binaries O
and O
build O
protection O
into O
all O
Cisco B-Organization
Security O
products O
. O
Umbrella O
, O
our O
secure O
internet O
gateway O
( O
SIG O
) O
, O
blocks O
users O
from O
connecting O
to O
malicious O
domains O
, O
IPs O
, O
and O
URLs O
, O
whether O
users O
are O
on O
or O
off O
the O
corporate O
network O
. O
Open O
Source O
SNORTⓇ O
Subscriber O
Rule O
Set O
customers O
can O
stay O
up O
to O
date O
by O
downloading O
the O
latest O
rule O
pack O
available O
for O
purchase O
on O
Snort.org O
. O
INDICATORS O
OF O
COMPROMISE O
( O
IOCS O
) O
Domains O
Facebook-photos-au.su O
Homevideo2-12l.ml B-Indicator
videohosting1-5j.gq B-Indicator
URLs O
hxxp B-Indicator
: I-Indicator
//88.99.227 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
26/html2/2018/GrafKey/new-inj-135-3-dark.html I-Indicator
hxxp B-Indicator
: I-Indicator
//88.99.227 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
26/html2/arc92/au483x.zip I-Indicator
hxxp B-Indicator
: I-Indicator
//94.130.106 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
117:8080/api/v1/report/records.php I-Indicator
hxxp B-Indicator
: I-Indicator
//88.99.227 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
26/html2/new-inj-135-3-white.html I-Indicator
hxxp B-Indicator
: I-Indicator
//facebook-photos-au I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
su/ChristinaMorrow I-Indicator
hxxp B-Indicator
: I-Indicator
//homevideo2-12l I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ml/mms3/download_3.php I-Indicator
IP O
addresses O
78.46.201.36 B-Indicator
88.99.170.84 B-Indicator
88.99.227.26 B-Indicator
94.130.106.117 B-Indicator
88.99.174.200 B-Indicator
88.99.189.31 B-Indicator
Hash O
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01c5b637f283697350ca361f241416303ab6123da4c6726a6555ac36cb654b5c B-Indicator
1fb06666befd581019af509951320c7e8535e5b38ad058069f4979e9a21c7e1c B-Indicator
6bdfb79f813448b7f1b4f4dbe6a45d1938f3039c93ecf80318cedd1090f7e341 B-Indicator
ADDITIONAL O
INFORMATION O
Packages O
monitored O
pin.secret.access B-Indicator
com.chase.sig.android B-Indicator
com.morganstanley.clientmobile.prod B-Indicator
com.wf.wellsfargomobile B-Indicator
com.citi.citimobile B-Indicator
com.konylabs.capitalone B-Indicator
com.infonow.bofa B-Indicator
com.htsu.hsbcpersonalbanking B-Indicator
com.usaa.mobile.android.usaa B-Indicator
com.schwab.mobile B-Indicator
com.americanexpress.android.acctsvcs.us O
com.pnc.ecommerce.mobile B-Indicator
com.regions.mobbanking B-Indicator
com.clairmail.fth B-Indicator
com.grppl.android.shell.BOS B-Indicator
com.tdbank B-Indicator
com.huntington.m B-Indicator
com.citizensbank.androidapp B-Indicator
com.usbank.mobilebanking B-Indicator
com.ally.MobileBanking B-Indicator
com.key.android B-Indicator
com.unionbank.ecommerce.mobile.android B-Indicator
com.mfoundry.mb.android.mb_BMOH071025661 B-Indicator
com.bbt.cmol B-Indicator
com.sovereign.santander B-Indicator
com.mtb.mbanking.sc.retail.prod B-Indicator
com.fi9293.godough B-Indicator
com.commbank.netbank B-Indicator
org.westpac.bank B-Indicator
org.stgeorge.bank B-Indicator
au.com.nab.mobile B-Indicator
au.com.bankwest.mobile B-Indicator
au.com.ingdirect.android B-Indicator
org.banksa.bank B-Indicator
com.anz.android B-Indicator
com.anz.android.gomoney B-Indicator
com.citibank.mobile.au B-Indicator
org.bom.bank B-Indicator
com.latuabancaperandroid B-Indicator
com.comarch.mobile B-Indicator
com.jpm.sig.android B-Indicator
com.konylabs.cbplpat B-Indicator
by.belinvestbank B-Indicator
no.apps.dnbnor B-Indicator
com.arkea.phonegap B-Indicator
com.alseda.bpssberbank B-Indicator
com.belveb.belvebmobile B-Indicator
com.finanteq.finance.ca B-Indicator
pl.eurobank B-Indicator
pl.eurobank2 B-Indicator
pl.noblebank.mobile B-Indicator
com.getingroup.mobilebanking B-Indicator
hr.asseco.android.mtoken.getin B-Indicator
pl.getinleasing.mobile B-Indicator
com.icp.ikasa.getinon B-Indicator
eu.eleader.mobilebanking.pekao B-Indicator
softax.pekao.powerpay B-Indicator
softax.pekao.mpos B-Indicator
dk.jyskebank.mobilbank B-Indicator
com.starfinanz.smob.android.bwmobilbanking B-Indicator
eu.newfrontier.iBanking.mobile.SOG.Retail B-Indicator
com.accessbank.accessbankapp B-Indicator
com.sbi.SBIFreedomPlus B-Indicator
com.zenithBank.eazymoney B-Indicator
net.cts.android.centralbank B-Indicator
com.f1soft.nmbmobilebanking.activities.main B-Indicator
com.lb.smartpay B-Indicator
com.mbmobile B-Indicator
com.db.mobilebanking B-Indicator
com.botw.mobilebanking B-Indicator
com.fg.wallet B-Indicator
com.sbi.SBISecure B-Indicator
com.icsfs.safwa B-Indicator
com.interswitchng.www B-Indicator
com.dhanlaxmi.dhansmart.mtc B-Indicator
com.icomvision.bsc.tbc B-Indicator
hr.asseco.android.jimba.cecro B-Indicator
com.vanso.gtbankapp B-Indicator
com.fss.pnbpsp B-Indicator
com.mfino.sterling B-Indicator
cy.com.netinfo.netteller.boc B-Indicator
ge.mobility.basisbank B-Indicator
com.snapwork.IDBI B-Indicator
com.lcode.apgvb B-Indicator
com.fact.jib B-Indicator
mn.egolomt.bank B-Indicator
com.pnbrewardz B-Indicator
com.firstbank.firstmobile B-Indicator
wit.android.bcpBankingApp.millenniumPL B-Indicator
com.grppl.android.shell.halifax B-Indicator
com.revolut.revolut B-Indicator
de.commerzbanking.mobil B-Indicator
uk.co.santander.santanderUK B-Indicator
se.nordea.mobilebank B-Indicator
com.snapwork.hdfc B-Indicator
com.csam.icici.bank.imobile B-Indicator
com.msf.kbank.mobile B-Indicator
com.bmm.mobilebankingapp B-Indicator
net.bnpparibas.mescomptes B-Indicator
fr.banquepopulaire.cyberplus B-Indicator
com.caisseepargne.android.mobilebanking B-Indicator
com.palatine.android.mobilebanking.prod B-Indicator
com.ocito.cdn.activity.creditdunord B-Indicator
com.fullsix.android.labanquepostale.accountaccess B-Indicator
mobi.societegenerale.mobile.lappli B-Indicator
com.db.businessline.cardapp B-Indicator
com.skh.android.mbanking B-Indicator
com.ifs.banking.fiid1491 B-Indicator
de.dkb.portalapp B-Indicator
pl.pkobp.ipkobiznes B-Indicator
pl.com.suntech.mobileconnect B-Indicator
eu.eleader.mobilebanking.pekao.firm B-Indicator
pl.mbank B-Indicator
pl.upaid.nfcwallet.mbank B-Indicator
eu.eleader.mobilebanking.bre B-Indicator
pl.asseco.mpromak.android.app.bre B-Indicator
pl.asseco.mpromak.android.app.bre.hd B-Indicator
pl.mbank.mnews B-Indicator
eu.eleader.mobilebanking.raiffeisen B-Indicator
pl.raiffeisen.nfc B-Indicator
hr.asseco.android.jimba.rmb B-Indicator
com.advantage.RaiffeisenBank B-Indicator
pl.bzwbk.ibiznes24 B-Indicator
pl.bzwbk.bzwbk24 B-Indicator
pl.bzwbk.mobile.tab.bzwbk24 B-Indicator
com.comarch.mobile.investment B-Indicator
com.android.vending B-Indicator
com.snapchat.android B-Indicator
jp.naver.line.android B-Indicator
com.viber.voip B-Indicator
com.gettaxi.android B-Indicator
com.whatsapp B-Indicator
com.tencent.mm B-Indicator
com.skype.raider B-Indicator
com.ubercab B-Indicator
com.paypal.android.p2pmobile B-Indicator
com.circle.android B-Indicator
com.coinbase.android B-Indicator
com.walmart.android B-Indicator
com.bestbuy.android B-Indicator
com.ebay.gumtree.au B-Indicator
com.ebay.mobile B-Indicator
com.westernunion.android.mtapp B-Indicator
com.moneybookers.skrillpayments B-Indicator
com.gyft.android B-Indicator
com.amazon.mShop.android.shopping B-Indicator
com.comarch.mobile.banking.bgzbnpparibas.biznes B-Indicator
pl.bnpbgzparibas.firmapp B-Indicator
com.finanteq.finance.bgz B-Indicator
pl.upaid.bgzbnpp B-Indicator
de.postbank.finanzassistent B-Indicator
pl.bph B-Indicator
de.comdirect.android B-Indicator
com.starfinanz.smob.android.sfinanzstatus B-Indicator
de.sdvrz.ihb.mobile.app B-Indicator
pl.ing.mojeing B-Indicator
com.ing.mobile B-Indicator
pl.ing.ingksiegowosc B-Indicator
com.comarch.security.mobilebanking B-Indicator
com.comarch.mobile.investment.ing B-Indicator
com.ingcb.mobile.cbportal B-Indicator
de.buhl.finanzblick B-Indicator
pl.pkobp.iko B-Indicator
pl.ipko.mobile B-Indicator
pl.inteligo.mobile B-Indicator
de.number26.android B-Indicator
pl.millennium.corpApp I-Indicator
eu.transfer24.app O
pl.aliorbank.aib O
pl.corelogic.mtoken B-Indicator
alior.bankingapp.android B-Indicator
com.ferratumbank.mobilebank B-Indicator
com.swmind.vcc.android.bzwbk_mobile.app B-Indicator
de.schildbach.wallet B-Indicator
piuk.blockchain.android B-Indicator
com.bitcoin.mwallet B-Indicator
com.btcontract.wallet B-Indicator
com.bitpay.wallet B-Indicator
com.bitpay.copay B-Indicator
btc.org.freewallet.app B-Indicator
org.electrum.electrum B-Indicator
com.xapo B-Indicator
com.airbitz B-Indicator
com.kibou.bitcoin B-Indicator
com.qcan.mobile.bitcoin.wallet B-Indicator
me.cryptopay.android B-Indicator
com.bitcoin.wallet B-Indicator
lt.spectrofinance.spectrocoin.android.wallet B-Indicator
com.kryptokit.jaxx B-Indicator
com.wirex B-Indicator
bcn.org.freewallet.app B-Indicator
com.hashengineering.bitcoincash.wallet B-Indicator
bcc.org.freewallet.app B-Indicator
com.coinspace.app B-Indicator
btg.org.freewallet.app B-Indicator
net.bither B-Indicator
co.edgesecure.app B-Indicator
com.arcbit.arcbit B-Indicator
distributedlab.wallet B-Indicator
de.schildbach.wallet_test B-Indicator
com.aegiswallet B-Indicator
com.plutus.wallet B-Indicator
com.coincorner.app.crypt B-Indicator
eth.org.freewallet.app B-Indicator
secret.access B-Indicator
secret.pattern B-Indicator
RuMMS B-Malware
: O
The O
Latest O
Family O
of O
Android B-System
Malware O
Attacking O
Users O
in O
Russia O
Via O
SMS O
Phishing O
April O
26 O
, O
2016 O
Introduction O
Recently O
we O
observed O
an O
Android B-Malware
malware O
family O
being O
used O
to O
attack O
users O
in O
Russia O
. O
The O
malware O
samples O
were O
mainly O
distributed O
through O
a O
series O
of O
malicious O
subdomains O
registered O
under O
a O
legitimate O
domain O
belonging O
to O
a O
well-known O
shared O
hosting O
service O
provider O
in O
Russia O
. O
Because O
all O
the O
URLs O
used O
in O
this O
campaign O
have O
the O
form O
of O
hxxp B-Indicator
: I-Indicator
//yyyyyyyy I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
XXXX.ru/mms.apk I-Indicator
( O
where O
XXXX.ru B-Indicator
represents O
the O
hosting O
provider O
’ O
s O
domain O
) O
, O
we O
named O
this O
malware O
family O
RuMMS B-Malware
. O
To O
lure O
the O
victims O
to O
download O
the O
malware O
, O
threat O
actors O
use O
SMS O
phishing O
– O
sending O
a O
short O
SMS O
message O
containing O
a O
malicious O
URL O
to O
the O
potential O
victims O
. O
Unwary O
users O
who O
click O
the O
seemingly O
innocuous O
link O
will O
have O
their O
device O
infected O
with O
RuMMS B-Malware
malware O
. O
Figure O
1 O
describes O
this O
infection O
process O
and O
the O
main O
behaviors O
of O
RuMMS B-Malware
. O
On O
April O
3 O
, O
2016 O
, O
we O
still O
observed O
new O
RuMMS B-Malware
samples O
emerging O
in O
the O
wild O
. O
The O
earliest O
identified O
sample O
, O
however O
, O
can O
be O
traced O
back O
to O
Jan. O
18 O
, O
2016 O
. O
Within O
this O
time O
period O
, O
we O
identified O
close O
to O
300 O
samples O
belonging O
to O
this O
family O
( O
all O
sample O
hashes O
are O
listed O
in O
the O
Appendix O
) O
. O
After O
landing O
on O
the O
victim O
’ O
s O
phone O
, O
the O
RuMMS B-Malware
apps O
will O
request O
device O
administrator O
privileges O
, O
remove O
their O
icons O
to O
hide O
themselves O
from O
users O
, O
and O
remain O
running O
in O
the O
background O
to O
perform O
a O
series O
of O
malicious O
behaviors O
. O
So O
far O
we O
have O
identified O
the O
following O
behaviors O
: O
Sending O
device O
information O
to O
a O
remote O
command O
and O
control O
( O
C2 O
) O
server O
. O
Contacting O
the O
C2 O
server O
for O
instructions O
. O
Sending O
SMS O
messages O
to O
financial O
institutions O
to O
query O
account O
balances O
. O
Uploading O
any O
incoming O
SMS O
messages O
( O
including O
the O
balance O
inquiry O
results O
) O
to O
the O
remote O
C2 O
server O
. O
Sending O
C2-specified O
SMS O
messages O
to O
phone O
numbers O
in O
the O
victim O
’ O
s O
contacts O
. O
Forward O
incoming O
phone O
calls O
to O
intercept O
voice-based O
two-factor O
authentication O
. O
Each O
of O
these O
behaviors O
is O
under O
the O
control O
of O
the O
remote O
C2 O
server O
. O
In O
other O
words O
, O
the O
C2 O
server O
can O
specify O
the O
message O
contents O
to O
be O
sent O
, O
the O
time O
period O
in O
which O
to O
forward O
the O
voice O
call O
, O
and O
the O
recipients O
of O
outgoing O
messages O
. O
As O
part O
of O
our O
investigation O
into O
this O
malware O
, O
we O
emulated O
an O
infected O
Android B-System
device O
in O
order O
to O
communicate O
with O
the O
RuMMS B-Malware
C2 O
server O
. O
During O
one O
session O
, O
the O
C2 O
server O
commanded O
our O
emulated O
device O
to O
send O
four O
different O
SMS O
messages O
to O
four O
different O
phone O
numbers O
, O
all O
of O
which O
were O
associated O
with O
Russian O
financial O
institutions O
. O
At O
least O
three O
of O
the O
messages O
were O
intended O
to O
check O
a O
user O
’ O
s O
account O
balance O
at O
the O
institution O
( O
we O
could O
not O
confirm O
the O
purpose O
of O
the O
fourth O
) O
.Through O
additional O
research O
, O
we O
identified O
several O
forum O
posts O
where O
victims O
complained O
of O
funds O
( O
up O
to O
600 O
rubles O
) O
were O
transferred O
out O
of O
their O
accounts O
after O
RuMMS B-Malware
infected O
their O
phones O
. O
We O
do O
not O
know O
exactly O
how O
many O
people O
have O
been O
infected O
with O
RuMMS B-Malware
malware O
. O
However O
, O
our O
data O
suggests O
that O
there O
have O
been O
at O
least O
2,729 O
infections O
between O
January O
2016 O
and O
early O
April O
2016 O
, O
with O
a O
peak O
in O
March O
of O
more O
than O
1,100 O
infections O
. O
Smishing O
: O
The O
Major O
Way O
To O
Distribute O
RuMMS B-Malware
We O
have O
not O
observed O
any O
instances O
of O
RuMMS B-Malware
on O
Google B-System
Play I-System
or O
other O
online O
app O
stores O
. O
Smishing O
( O
SMS O
phishing O
) O
is O
currently O
the O
primary O
way O
threat O
actors O
are O
distributing O
the O
malware O
. O
The O
process O
starts O
when O
an O
SMS O
phishing O
message O
arrives O
at O
a O
user O
’ O
s O
phone O
. O
An O
example O
SMS O
message O
is O
shown O
in O
Figure O
1 O
. O
The O
message O
translates O
roughly O
to O
“ O
You O
got O
a O
photo O
in O
MMS O
format O
: O
hxxp B-Indicator
: I-Indicator
//yyyyyyyy.XXXX.ru/mms.apk. I-Indicator
” O
So O
far O
we O
identified O
seven O
different O
URLs O
being O
used O
to O
spread O
RuMMS B-Malware
in O
the O
wild O
. O
All O
of O
the O
URLs O
reference O
the O
file O
“ O
mms.apk B-Indicator
” O
and O
all O
use O
the O
domain O
“ O
XXXX.ru B-Indicator
” O
, O
which O
belongs O
to O
a O
top O
five O
shared O
hosting O
platform O
in O
Russia O
( O
the O
domain O
itself O
has O
been O
obfuscated O
to O
anonymize O
the O
provider O
) O
. O
The O
threat O
actors O
registered O
at O
least O
seven O
subdomains O
through O
the O
hosting O
provider O
, O
each O
consisting O
of O
eight O
random-looking O
characters O
( O
asdfgjcr B-Indicator
, O
cacama18 B-Indicator
, O
cacamadf B-Indicator
, O
konkonq2 B-Indicator
, O
mmsmtsh5 B-Indicator
, O
riveroer B-Indicator
, O
and O
sdfkjhl2 B-Indicator
. O
) O
As O
of O
this O
writing O
, O
no O
files O
were O
hosted O
at O
any O
of O
the O
links O
. O
The O
threat O
actors O
seem O
to O
have O
abandoned O
these O
URLs O
and O
might O
be O
looking O
into O
other O
ways O
to O
reach O
more O
victims O
. O
Use O
of O
a O
shared O
hosting O
service O
to O
distribute O
malware O
is O
highly O
flexible O
and O
low O
cost O
for O
the O
threat O
actors O
. O
It O
is O
also O
much O
harder O
for O
network O
defenders O
or O
researchers O
to O
track O
a O
campaign O
where O
the O
infrastructure O
is O
a O
moving O
target O
. O
Many O
top O
providers O
in O
Russia O
offer O
cheap O
prices O
for O
their O
shared O
hosting O
services O
, O
and O
some O
even O
provide O
free O
30-day O
trial O
periods O
. O
Threat O
actors O
can O
register O
subdomains O
through O
the O
hosting O
provider O
and O
use O
the O
provider O
’ O
s O
services O
for O
a O
short-period O
campaign O
. O
A O
few O
days O
later O
they O
can O
cancel O
the O
trial O
and O
do O
not O
need O
to O
pay O
a O
penny O
. O
In O
addition O
, O
these O
out-of-the-box O
hosting O
services O
usually O
provide O
better O
infrastructure O
than O
the O
attackers O
could O
manage O
to O
construct O
( O
or O
compromise O
) O
themselves O
. O
RuMMS B-Malware
Code O
Analysis O
All O
RuMMS B-Malware
samples O
share O
the O
same O
behaviors O
, O
major O
parts O
of O
which O
are O
shown O
in O
Figure O
1 O
. O
However O
, O
the O
underlying O
code O
can O
be O
quite O
different O
in O
that O
various O
obfuscation O
mechanisms O
were O
adopted O
to O
evade O
detection O
by O
anti-virus O
tools O
. O
We O
used O
a O
sample O
app O
named O
“ O
org.starsizew B-Indicator
” O
with O
an O
MD5 O
of O
d8caad151e07025fdbf5f3c26e3ceaff B-Indicator
to O
analyze O
RuMMS B-Malware
’ O
s O
code O
. O
Several O
of O
the O
main O
components O
of O
RuMMS B-Malware
are O
shown O
in O
Figure O
2 O
. O
The O
activity O
class O
“ O
org.starsizew.MainActivity B-Indicator
” O
executes O
when O
the O
app O
is O
started O
. O
It O
first O
starts O
another O
activity O
defined O
in O
“ O
org.starsizew.Aa B-Indicator
” O
to O
request O
device O
administrator O
privileges O
, O
and O
then O
calls O
the O
following O
API O
of O
“ O
android.content.pm.PackageManager B-Indicator
” O
( O
the O
Android B-System
package O
manager O
to O
remove O
its O
own O
icon O
on O
the O
home O
screen O
in O
order O
to O
conceal O
the O
existence O
of O
RuMMS B-Malware
from O
the O
user O
: O
At O
the O
same O
time O
, O
” O
org.starsizew.MainActivity B-Indicator
” O
will O
start O
the O
main O
service O
as O
defined O
in O
“ O
org.starsizew.Tb B-Indicator
” O
, O
and O
use O
a O
few O
mechanisms O
to O
keep O
the O
main O
service O
running O
continuously O
in O
the O
background O
. O
The O
class O
“ O
org.starsizew.Ac B-Indicator
” O
is O
designed O
for O
this O
purpose O
; O
its O
only O
task O
is O
to O
check O
if O
the O
main O
service O
is O
running O
, O
and O
restart O
the O
main O
service O
if O
the O
answer O
is O
no O
. O
The O
class O
“ O
org.starsizew.Tb B-Indicator
” O
also O
has O
a O
self-monitoring O
mechanism O
to O
restart O
itself O
when O
its O
own O
onDestroy O
API O
is O
triggered O
. O
Other O
than O
that O
, O
its O
major O
functionality O
is O
to O
collect O
private O
device O
information O
, O
upload O
it O
to O
a O
remote O
C2 O
server O
, O
and O
handle O
any O
commands O
as O
requested O
by O
the O
C2 O
server O
. O
All O
those O
functions O
are O
implemented O
in O
asynchronous O
tasks O
by O
“ O
org.starsizew.i B-Indicator
” O
. O
The O
class O
“ O
org.starsizew.Ma B-Indicator
” O
is O
registered O
to O
intercept O
incoming O
SMS O
messages O
, O
the O
arrival O
of O
which O
will O
trigger O
the O
Android B-System
system O
to O
call O
its O
“ O
onReceive O
” O
API O
. O
Its O
major O
functionality O
is O
also O
implemented O
through O
the O
call O
of O
the O
asynchronous O
task O
( O
“ O
org.starsizew.i B-Indicator
” O
) O
, O
including O
uploading O
the O
incoming O
SMS O
messages O
to O
the O
remote O
C2 O
server O
and O
executing O
any O
commands O
as O
instructed O
by O
the O
remote O
attacker O
. O
C2 O
Communication O
The O
C2 O
communication O
includes O
two O
parts O
: O
sending O
information O
to O
the O
remote O
HTTP O
server O
and O
parsing O
the O
server O
’ O
s O
response O
to O
execute O
any O
commands O
as O
instructed O
by O
the O
remote O
attackers O
. O
The O
functionality O
for O
these O
two O
parts O
is O
implemented O
by O
doInBackground O
and O
onPostExecute O
respectively O
, O
two O
API O
methods O
of O
“ O
android.os.AsyncTask B-Indicator
” O
as O
extended O
by O
class O
“ O
org.starsizew.i B-Indicator
” O
. O
Figure O
3 O
. O
Method O
doInBackground O
: O
to O
send O
information O
to O
remote O
C2 O
server O
As O
seen O
from O
the O
major O
code O
body O
of O
method O
doInBackground O
shown O
in O
Figure O
3 O
( O
some O
of O
the O
original O
classes O
and O
methods O
are O
renamed O
for O
easier O
understanding O
) O
, O
there O
are O
three O
calls O
to O
HttpPost O
with O
different O
contents O
as O
parameters O
. O
At O
line O
5 O
, O
local O
variable O
v4 O
specifies O
the O
first O
parameter O
url O
, O
which O
can O
be O
changed O
by O
the O
remote O
C2 O
server O
later O
. O
These O
URLs O
are O
all O
in O
the O
form O
of O
“ O
http B-Indicator
: I-Indicator
// I-Indicator
$ I-Indicator
C2. I-Indicator
$ I-Indicator
SERVER. I-Indicator
$ I-Indicator
IP/api/ I-Indicator
? I-Indicator
id= I-Indicator
$ I-Indicator
NUM I-Indicator
” O
. O
The O
second O
parameter O
is O
a O
constant O
string O
“ O
POST O
” O
, O
and O
the O
third O
parameter O
is O
a O
series O
of O
key-value O
pairs O
to O
be O
sent O
, O
assembled O
at O
runtime O
. O
The O
value O
of O
the O
first O
item O
, O
whose O
key O
is O
“ O
method O
” O
( O
line O
7 O
) O
, O
indicates O
the O
type O
of O
the O
contents O
: O
install O
, O
info O
and O
sms O
. O
The O
first O
type O
of O
content O
, O
starting O
with O
“ O
method=install O
” O
, O
will O
be O
sent O
when O
the O
app O
is O
started O
for O
the O
first O
time O
, O
including O
the O
following O
device O
private O
information O
: O
Victim O
identifier O
Network O
operator O
Device O
model O
Device O
OS O
version O
Phone O
number O
Device O
identifier O
App O
version O
Country O
The O
second O
type O
of O
information O
will O
be O
sent O
periodically O
to O
indicate O
that O
the O
device O
is O
alive O
. O
It O
only O
has O
two O
parts O
, O
the O
method O
indicated O
by O
word O
“ O
info O
” O
and O
the O
victim O
identifier O
. O
The O
third O
type O
of O
information O
will O
be O
sent O
when O
RuMMS B-Malware
intercepts O
any O
SMS O
messages O
, O
including O
the O
balance O
inquiry O
results O
when O
it O
contacts O
the O
SMS O
code O
of O
a O
particular O
financial O
service O
. O
Method O
onPostExecute O
parses O
the O
response O
from O
the O
above O
HTTP O
session O
and O
executes O
the O
commands O
provided O
by O
the O
remote O
attacker O
. O
As O
seen O
from O
the O
code O
in O
Figure O
5 O
, O
the O
commands O
RuMMS B-Malware
supports O
right O
now O
include O
: O
install_true O
: O
to O
modify O
app O
preference O
to O
indicate O
that O
the O
C2 O
server O
received O
the O
victim O
device O
’ O
s O
status O
. O
sms_send O
: O
to O
send O
C2-specified O
SMS O
messages O
to O
C2-specified O
recipients O
. O
sms_grab O
: O
to O
upload O
periodically O
the O
SMS O
messages O
in O
the O
inbox O
to O
C2 O
server O
. O
delivery O
: O
to O
deliver O
specified O
text O
to O
all O
victim O
’ O
s O
contacts O
( O
SMS O
worming O
) O
. O
call_number O
: O
to O
forward O
phone O
calls O
to O
intercept O
voice O
based O
two-factor O
authentication O
. O
new_url O
: O
to O
change O
the O
URL O
of O
the O
C2 O
server O
in O
the O
app O
preference O
. O
ussd O
: O
to O
call O
a O
C2-specified O
phone O
number O
. O
Figure O
5 O
. O
Method O
onPostExecute O
: O
to O
handle O
instructions O
from O
remote O
C2 O
Figure O
6 O
shows O
an O
example O
response O
sent O
back O
from O
one O
C2 O
server O
. O
Note O
that O
inside O
this O
single O
response O
, O
there O
is O
one O
“ O
install_true O
” O
command O
, O
one O
“ O
sms_grab O
” O
command O
and O
four O
“ O
sms_send O
” O
commands O
. O
With O
the O
four O
“ O
sms_send O
” O
commands O
, O
the O
messages O
as O
specified O
in O
the O
key O
“ O
text O
” O
will O
be O
sent O
immediately O
to O
the O
specified O
short O
numbers O
. O
Our O
analysis O
suggests O
that O
the O
four O
short O
numbers O
are O
associated O
with O
Russian O
financial O
institutions O
, O
presumably O
where O
a O
victim O
would O
be O
likely O
to O
have O
accounts O
. O
Figure O
6 O
. O
Example O
Response O
in O
JSON O
format O
In O
particular O
, O
short O
number O
“ O
+7494 O
” O
is O
associated O
with O
a O
payment O
service O
provider O
in O
Russia O
. O
The O
provider O
’ O
s O
website O
described O
how O
the O
code O
7494 O
can O
be O
used O
to O
provide O
a O
series O
of O
payment-related O
capabilities O
. O
For O
example O
, O
sending O
text O
“ O
Balance O
” O
will O
trigger O
a O
response O
with O
the O
victim O
’ O
s O
wallet O
balance O
. O
Sending O
text O
“ O
confirm O
1 O
” O
will O
include O
proof O
of O
payment O
. O
Sending O
text O
“ O
call O
on O
” O
will O
activate O
the O
USSD O
payment O
confirmation O
service O
. O
During O
our O
investigation O
, O
we O
observed O
the O
C2 O
server O
sending O
multiple O
“ O
balance O
” O
commands O
to O
different O
institutions O
, O
presumably O
to O
query O
the O
victim O
’ O
s O
financial O
account O
balances O
. O
RuMMS B-Malware
can O
upload O
responses O
to O
the O
balance O
inquiries O
( O
received O
via O
SMS O
message O
) O
to O
the O
remote O
C2 O
server O
, O
which O
can O
send O
back O
additional O
commands O
to O
be O
sent O
from O
the O
victim O
to O
the O
provider O
’ O
s O
payment O
service O
. O
These O
could O
include O
resetting O
the O
user O
’ O
s O
PIN O
, O
enabling O
or O
disabling O
various O
alerts O
and O
confirmations O
, O
and O
confirming O
the O
user O
’ O
s O
identity O
. O
RuMMS B-Malware
Samples O
, O
C2 O
, O
Hosting O
Sites O
, O
Infections O
and O
Timeline O
In O
total O
we O
captured O
297 O
RuMMS B-Malware
samples O
, O
all O
of O
which O
attempt O
to O
contact O
an O
initial O
C2 O
server O
that O
we O
extracted O
from O
the O
app O
package O
. O
Figure O
7 O
lists O
the O
IP O
addresses O
of O
these O
C2 O
servers O
, O
the O
number O
of O
RuMMS B-Malware
apps O
that O
connect O
to O
each O
of O
them O
, O
and O
the O
example O
URL O
used O
as O
the O
first O
parameter O
of O
the O
HttpPost O
operation O
( O
used O
in O
the O
code O
of O
Figure O
3 O
) O
. O
This O
indicates O
that O
multiple O
C2 O
servers O
were O
used O
in O
this O
campaign O
, O
but O
one O
( O
37.1.207.31 B-Indicator
) O
was O
the O
most O
heavily O
used O
. O
Figure O
7 O
. O
RuMMS B-Malware
samples O
and O
C2 O
servers O
Figure O
8 O
shows O
how O
these O
samples O
, O
C2 O
servers O
and O
hosting O
websites O
are O
related O
to O
each O
other O
, O
including O
when O
they O
were O
compiled O
or O
observed O
. O
In O
the O
quadrant O
, O
the O
smaller O
boxes O
in O
blue-gray O
represent O
particular O
apps O
in O
the O
RuMMS B-Malware
family O
, O
while O
the O
bigger O
boxes O
in O
deep-blue O
represent O
C2 O
servers O
used O
by O
some O
RuMMS B-Malware
apps O
. O
The O
dotted O
arrows O
represent O
the O
use O
of O
a O
particular O
C2 O
server O
by O
a O
specific O
app O
to O
send O
information O
and O
fetch O
instructions O
. O
In O
this O
figure O
we O
have O
11 O
RuMMS B-Malware
samples O
, O
all O
of O
which O
were O
hosted O
on O
the O
website O
as O
shown O
in O
the O
“ O
y O
” O
axis O
. O
The O
dates O
on O
the O
“ O
x O
” O
axis O
show O
the O
dates O
when O
we O
first O
saw O
these O
apps O
in O
the O
wild O
. O
This O
figure O
demonstrates O
the O
following O
interesting O
information O
: O
The O
time O
range O
when O
threat O
actors O
distributed O
RuMMS B-Malware
on O
those O
shared-hosting O
websites O
is O
from O
January O
2016 O
to O
March O
2016 O
. O
Threat O
actors O
used O
different O
websites O
to O
host O
different O
payloads O
at O
different O
times O
. O
This O
kind O
of O
“ O
moving O
target O
” O
behavior O
made O
it O
harder O
to O
track O
their O
actions O
. O
The O
same O
websites O
have O
hosted O
different O
RuMMS B-Malware
samples O
at O
different O
dates O
. O
C2 O
servers O
are O
shared O
by O
multiple O
samples O
. O
This O
matches O
our O
observations O
of O
C2 O
servers O
as O
shown O
in O
Figure O
7 O
. O
Figure O
8 O
. O
RuMMS B-Malware
samples O
, O
hosting O
sites O
, O
C2 O
servers O
from O
Jan. O
2016 O
to O
Mar O
. O
2016 O
We O
do O
not O
know O
exactly O
how O
many O
people O
have O
been O
infected O
with O
RuMMS B-Malware
malware O
; O
however O
, O
our O
data O
suggests O
that O
there O
are O
at O
least O
2,729 O
infections O
with O
RuMMS B-Malware
samples O
from O
January O
2016 O
to O
early O
April O
2016 O
. O
Figure O
9 O
shows O
the O
number O
of O
RuMMS B-Malware
infections O
recorded O
in O
the O
last O
four O
months O
. O
When O
we O
first O
observed O
the O
malware O
in O
January O
, O
we O
recorded O
380 O
infections O
. O
In O
February O
, O
we O
recorded O
767 O
infections O
. O
In O
March O
, O
it O
peaked O
at O
1,169 O
infections O
. O
In O
April O
, O
at O
the O
time O
of O
writing O
this O
post O
, O
we O
recorded O
413 O
RuMMS B-Malware
infections O
. O
Although O
the O
propagation O
trend O
seems O
to O
be O
slowing O
down O
a O
bit O
, O
the O
figure O
tells O
us O
that O
RuMMS B-Malware
malware O
is O
still O
alive O
in O
the O
wild O
. O
We O
continue O
to O
monitor O
its O
progress O
. O
Conclusion O
Smishing O
( O
SMS O
phishing O
) O
offers O
a O
unique O
vector O
to O
infect O
mobile O
users O
. O
The O
recent O
RuMMS B-Malware
campaign O
shows O
that O
Smishing O
is O
still O
a O
popular O
means O
for O
threat O
actors O
to O
distribute O
their O
malware O
. O
In O
addition O
, O
the O
use O
of O
shared-hosting O
providers O
adds O
flexibility O
to O
the O
threat O
actor O
’ O
s O
campaign O
and O
makes O
it O
harder O
for O
defending O
parties O
to O
track O
these O
moving O
targets O
. O
Fortunately O
, O
FireEye B-System
Mobile I-System
Threat I-System
Prevention I-System
platform O
can O
recognize O
the O
malicious O
SMS O
and O
networking O
behaviors O
used O
by O
these O
RuMMS B-Malware
samples O
, O
and O
help O
us O
quickly O
identify O
the O
threat O
. O
To O
protect O
yourself O
from O
these O
threats O
, O
FireEye B-Organization
suggests O
that O
users O
: O
Take O
caution O
before O
clicking O
any O
links O
where O
you O
are O
not O
sure O
about O
the O
origin O
. O
Don O
’ O
t O
install O
apps O
outside O
the O
official O
app O
store O
. O
Exodus B-Malware
: O
New O
Android B-System
Spyware O
Made O
in O
Italy O
Mar O
29 O
Summary O
We O
identified O
a O
new O
Android B-System
spyware O
platform O
we O
named O
Exodus B-Malware
, O
which O
is O
composed O
of O
two O
stages O
we O
call O
Exodus B-Malware
One I-Malware
and O
Exodus B-Malware
Two I-Malware
. O
We O
have O
collected O
numerous O
samples O
spanning O
from O
2016 O
to O
early O
2019 O
. O
Instances O
of O
this O
spyware O
were O
found O
on O
the O
Google B-System
Play I-System
Store I-System
, O
disguised O
as O
service O
applications O
from O
mobile O
operators O
. O
Both O
the O
Google B-System
Play I-System
Store I-System
pages O
and O
the O
decoys O
of O
the O
malicious O
apps O
are O
in O
Italian O
. O
According O
to O
publicly O
available O
statistics O
, O
as O
well O
as O
confirmation O
from O
Google B-Organization
, O
most O
of O
these O
apps O
collected O
a O
few O
dozens O
installations O
each O
, O
with O
one O
case O
reaching O
over O
350 O
. O
All O
of O
the O
victims O
are O
located O
in O
Italy O
. O
All O
of O
these O
Google B-System
Play I-System
Store I-System
pages O
have O
been O
taken O
down O
by O
Google B-Organization
. O
We O
believe O
this O
spyware O
platform O
is O
developed O
by O
an O
Italian O
company O
called O
eSurv B-Organization
, O
which O
primarily O
operates O
in O
the O
business O
of O
video O
surveillance O
. O
According O
to O
public O
records O
it O
appears O
that O
eSurv B-Organization
began O
to O
also O
develop O
intrusion O
software O
in O
2016 O
. O
Exodus B-Malware
is O
equipped O
with O
extensive O
collection O
and O
interception O
capabilities O
. O
Worryingly O
, O
some O
of O
the O
modifications O
enforced O
by O
the O
spyware O
might O
expose O
the O
infected O
devices O
to O
further O
compromise O
or O
data O
tampering O
. O
Disguised O
Spyware O
Uploaded O
on O
Google B-System
Play I-System
Store I-System
We O
identified O
previously O
unknown O
spyware O
apps O
being O
successfully O
uploaded O
on O
Google B-System
Play I-System
Store I-System
multiple O
times O
over O
the O
course O
of O
over O
two O
years O
. O
These O
apps O
would O
remain O
available O
on O
the O
Play B-System
Store I-System
for O
months O
and O
would O
eventually O
be O
re-uploaded O
. O
While O
details O
would O
vary O
, O
all O
of O
the O
identified O
copies O
of O
this O
spyware O
shared O
a O
similar O
disguise O
. O
In O
most O
cases O
they O
would O
be O
crafted O
to O
appear O
as O
applications O
distributed O
by O
unspecified O
mobile O
operators O
in O
Italy O
. O
Often O
the O
app O
description O
on O
the O
Play B-System
Store I-System
would O
reference O
some O
SMS O
messages O
the O
targets O
would O
supposedly O
receive O
leading O
them O
to O
the O
Play B-System
Store I-System
page O
. O
All O
of O
the O
Play B-System
Store I-System
pages O
we O
identified O
and O
all O
of O
the O
decoys O
of O
the O
apps O
themselves O
are O
written O
in O
Italian O
. O
According O
to O
Google B-Organization
, O
whom O
we O
have O
contacted O
to O
alert O
about O
our O
discoveries O
, O
nearly O
25 O
variants O
of O
this O
spyware O
were O
uploaded O
on O
Google B-System
Play I-System
Store I-System
. O
Google B-System
Play I-System
has O
removed O
the O
apps O
and O
they O
stated O
that O
" O
thanks O
to O
enhanced O
detection O
models O
, O
Google B-System
Play I-System
Protect I-System
will O
now O
be O
able O
to O
better O
detect O
future O
variants O
of O
these O
applications O
'' O
. O
While O
Google I-Organization
did O
not O
share O
with O
us O
the O
total O
number O
of O
infected O
devices O
, O
they O
confirmed O
that O
one O
of O
these O
malicious O
apps O
collected O
over O
350 O
installations O
through O
the O
Play B-System
Store I-System
, O
while O
other O
variants O
collected O
few O
dozens O
each O
, O
and O
that O
all O
infections O
were O
located O
in O
Italy O
. O
We O
have O
directly O
observed O
multiple O
copies O
of O
Exodus B-Malware
with O
more O
than O
50 O
installs O
and O
we O
can O
estimate O
the O
total O
number O
of O
infections O
to O
amount O
in O
the O
several O
hundreds O
, O
if O
not O
a O
thousand O
or O
more O
. O
Stage O
1 O
: O
Exodus B-Malware
One I-Malware
The O
first O
stage O
installed O
by O
downloading O
the O
malicious O
apps O
uploaded O
on O
Google B-System
Play I-System
Store I-System
only O
acts O
as O
a O
dropper O
. O
Following O
are O
some O
examples O
of O
the O
decoys O
used O
by O
these O
droppers O
: O
The O
purpose O
of O
Exodus B-Malware
One I-Malware
seems O
to O
be O
to O
collect O
some O
basic O
identifying O
information O
about O
the O
device O
( O
namely O
the O
IMEI O
code O
and O
the O
phone O
number O
) O
and O
send O
it O
to O
the O
Command O
& O
Control O
server O
. O
This O
is O
usually O
done O
in O
order O
to O
validate O
the O
target O
of O
a O
new O
infection O
. O
This O
is O
further O
corroborated O
by O
some O
older O
and O
unobfuscated O
samples O
from O
2016 O
, O
whose O
primary O
classes O
are O
named O
CheckValidTarget O
. O
During O
our O
tests O
the O
spyware O
was O
upgraded O
to O
the O
second O
stage O
on O
our O
test O
device O
immediately O
after O
the O
first O
check-ins O
. O
This O
suggests O
that O
the O
operators O
of O
the O
Command O
& O
Control O
are O
not O
enforcing O
a O
validation O
of O
the O
targets O
. O
Additionally O
, O
during O
a O
period O
of O
several O
days O
, O
our O
infected O
test O
device O
was O
never O
remotely O
disinfected O
by O
the O
operators O
. O
For O
the O
purpose O
of O
this O
report O
we O
analyze O
here O
the O
Exodus B-Malware
One I-Malware
sample O
with O
hash O
8453ce501fee1ca8a321f16b09969c517f92a24b058ac5b54549eabd58bf1884 B-Indicator
which O
communicated O
with O
the O
Command O
& O
Control O
server O
at O
54.71.249.137 B-Indicator
. O
Other O
samples O
communicated O
with O
other O
servers O
listed O
at O
the O
bottom O
of O
this O
report O
. O
Exodus O
One O
checks-in O
by O
sending O
a O
POST O
request O
containing O
the O
app O
package O
name O
, O
the O
device O
IMEI O
and O
an O
encrypted O
body O
containing O
additional O
device O
information O
. O
The O
encrypted O
body O
is O
composed O
of O
various O
identifiers O
which O
are O
joined O
together O
: O
doFinal O
( O
) O
is O
called O
to O
encrypt O
the O
device O
information O
string O
: O
The O
user O
agent O
string O
is O
built O
from O
the O
package O
name O
and O
IMEI O
number O
: O
Finally O
the O
HTTP O
request O
is O
sent O
to O
the O
server O
at O
https B-Indicator
: I-Indicator
//54.71.249.137/eddd0317-2bdc-4140-86cb-0e8d7047b874 I-Indicator
. O
Many O
of O
the O
strings O
in O
the O
application O
are O
XOR O
'd O
with O
the O
key O
Kjk1MmphFG O
: O
After O
some O
additional O
requests O
, O
the O
dropper O
made O
a O
POST O
request O
to O
https B-Indicator
: I-Indicator
//54.71.249.137/56e087c9-fc56-49bb-bbd0-4fafc4acd6e1 I-Indicator
which O
returned O
a O
zip O
file O
containing O
the O
second O
stage O
binaries O
. O
Stage O
2 O
: O
Exodus B-Malware
Two I-Malware
The O
Zip O
archive O
returned O
by O
the O
check-in O
performed O
by O
Exodus B-Malware
One I-Malware
is O
a O
collection O
of O
files O
including O
the O
primary O
payload O
mike.jar B-Indicator
and O
several O
compiled O
utilities O
that O
serve O
different O
functions O
. O
At O
least O
in O
most O
recent O
versions O
, O
as O
of O
January O
2019 O
, O
the O
Zip O
archive O
would O
actually O
contain O
the O
i686 O
, O
arm O
and O
arm64 O
versions O
of O
all O
deployed O
binaries O
. O
File O
Name O
Modified O
Date O
SHA256 O
null_arm O
2018-02-27 O
06:44:00 O
48a7dd672931e408662d2b5e1abcd6ef00097b8ffe3814f0d2799dd6fd74bd88 B-Indicator
null_i686 O
2018-02-27 O
06:44:00 O
c228a534535b22a316a97908595a2d793d0fecabadc32846c6d1bfb08ca9a658 B-Indicator
null_arm64 O
2018-02-27 O
06:43:00 O
48a7dd672931e408662d2b5e1abcd6ef00097b8ffe3814f0d2799dd6fd74bd88 B-Indicator
sepolicy-inject_arm O
2019-01-08 O
04:55:00 O
47449a612697ad99a6fbd6e02a84e957557371151f2b034a411ebb10496648c8 B-Indicator
sepolicy-inject_arm64 O
2019-01-08 O
04:55:00 O
824ad333320cbb7873dc49e61c14f749b0e0d88723635524463f2e6f56ea133a B-Indicator
sepolicy-inject_i686 O
2019-01-08 O
04:55:00 O
13ec6cec511297ac3137cf7d6e4a7c4f5dd2b24478a06262a44f13a3d61070b6 B-Indicator
rootdaemon_arm O
2019-01-08 O
04:55:00 O
00c787c0c0bc26caf623e66373a5aaa1b913b9caee1f34580bdfdd21954b7cc4 B-Indicator
rootdaemon_arm64 O
2019-01-08 O
04:55:00 O
3ee3a973c62ba5bd9eab595a7c94b7a26827c5fa5b21964d511ab58903929ec5 B-Indicator
mike.jar B-Indicator
2018-12-06 O
05:50:00 O
a42a05bf9b412cd84ea92b166d790e8e72f1d01764f93b05ace62237fbabe40e B-Indicator
rootdaemon_i686 O
2019-01-08 O
04:55:00 O
b46f282f9a1bce3798faee3212e28924730a657eb93cda3824c449868b6ee2e7 B-Indicator
zygotedaemonarm O
2019-01-08 O
04:55:00 O
e3f65f84dd6c2c3a5a653a3788d78920c0321526062a6b53daaf23fa57778a5f B-Indicator
zygotedaemonarm64 O
2019-01-08 O
04:55:00 O
11499ff2418f4523344de81a447f6786fdba4982057d4114f64db929990b4b59 B-Indicator
zygotedaemoni686 O
2019-01-08 O
04:55:00 O
3c9f08b3280851f54414dfa5a57f40d3b7be7b73736fa0ba21b078e75ce54d33 B-Indicator
sapp.apk B-Indicator
2019-01-08 O
04:53:00 O
4bf1446c412dd5c552539490d03e999a6ceb96ae60a9e7846427612bec316619 B-Indicator
placeholder O
2018-03-29 O
16:31:00 O
e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855 B-Indicator
After O
download O
, O
Exodus B-Malware
One I-Malware
would O
dynamically O
load O
and O
execute O
the O
primary O
stage O
2 O
payload O
mike.jar B-Indicator
using O
the O
Android B-System
API I-System
DexClassLoader O
( O
) O
. O
mike.jar B-Indicator
implements O
most O
of O
the O
data O
collection O
and O
exfiltration O
capabilities O
of O
this O
spyware O
. O
Of O
the O
various O
binaries O
downloaded O
, O
the O
most O
interesting O
are O
null O
, O
which O
serves O
as O
a O
local O
and O
reverse O
shell O
, O
and O
rootdaemon O
, O
which O
takes O
care O
of O
privilege O
escalation O
and O
data O
acquisition O
. O
rootdaemon O
will O
first O
attempt O
to O
jailbreak O
the O
device O
using O
a O
modified O
version O
of O
the O
DirtyCow B-Vulnerability
exploit I-Vulnerability
. O
Similarly O
to O
another O
Android B-System
spyware O
made O
in O
Italy O
, O
originally O
discovered O
by O
Lukas O
Stefanko O
and O
later O
named O
Skygofree B-Malware
and O
analyzed O
in O
depth O
by O
Kaspersky B-Organization
Labs I-Organization
, O
Exodus B-Malware
also O
takes O
advantage O
of O
" O
protectedapps O
'' O
, O
a O
feature O
in O
Huawei B-Organization
phones O
that O
allows O
to O
configure O
power-saving O
options O
for O
running O
applications O
. O
By O
manipulating O
a O
SQLite O
database O
, O
Exodus B-Malware
is O
able O
to O
keep O
itself O
running O
even O
when O
the O
screen O
goes O
off O
and O
the O
application O
would O
otherwise O
be O
suspended O
to O
reduce O
battery O
consumption O
. O
Additionally O
, O
rootdaemon O
attempts O
to O
remove O
its O
own O
power O
usage O
statistics O
from O
Huawei B-Organization
phones O
' O
SystemManager O
: O
Similarly O
, O
the O
malicious O
application O
probably O
attempts O
to O
minimize O
traces O
on O
Samsung B-Organization
phones O
by O
adding O
to O
the O
file O
/data/data/com.samsung.android.securitylogagent/shared_prefs/apm_sp_status_of_apps.xml B-Indicator
the O
following O
lines O
: O
And O
adding O
to O
the O
file O
/data/data/com.samsung.android.securitylogagent/shared_prefs/com.samsung.android.securitylogagent_preferences.xml B-Indicator
these O
lines O
instead O
: O
Data O
Collection O
and O
Exfiltration O
As O
mentioned O
, O
mike.jar B-Indicator
equips O
the O
spyware O
with O
extensive O
collection O
capabilities O
, O
including O
: O
Retrieve O
a O
list O
of O
installed O
applications O
. O
Record O
surroundings O
using O
the O
built-in O
microphone O
in O
3gp O
format O
. O
Retrieve O
the O
browsing O
history O
and O
bookmarks O
from O
Chrome B-System
and O
SBrowser B-System
( O
the O
browser O
shipped O
with O
Samsung B-Organization
phones O
) O
. O
Extract O
events O
from O
the O
Calendar B-System
app I-System
. O
Extract O
the O
calls O
log O
. O
Record O
phone O
calls O
audio O
in O
3gp O
format O
. O
Take O
pictures O
with O
the O
embedded O
camera O
. O
Collect O
information O
on O
surrounding O
cellular O
towers O
( O
BTS O
) O
. O
Extract O
the O
address B-System
book I-System
. O
Extract O
the O
contacts O
list O
from O
the O
Facebook B-System
app I-System
. O
Extract O
logs O
from O
Facebook B-System
Messenger I-System
conversations O
. O
Take O
a O
screenshot O
of O
any O
app O
in O
foreground O
. O
Extract O
information O
on O
pictures O
from O
the O
Gallery O
. O
Extract O
information O
from O
th O
GMail B-System
app O
. O
Dump O
data O
from O
the O
IMO O
messenger B-System
app O
. O
Extract O
call O
logs O
, O
contacts O
and O
messages O
from O
the O
Skype B-System
app O
. O
Retrieve O
all O
SMS O
messages O
. O
Extract O
messages O
and O
the O
encryption O
key O
from O
the O
Telegram B-System
app O
. O
Dump O
data O
from O
the O
Viber B-System
messenger I-System
app O
. O
Extract O
logs O
from O
WhatsApp B-System
. O
Retrieve O
media O
exchanged O
through O
WhatsApp B-System
. O
Extract O
the O
Wi-Fi O
network O
's O
password O
. O
Extract O
data O
from O
WeChat B-System
app O
. O
Extract O
current O
GPS O
coordinates O
of O
the O
phone O
. O
While O
some O
of O
these O
acquisition O
are O
performed O
purely O
through O
code O
in O
mike.jar B-Indicator
, O
some O
others O
that O
require O
access O
to O
, O
for O
example O
, O
SQLite O
databases O
or O
other O
files O
in O
the O
application O
's O
storage O
are O
performed O
through O
rootdaemon O
instead O
, O
which O
should O
be O
running O
with O
root O
privileges O
. O
In O
order O
to O
achieve O
this O
, O
mike.jar B-Indicator
connects O
to O
rootdaemon O
through O
various O
TCP O
ports O
that O
the O
daemon O
binds O
on O
some O
extraction O
routines O
for O
supported O
applications O
: O
Port B-Indicator
6202 I-Indicator
: O
WhatsApp B-System
extraction O
service O
. O
Ports B-Indicator
6203 I-Indicator
and I-Indicator
6204 I-Indicator
: O
Facebook B-Organization
extraction O
service O
. O
Port B-Indicator
6205 I-Indicator
: O
Gmail B-System
extraction O
service O
. O
Port B-Indicator
6206 I-Indicator
: O
Skype B-System
extraction O
service O
. O
Port B-Indicator
6207 I-Indicator
: O
Viber B-System
extraction O
service O
. O
Port B-Indicator
6208 I-Indicator
: O
IMO B-System
extraction O
service O
. O
Port B-Indicator
6209 I-Indicator
: O
Telegram B-System
extraction O
service O
. O
Port B-Indicator
6210 I-Indicator
: O
SBrowser B-System
extraction O
service O
. O
Port B-Indicator
6211 I-Indicator
: O
Calendar B-System
extraction O
service O
. O
Port B-Indicator
6212 I-Indicator
: O
Chrome B-System
extraction O
service O
. O
These O
services O
appear O
to O
be O
running O
on O
all O
network O
interfaces O
and O
are O
therefore O
accessible O
to O
anyone O
sharing O
a O
local O
network O
with O
an O
infected O
device O
. O
Following O
we O
can O
see O
an O
example O
of O
a O
connection O
to O
port B-Indicator
6209 I-Indicator
which O
is O
used O
to O
extract O
data O
from O
the O
Telegram B-System
app O
. O
We O
are O
able O
to O
send O
commands O
to O
the O
service O
such O
as O
dumpmsgdb O
or O
getkey O
( O
which O
dumps O
the O
tgnet.dat B-Indicator
file I-Indicator
) O
. O
Data O
acquired O
from O
mike.jar B-Indicator
's O
extraction O
modules O
is O
normally O
XORed O
and O
stored O
in O
a O
folder O
named O
.lost+found O
on O
the O
SD O
card O
. O
Data O
is O
eventually O
exfiltrated O
over O
a O
TLS O
connection O
to O
the O
Command O
& O
Control O
server B-Indicator
ws.my-local-weather I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
through O
an O
upload O
queue O
. O
As O
mentioned O
before O
, O
our O
test O
device O
was O
automatically O
from O
stage O
one O
to O
stage O
two O
, O
which O
started O
collecting O
data O
. O
For O
example O
, O
the O
password O
of O
the O
WiFi O
network O
used O
by O
the O
phone O
was O
stored O
in O
the O
folder O
/storage/emulated/0/.lost+found/0BBDA068-9D27-4B55-B226-299FCF2B4242/ B-Indicator
using O
the O
following O
file O
name O
format O
DD_MM_2019_HH_mm_ss_XXXXXXXXXXXXX.txt.crypt B-Indicator
( O
the O
datetime O
followed O
by O
the O
IMEI O
) O
. O
Eventually O
we O
observed O
the O
agent O
exfiltrate O
the O
WiFi O
password O
from O
our O
test O
phone O
to O
the O
Command O
& O
Control O
server O
: O
Similarly O
, O
the O
agent O
also O
sent O
to O
the O
Command O
& O
Control O
the O
list O
of O
installed O
apps O
: O
This O
Command O
& O
Control O
seems O
to O
have O
been O
active O
since O
at O
least O
April O
2017 O
and O
was O
registered O
impersonating O
the O
legitimate O
service O
AccuWeather B-System
. O
Local O
and O
Remote O
Shells O
In O
order O
to O
execute O
commands O
on O
the O
infected O
devices O
, O
as O
well O
as O
to O
provide O
a O
reverse O
shell O
to O
the O
Command O
& O
Control O
operators O
, O
Exodus B-Malware
Two I-Malware
immediately O
attempts O
to O
execute O
a O
payload O
it O
downloads O
with O
the O
name O
null O
. O
Once O
launched O
, O
null O
will O
first O
verify O
whether O
it O
is O
able O
to O
fork O
on O
the O
system O
and O
that O
there O
is O
no O
other O
instance O
of O
itself O
currently O
running O
by O
checking O
whether O
the O
local O
port B-Indicator
number I-Indicator
6842 I-Indicator
is O
available O
. O
This O
payload O
will O
then O
attempt O
to O
instantiate O
a O
remote O
reverse O
/system/bin/sh B-Indicator
shell O
to O
the O
Command O
& O
Control O
ws.my-local-weather B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
on O
port B-Indicator
22011 I-Indicator
. O
It O
is O
worth O
noticing O
that O
this O
remote O
reverse O
shell O
does O
not O
employ O
any O
transport O
cryptography O
. O
The O
traffic O
transits O
in O
clear O
and O
is O
therefore O
potentially O
exposed O
to O
man-in-the-middle O
attacks O
: O
At O
the O
same O
time O
, O
null O
will O
also O
bind O
a O
local O
shell O
on O
0.0.0.0:6842 B-Indicator
. O
This O
local O
port O
is O
used O
by O
Exodus B-Malware
Two I-Malware
to O
execute O
various O
commands O
on O
the O
Android B-System
device O
, O
such O
as O
enabling O
or O
disabling O
certain O
services O
, O
or O
parsing O
app O
databases O
. O
However O
, O
binding O
a O
shell O
on O
all O
available O
interfaces O
will O
obviously O
make O
it O
accessible O
to O
anyone O
who O
is O
sharing O
at O
least O
a O
local O
network O
with O
an O
infected O
device O
. O
For O
example O
, O
if O
an O
infected O
device O
is O
connected O
to O
a O
public O
Wi-Fi O
network O
any O
other O
host O
will O
be O
able O
to O
obtain O
a O
terminal O
on O
the O
device O
without O
any O
form O
of O
authentication O
or O
verification O
by O
simply O
connecting O
to O
the O
port O
. O
If O
the O
mobile O
operator O
does O
n't O
enforce O
proper O
client O
isolation O
, O
it O
is O
possible O
that O
the O
infected O
devices O
are O
also O
exposed O
to O
the O
rest O
of O
the O
cellular O
network O
. O
Obviously O
, O
this O
inevitably O
leaves O
the O
device O
open O
not O
only O
to O
further O
compromise O
but O
to O
data O
tampering O
as O
well O
. O
null O
is O
not O
the O
only O
payload O
opening O
a O
shell O
on O
the O
phone O
. O
The O
rootdaemon O
binary O
in O
fact O
offers O
several O
other O
possibilities O
to O
execute O
commands O
on O
the O
infected O
device O
just O
by O
connecting O
to O
TCP O
port B-Indicator
6200 I-Indicator
and O
issuing O
one O
of O
the O
following O
commands O
. O
Sending O
the O
command O
sh O
to O
TCP O
port B-Indicator
6200 I-Indicator
results O
in O
a O
full O
terminal O
being O
dropped O
: O
Sending O
the O
command O
cmd O
followed O
by O
a O
proper O
terminal O
command O
will O
execute O
it O
and O
print O
the O
output O
( O
in O
the O
example O
we O
use O
id O
which O
displays O
the O
identity O
of O
the O
system O
user O
running O
the O
issued O
commands O
) O
: O
Doing O
the O
same O
as O
above O
but O
with O
command O
sucmd O
will O
run O
the O
terminal O
command O
as O
root O
: O
Other O
commands O
supported O
by O
rootdaemon O
on O
TCP O
port B-Indicator
6200 I-Indicator
are O
su O
( O
which O
in O
our O
tests O
did O
n't O
properly O
work O
) O
, O
loadsocketpolicy O
, O
loadfilepolicy O
, O
remount O
and O
removeroot O
. O
At O
the O
cost O
of O
possibly O
being O
overly O
verbose O
, O
following O
is O
the O
output O
of O
an O
nmap O
scan O
of O
the O
infected O
Android O
device O
from O
a O
laptop O
in O
the O
same O
local O
network O
, O
which O
further O
demonstrantes O
the O
availability O
of O
the O
same O
open O
TCP O
ports O
that O
we O
have O
mentioned O
thus O
far O
: O
Identification O
of O
eSurv B-Organization
Presence O
of O
Italian O
language O
At O
a O
first O
look O
, O
the O
first O
samples O
of O
the O
spyware O
we O
obtained O
did O
not O
show O
immediately O
evident O
connections O
to O
any O
company O
. O
However O
, O
the O
persistent O
presence O
of O
Italian O
language O
both O
on O
the O
Google B-System
Play I-System
Store O
pages O
as O
well O
as O
inside O
the O
spyware O
code O
was O
a O
clear O
sign O
that O
an O
Italian O
actor O
was O
behind O
the O
creation O
of O
this O
platform O
. O
Initially O
some O
particular O
words O
from O
the O
decompiled O
classes.dex B-Indicator
of O
Exodus B-Malware
Two O
sent O
us O
in O
the O
right O
direction O
. O
" O
Mundizza O
'' O
is O
a O
dialectal O
word O
, O
a O
derivative O
of O
the O
proper O
Italian O
word O
" O
immondizia O
'' O
that O
translates O
to O
" O
trash O
'' O
or O
" O
garbage O
'' O
in O
English O
. O
Interestingly O
, O
" O
mundizza O
'' O
is O
typical O
of O
Calabria O
, O
a O
region O
in O
the O
south O
of O
Italy O
, O
and O
more O
specifically O
it O
appears O
to O
be O
language O
native O
of O
the O
city O
of O
Catanzaro O
. O
Additionally O
, O
some O
copies O
of O
Exodus O
One O
use O
the O
following O
XOR O
key O
: O
Rino O
Gattuso O
is O
a O
famous O
retired O
Italian O
footballer O
, O
originally O
from O
Calabria O
. O
While O
not O
too O
seriously O
, O
these O
elements O
made O
us O
restrict O
our O
research O
into O
surveillance O
companies O
from O
the O
region O
. O
Overlapping O
Infrastructure O
with O
eSurv O
Surveillance O
Cameras O
The O
Command O
& O
Control O
domain O
configured O
in O
several O
of O
the O
malicious O
applications O
found O
on O
Google B-System
Play I-System
Store I-System
, O
ws.my-local-weather B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
, O
points O
to O
the O
IP O
address O
54.69.156.31 B-Indicator
which O
serves O
a O
self-signed O
TLS O
certificate O
with O
the O
certificate O
common O
name O
MyCert O
and O
fingerprint O
11:41:45:2F B-Indicator
: I-Indicator
A7:07:23:54 I-Indicator
: O
AE:9A B-Indicator
: I-Indicator
CE I-Indicator
: I-Indicator
F4 I-Indicator
: I-Indicator
FE:56 I-Indicator
: I-Indicator
AE I-Indicator
: I-Indicator
AC I-Indicator
: O
B1 B-Indicator
: I-Indicator
C2:15:9F:6A I-Indicator
: I-Indicator
FC:1E I-Indicator
: I-Indicator
CC:7D I-Indicator
: B-Indicator
F8:61 I-Indicator
: I-Indicator
E3:25:26:73:6A I-Indicator
. O
A O
search O
for O
this O
certificate O
fingerprint O
on O
the O
Internet O
scanning O
service O
Censys O
returns O
8 O
additional O
servers O
: O
IP O
address O
34.208.71.9 B-Indicator
34.212.92.0 B-Indicator
34.216.43.114 B-Indicator
52.34.144.229 B-Indicator
54.69.156.31 B-Indicator
54.71.249.137 B-Indicator
54.189.5.198 B-Indicator
78.5.0.195 B-Indicator
207.180.245.74 B-Indicator
Opening O
the O
Command O
& O
Control O
web O
page O
in O
a O
browser O
presents O
a O
Basic O
Authentication O
prompt O
: O
Closing O
this O
prompt O
causes O
the O
server O
to O
send O
a O
" O
401 O
Unauthorized O
Response O
'' O
with O
an O
" O
Access O
Denied O
'' O
message O
in O
Italian O
. O
All O
of O
the O
other O
IP O
address O
we O
discovered O
sharing O
the O
same O
TLS O
certificate O
behave O
in O
the O
same O
way O
. O
The O
Command O
& O
Control O
server O
also O
displays O
a O
favicon O
image O
which O
looks O
like O
a O
small O
orange O
ball O
. O
At O
the O
time O
of O
writing O
, O
a O
reverse O
image O
search O
for O
the O
favicon O
on O
Shodan O
using O
the O
query O
http.favicon.hash:990643579 B-Indicator
returned O
around O
40 O
web O
servers O
which O
use O
the O
same O
favicon O
. O
Many O
of O
these O
servers O
are O
control O
panels O
for O
video O
surveillance O
systems O
developed O
by O
the O
Italian O
company O
eSurv O
, O
based O
in O
Catanzaro O
, O
in O
Calabria O
, O
Italy O
. O
Their O
publicly O
advertised O
products O
include O
CCTV O
management O
systems O
, O
surveillance O
drones O
, O
face O
and O
license O
plate O
recognition O
systems O
. O
eSurv B-Organization
's O
logo O
is O
identical O
to O
the O
Command O
& O
Control O
server O
favicon O
. O
Older O
samples O
connecting O
to O
eSurv B-Organization
Finally O
, O
Google B-Organization
shared O
with O
us O
some O
older O
samples O
of O
Exodus B-Malware
One I-Malware
( O
with O
hashes O
2055584625d24687bd027a63bc0b8faa7d1a854a535de74afba24840a52b1d2f B-Indicator
and O
a37f5d2418c5f2f64d06ba28fe62edee1293a56158ddfa9f04020e316054363f B-Indicator
) O
which O
are O
not O
obfuscated O
and O
use O
the O
following O
disguise O
: O
The O
configuration O
of O
these O
older O
samples O
is O
very O
similar O
to O
newer O
ones O
, O
but O
it O
provides O
additional O
insights O
being O
not O
obfuscated O
: O
Firstly O
we O
can O
notice O
that O
, O
instead O
of O
generic O
domain O
names O
or O
IP O
addresses O
, O
these O
samples O
communicated O
with O
a O
Command O
& O
Control O
server O
located O
at O
attiva.exodus.esurv B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
( O
" O
attiva O
'' O
is O
the O
Italian O
for O
" O
activate O
'' O
) O
. O
( O
We I-System
named O
the O
spyware O
" O
Exodus O
'' O
after O
this O
Command O
& O
Control O
domain O
name O
. O
) O
Following O
is O
the O
snippet O
of O
code O
in O
these O
older O
Exodus B-Malware
One I-Malware
samples O
showing O
the O
connection O
to O
the O
Command O
& O
Control O
: O
Below O
is O
the O
almost O
identical O
composition O
of O
the O
request O
to O
the O
Command O
& O
Control O
server O
in O
mike.jar B-Indicator
( O
also O
containing O
the O
path O
7e661733-e332-429a-a7e2-23649f27690f O
) O
: O
To O
further O
corroborate O
the O
connection O
of O
the O
Exodus B-Malware
spyware I-Malware
with O
eSurv O
, O
the O
domain B-Indicator
attiva.exodus.esurv.it I-Indicator
resolves O
to O
the O
IP O
212.47.242.236 B-Indicator
which O
, O
according O
to O
public O
passive O
DNS O
data O
, O
in O
2017 O
was O
used O
to O
host O
the O
domain B-Indicator
server1cs.exodus.connexxa.it I-Indicator
. O
Connexxa O
was O
a O
company O
also O
from O
Catanzaro O
. O
According O
to O
publicly O
available O
information O
, O
the O
founder O
of O
Connexxa B-Organization
seems O
to O
also O
be O
the O
CEO O
of O
eSurv B-Organization
. O
Interestingly O
, O
we O
found O
other O
DNS O
records O
mostly O
from O
2017 O
that O
follow O
a O
similar O
pattern O
and O
appear O
to O
contain O
two-letters O
codes O
for O
districts O
in O
Italy O
: O
Server O
City O
server1bo.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Bologna O
server1bs.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Brescia O
server1cs.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Cosenza O
server1ct.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Catania O
server1fermo.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
server1fi.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Firenze O
server1gioiat.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
server1na.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Napoli O
server1rc.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Reggio O
Calabria O
server2ct.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Catania O
server2cz.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Catanzaro O
server2fi.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Firenze O
server2mi.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Milano O
server2rc.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Reggio O
Calabria O
server3bo.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Bologna O
server3ct.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Catania O
server3.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
server3fi.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Firenze O
server4fi.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Firenze O
serverrt.exodus.connexxa B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
Public O
Resume O
Confirms O
Development O
of O
Android B-System
Agent O
Additionally O
, O
an O
employee O
of O
eSurv B-Organization
quite O
precisely O
described O
their O
work O
in O
developing O
an O
" O
agent O
to O
gather O
data O
from O
Android B-System
devices O
and O
send O
it O
to O
a O
C O
& O
C O
server O
'' O
as O
well O
as O
researching O
" O
vulnerabilities O
in O
mobile O
devices O
( O
mainly O
Android B-System
) O
'' O
in O
a O
publicly O
available O
resume O
. O
Further O
details O
in O
it O
reflect O
characteristics O
of O
Exodus B-Malware
( O
such O
as O
the O
bypass O
of O
power O
managers O
we O
described O
from O
Exodus B-Malware
One I-Malware
, O
and O
more O
) O
: O
Indicators O
of O
Compromise O
Exodus B-Malware
One I-Malware
011b6bcebd543d4eb227e840f04e188fb01f2335b0b81684b60e6b45388d3820 B-Indicator
0f5f1409b1ebbee4aa837d20479732e11399d37f05b47b5359dc53a4001314e5 B-Indicator
2055584625d24687bd027a63bc0b8faa7d1a854a535de74afba24840a52b1d2f B-Indicator
26fef238028ee4b5b8da631c77bfb44ada3d5db8129c45dea5df6a51c9ea5f55 B-Indicator
33a9da16d096426c82f150e39fc4f9172677885cfeaedcff10c86414e88be802 B-Indicator
34d000ee1e36efd10eb37e2b79d69249d5a85682a61390a89a1b9391c46bf2ba B-Indicator
4f6146956b50ae3a6e80a1c1f771dba848ba677064eb0e166df5804ac2766898 B-Indicator
5db49122d866967295874ab2c1ce23a7cde50212ff044bbea1da9b49bb9bc149 B-Indicator
70e2eea5609c6954c61f2e5e0a3aea832d0643df93d18d7d78b6f9444dcceef0 B-Indicator
80810a8ec9624f317f832ac2e212dba033212258285344661e5da11b0d9f0b62 B-Indicator
8453ce501fee1ca8a321f16b09969c517f92a24b058ac5b54549eabd58bf1884 B-Indicator
a37f5d2418c5f2f64d06ba28fe62edee1293a56158ddfa9f04020e316054363f B-Indicator
db59407f72666526fca23d31e3b4c5df86f25eff178e17221219216c6975c63f B-Indicator
e0acbb0d7e55fb67e550a6bf5cf5c499a9960eaf5f037b785f9004585202593b B-Indicator
Exodus B-Malware
One I-Malware
Package O
Names O
com.phonecarrier.linecheck B-Indicator
rm.rf I-Indicator
operatore.italia B-Indicator
it.offertetelefonicheperte I-Indicator
it.servizipremium B-Indicator
assistenza.sim B-Indicator
assistenza.linea.riattiva B-Indicator
assistenza.linea B-Indicator
it.promofferte B-Indicator
Exodus B-Malware
Two I-Malware
64c11fdb317d6b7c9930e639f55863df592f23f3c7c861ddd97048891a90c64b B-Indicator
a42a05bf9b412cd84ea92b166d790e8e72f1d01764f93b05ace62237fbabe40e B-Indicator
Exodus B-Malware
Two I-Malware
ELF O
Utilities O
00c787c0c0bc26caf623e66373a5aaa1b913b9caee1f34580bdfdd21954b7cc4 B-Indicator
11499ff2418f4523344de81a447f6786fdba4982057d4114f64db929990b4b59 B-Indicator
13ec6cec511297ac3137cf7d6e4a7c4f5dd2b24478a06262a44f13a3d61070b6 B-Indicator
3c9f08b3280851f54414dfa5a57f40d3b7be7b73736fa0ba21b078e75ce54d33 B-Indicator
3ee3a973c62ba5bd9eab595a7c94b7a26827c5fa5b21964d511ab58903929ec5 B-Indicator
47449a612697ad99a6fbd6e02a84e957557371151f2b034a411ebb10496648c8 B-Indicator
48a7dd672931e408662d2b5e1abcd6ef00097b8ffe3814f0d2799dd6fd74bd88 B-Indicator
824ad333320cbb7873dc49e61c14f749b0e0d88723635524463f2e6f56ea133a B-Indicator
b46f282f9a1bce3798faee3212e28924730a657eb93cda3824c449868b6ee2e7 B-Indicator
c228a534535b22a316a97908595a2d793d0fecabadc32846c6d1bfb08ca9a658 B-Indicator
e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855 B-Indicator
e3f65f84dd6c2c3a5a653a3788d78920c0321526062a6b53daaf23fa57778a5f B-Indicator
Command O
& O
Controls O
ad1.fbsba B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
ws.my-local-weather B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
54.71.249 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
137 I-Indicator
54.69.156 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
31 I-Indicator
162.243.172 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
208 I-Indicator
attiva.exodus.esurv B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
it I-Indicator
The O
rise O
of O
mobile O
banker O
Asacub B-Malware
28 O
AUG O
2018 O
We O
encountered O
the O
Trojan-Banker.AndroidOS.Asacub B-Malware
family O
for O
the O
first O
time O
in O
2015 O
, O
when O
the O
first O
versions O
of O
the O
malware O
were O
detected O
, O
analyzed O
, O
and O
found O
to O
be O
more O
adept O
at O
spying O
than O
stealing O
funds O
. O
The O
Trojan O
has O
evolved O
since O
then O
, O
aided O
by O
a O
large-scale O
distribution O
campaign O
by O
its O
creators O
( O
in O
spring-summer O
2017 O
) O
, O
helping O
Asacub B-Malware
to O
claim O
top O
spots O
in O
last O
year O
’ O
s O
ranking O
by O
number O
of O
attacks O
among O
mobile O
banking O
Trojans O
, O
outperforming O
other O
families O
such O
as O
Svpeng B-Malware
and O
Faketoken B-Malware
. O
We O
decided O
to O
take O
a O
peek O
under O
the O
hood O
of O
a O
modern O
member O
of O
the O
Asacub B-Malware
family O
. O
Our O
eyes O
fell O
on O
the O
latest O
version O
of O
the O
Trojan O
, O
which O
is O
designed O
to O
steal O
money O
from O
owners O
of O
Android B-System
devices O
connected O
to O
the O
mobile O
banking O
service O
of O
one O
of O
Russia O
’ O
s O
largest O
banks O
. O
Asacub B-Malware
versions O
Sewn O
into O
the O
body O
of O
the O
Trojan O
is O
the O
version O
number O
, O
consisting O
of O
two O
or O
three O
digits O
separated O
by O
periods O
. O
The O
numbering O
seems O
to O
have O
started O
anew O
after O
the O
version O
9 O
. O
The O
name O
Asacub B-Malware
appeared O
with O
version O
4 O
in O
late O
2015 O
; O
previous O
versions O
were O
known O
as O
Trojan-SMS.AndroidOS.Smaps B-Indicator
. O
Versions O
5.X.X-8.X.X O
were O
active O
in O
2016 O
, O
and O
versions O
9.X.X-1.X.X O
in O
2017 O
. O
In O
2018 O
, O
the O
most O
actively O
distributed O
versions O
were O
5.0.0 O
and O
5.0.3 O
. O
Communication O
with O
C O
& O
C O
Although O
Asacub B-Malware
’ O
s O
capabilities O
gradually O
evolved O
, O
its O
network O
behavior O
and O
method O
of O
communication O
with O
the O
command-and-control O
( O
C O
& O
C O
) O
server O
changed O
little O
. O
This O
strongly O
suggested O
that O
the O
banking O
Trojans O
, O
despite O
differing O
in O
terms O
of O
capability O
, O
belong O
to O
the O
same O
family O
. O
Data O
was O
always O
sent O
to O
the O
C O
& O
C O
server O
via O
HTTP O
in O
the O
body O
of O
a O
POST O
request O
in O
encrypted O
form O
to O
the O
relative O
address O
/something/index.php B-Indicator
. O
In O
earlier O
versions O
, O
the O
something O
part O
of O
the O
relative O
path O
was O
a O
partially O
intelligible O
, O
yet O
random O
mix O
of O
words O
and O
short O
combinations O
of O
letters O
and O
numbers O
separated O
by O
an O
underscore O
, O
for O
example O
, O
“ O
bee_bomb O
” O
or O
“ O
my_te2_mms O
” O
. O
Example O
of O
traffic O
from O
an O
early O
version O
of O
Asacub B-Malware
( O
2015 O
) O
The O
data O
transmitted O
and O
received O
is O
encrypted O
with O
the O
RC4 O
algorithm O
and O
encoded O
using O
the O
base64 O
standard O
. O
The O
C O
& O
C O
address O
and O
the O
encryption O
key O
( O
one O
for O
different O
modifications O
in O
versions O
4.x O
and O
5.x O
, O
and O
distinct O
for O
different O
C O
& O
Cs O
in O
later O
versions O
) O
are O
stitched O
into O
the O
body O
of O
the O
Trojan O
. O
In O
early O
versions O
of O
Asacub B-Malware
, O
.com O
, O
.biz O
, O
.info O
, O
.in O
, O
.pw O
were O
used O
as O
top-level O
domains O
. O
In O
the O
2016 O
version O
, O
the O
value O
of O
the O
User-Agent O
header O
changed O
, O
as O
did O
the O
method O
of O
generating O
the O
relative O
path O
in O
the O
URL O
: O
now O
the O
part O
before O
/index.php O
is O
a O
mix O
of O
a O
pronounceable O
( O
if O
not O
entirely O
meaningful O
) O
word O
and O
random O
letters O
and O
numbers O
, O
for O
example O
, O
“ O
muromec280j9tqeyjy5sm1qy71 B-Indicator
” O
or O
“ O
parabbelumf8jgybdd6w0qa0 B-Indicator
” O
. O
Moreover O
, O
incoming O
traffic O
from O
the O
C O
& O
C O
server O
began O
to O
use O
gzip O
compression O
, O
and O
the O
top-level O
domain O
for O
all O
C O
& O
Cs O
was O
.com O
: O
Since O
December O
2016 O
, O
the O
changes O
in O
C O
& O
C O
communication O
methods O
have O
affected O
only O
how O
the O
relative O
path O
in O
the O
URL O
is O
generated O
: O
the O
pronounceable O
word O
was O
replaced O
by O
a O
rather O
long O
random O
combination O
of O
letters O
and O
numbers O
, O
for O
example O
, O
“ O
ozvi4malen7dwdh B-Indicator
” O
or O
“ O
f29u8oi77024clufhw1u5ws62 B-Indicator
” O
. O
At O
the O
time O
of O
writing O
this O
article O
, O
no O
other O
significant O
changes O
in O
Asacub B-Malware
’ O
s O
network O
behavior O
had O
been O
observed O
: O
The O
origin O
of O
Asacub B-Malware
It O
is O
fairly O
safe O
to O
say O
that O
the O
Asacub B-Malware
family O
evolved O
from O
Trojan-SMS.AndroidOS.Smaps B-Indicator
. O
Communication O
between O
both O
Trojans O
and O
their O
C O
& O
C O
servers O
is O
based O
on O
the O
same O
principle O
, O
the O
relative O
addresses O
to O
which O
Trojans O
send O
network O
requests O
are O
generated O
in O
a O
similar O
manner O
, O
and O
the O
set O
of O
possible O
commands O
that O
the O
two O
Trojans O
can O
perform O
also O
overlaps O
. O
What O
’ O
s O
more O
, O
the O
numbering O
of O
Asacub B-Malware
versions O
is O
a O
continuation O
of O
the O
Smaps B-Malware
system O
. O
The O
main O
difference O
is O
that O
Smaps B-Malware
transmits O
data O
as O
plain O
text O
, O
while O
Asacub B-Malware
encrypts O
data O
with O
the O
RC4 O
algorithm O
and O
then O
encodes O
it O
into O
base64 O
format O
. O
Let O
’ O
s O
compare O
examples O
of O
traffic O
from O
Smaps B-Malware
and O
Asacub B-Malware
— O
an O
initializing O
request O
to O
the O
C O
& O
C O
server O
with O
information O
about O
the O
infected O
device O
and O
a O
response O
from O
the O
server O
with O
a O
command O
for O
execution O
: O
Smaps B-Malware
request O
Asacub B-Malware
request O
Decrypted O
data O
from O
Asacub B-Malware
traffic O
: O
{ O
“ O
id O
” O
: O
” O
532bf15a-b784-47e5-92fa-72198a2929f5″ B-Indicator
, O
” O
type O
” O
: O
” O
get O
” O
, O
” O
info O
” O
: O
” O
imei:365548770159066 O
, O
country O
: O
PL O
, O
cell O
: O
Tele2 O
, O
android:4.2.2 O
, O
model O
: O
GT-N5100 O
, O
phonenumber O
: O
+486679225120 O
, O
sim:6337076348906359089f O
, O
app O
: O
null O
, O
ver:5.0.2″ O
} O
Data O
sent O
to O
the O
server O
[ O
{ O
“ O
command O
” O
: O
” O
sent O
& O
& O
& O
” O
, O
” O
params O
” O
: O
{ O
“ O
to O
” O
: O
” O
+79262000900″ O
, O
” O
body O
” O
: O
” O
\u0410\u0412\u0422\u041e\u041f\u041b\u0410\u0422\u0415\u0416 O
1000 O
50″ O
, O
” O
timestamp O
” O
: O
” O
1452272572″ O
} O
} O
, O
{ O
“ O
command O
” O
: O
” O
sent O
& O
& O
& O
” O
, O
” O
params O
” O
: O
{ O
“ O
to O
” O
: O
” O
+79262000900″ O
, O
” O
body O
” O
: O
” O
BALANCE O
” O
, O
” O
timestamp O
” O
: O
” O
1452272573″ O
} O
} O
] O
Instructions O
received O
from O
the O
server O
A O
comparison O
can O
also O
be O
made O
of O
the O
format O
in O
which O
Asacub O
and O
Smaps O
forward O
incoming O
SMS O
( O
encoded O
with O
the O
base64 O
algorithm O
) O
from O
the O
device O
to O
the O
C O
& O
C O
server O
: O
Smaps O
format O
Asacub O
format O
Decrypted O
data O
from O
Asacub O
traffic O
: O
{ O
“ O
data O
” O
: O
” O
2015:10:14_02:41:15″ O
, O
” O
id O
” O
: O
” O
532bf15a-b784-47e5-92fa-72198a2929f5″ B-Indicator
, O
” O
text O
” O
: O
” O
SSB0aG91Z2h0IHdlIGdvdCBwYXN0IHRoaXMhISBJJ20gbm90IGh1bmdyeSBhbmQgbmU= O
” O
, O
” O
number O
” O
: O
” O
1790″ O
, O
” O
type O
” O
: O
” O
load O
” O
} O
Propagation O
The O
banking O
Trojan O
is O
propagated O
via O
phishing O
SMS O
containing O
a O
link O
and O
an O
offer O
to O
view O
a O
photo O
or O
MMS O
. O
The O
link O
points O
to O
a O
web O
page O
with O
a O
similar O
sentence O
and O
a O
button O
for O
downloading O
the O
APK O
file O
of O
the O
Trojan O
to O
the O
device O
. O
The O
Trojan O
download O
window O
Asacub B-Malware
masquerades O
under O
the O
guise O
of O
an O
MMS O
app O
or O
a O
client O
of O
a O
popular O
free O
ads O
service O
. O
We O
came O
across O
the O
names O
Photo O
, O
Message O
, O
Avito O
Offer O
, O
and O
MMS O
Message O
. O
App O
icons O
under O
which O
Asacub B-Malware
masks O
itself O
The O
APK O
files O
of O
the O
Trojan O
are O
downloaded O
from O
sites O
such O
as O
mmsprivate B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
site I-Indicator
, O
photolike B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
fun I-Indicator
, O
you-foto B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
site I-Indicator
, O
and O
mms4you B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
me I-Indicator
under O
names O
in O
the O
format O
: O
photo_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_img.apk I-Indicator
, O
mms_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_img.apk I-Indicator
avito_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
.apk I-Indicator
, O
mms.img_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_photo.apk I-Indicator
, O
mms B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_photo.image.apk I-Indicator
, O
mms B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_photo.img.apk I-Indicator
, O
mms.img.photo_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
.apk I-Indicator
, O
photo_ B-Indicator
[ I-Indicator
number I-Indicator
] I-Indicator
_obmen.img.apk I-Indicator
. O
For O
the O
Trojan O
to O
install O
, O
the O
user O
must O
allow O
installation O
of O
apps O
from O
unknown O
sources O
in O
the O
device O
settings O
. O
Infection O
During O
installation O
, O
depending O
on O
the O
version O
of O
the O
Trojan O
, O
Asacub B-Malware
prompts O
the O
user O
either O
for O
Device O
Administrator O
rights O
or O
for O
permission O
to O
use O
AccessibilityService O
. O
After O
receiving O
the O
rights O
, O
it O
sets O
itself O
as O
the O
default O
SMS O
app O
and O
disappears O
from O
the O
device O
screen O
. O
If O
the O
user O
ignores O
or O
rejects O
the O
request O
, O
the O
window O
reopens O
every O
few O
seconds O
. O
The O
Trojan O
requests O
Device O
Administrator O
rights O
The O
Trojan O
requests O
permission O
to O
use O
AccessibilityService O
After O
installation O
, O
the O
Trojan O
starts O
communicating O
with O
the O
cybercriminals O
’ O
C O
& O
C O
server O
. O
All O
data O
is O
transmitted O
in O
JSON O
format O
( O
after O
decryption O
) O
. O
It O
includes O
information O
about O
the O
smartphone O
model O
, O
the O
OS O
version O
, O
the O
mobile O
operator O
, O
and O
the O
Trojan O
version O
. O
Let O
’ O
s O
take O
an O
in-depth O
look O
at O
Asacub B-Malware
5.0.3 O
, O
the O
most O
widespread O
version O
in O
2018 O
. O
Structure O
of O
data O
sent O
to O
the O
server O
: O
To O
begin O
with O
, O
the O
Trojan O
sends O
information O
about O
the O
device O
to O
the O
server O
: O
In O
response O
, O
the O
server O
sends O
the O
code O
of O
the O
command O
for O
execution O
( O
“ O
command O
” O
) O
, O
its O
parameters O
( O
“ O
params O
” O
) O
, O
and O
the O
time O
delay O
before O
execution O
( O
“ O
waitrun O
” O
in O
milliseconds O
) O
. O
List O
of O
commands O
sewn O
into O
the O
body O
of O
the O
Trojan O
: O
Command O
code O
Parameters O
Actions O
2 O
– O
Sending O
a O
list O
of O
contacts O
from O
the O
address B-System
book I-System
of O
the O
infected O
device O
to O
the O
C O
& O
C O
server O
7 O
“ O
to O
” O
: O
int O
Calling O
the O
specified O
number O
11 O
“ O
to O
” O
: O
int O
, O
“ O
body O
” O
: O
string O
Sending O
an O
SMS O
with O
the O
specified O
text O
to O
the O
specified O
number O
19 O
“ O
text O
” O
: O
string O
, O
“ O
n O
” O
: O
string O
Sending O
SMS O
with O
the O
specified O
text O
to O
numbers O
from O
the O
address B-System
book I-System
of O
the O
infected O
device O
, O
with O
the O
name O
of O
the O
addressee O
from O
the O
address B-System
book I-System
substituted O
into O
the O
message O
text O
40 O
“ O
text O
” O
: O
string O
Shutting O
down O
applications O
with O
specific O
names O
( O
antivirus O
and O
banking O
applications O
) O
The O
set O
of O
possible O
commands O
is O
the O
most O
significant O
difference O
between O
the O
various O
flavors O
of O
Asacub B-Malware
. O
In O
the O
2015-early O
2016 O
versions O
examined O
in O
this O
article O
, O
C O
& O
C O
instructions O
in O
JSON O
format O
contained O
the O
name O
of O
the O
command O
in O
text O
form O
( O
“ O
get_sms O
” O
, O
“ O
block_phone O
” O
) O
. O
In O
later O
versions O
, O
instead O
of O
the O
name O
of O
the O
command O
, O
its O
numerical O
code O
was O
transmitted O
. O
The O
same O
numerical O
code O
corresponded O
to O
one O
command O
in O
different O
versions O
, O
but O
the O
set O
of O
supported O
commands O
varied O
. O
For O
example O
, O
version O
9.0.7 O
( O
2017 O
) O
featured O
the O
following O
set O
of O
commands O
: O
2 O
, O
4 O
, O
8 O
, O
11 O
, O
12 O
, O
15 O
, O
16 O
, O
17 O
, O
18 O
, O
19 O
, O
20 O
. O
After O
receiving O
the O
command O
, O
the O
Trojan O
attempts O
to O
execute O
it O
, O
before O
informing O
C O
& O
C O
of O
the O
execution O
status O
and O
any O
data O
received O
. O
The O
“ O
id O
” O
value O
inside O
the O
“ O
data O
” O
block O
is O
equal O
to O
the O
“ O
timestamp O
” O
value O
of O
the O
relevant O
command O
: O
In O
addition O
, O
the O
Trojan O
sets O
itself O
as O
the O
default O
SMS O
application O
and O
, O
on O
receiving O
a O
new O
SMS O
, O
forwards O
the O
sender O
’ O
s O
number O
and O
the O
message O
text O
in O
base64 O
format O
to O
the O
cybercriminal O
: O
Thus O
, O
Asacub B-Malware
can O
withdraw O
funds O
from O
a O
bank O
card O
linked O
to O
the O
phone O
by O
sending O
SMS O
for O
the O
transfer O
of O
funds O
to O
another O
account O
using O
the O
number O
of O
the O
card O
or O
mobile O
phone O
. O
Moreover O
, O
the O
Trojan O
intercepts O
SMS O
from O
the O
bank O
that O
contain O
one-time O
passwords O
and O
information O
about O
the O
balance O
of O
the O
linked O
bank O
card O
. O
Some O
versions O
of O
the O
Trojan O
can O
autonomously O
retrieve O
confirmation O
codes O
from O
such O
SMS O
and O
send O
them O
to O
the O
required O
number O
. O
What O
’ O
s O
more O
, O
the O
user O
can O
not O
check O
the O
balance O
via O
mobile O
banking O
or O
change O
any O
settings O
there O
, O
because O
after O
receiving O
the O
command O
with O
code O
40 O
, O
the O
Trojan O
prevents O
the O
banking O
app O
from O
running O
on O
the O
phone O
. O
User O
messages O
created O
by O
the O
Trojan O
during O
installation O
typically O
contain O
grammatical O
and O
spelling O
errors O
, O
and O
use O
a O
mixture O
of O
Cyrillic O
and O
Latin O
characters O
. O
The O
Trojan O
also O
employs O
various O
obfuscation O
methods O
: O
from O
the O
simplest O
, O
such O
as O
string O
concatenation O
and O
renaming O
of O
classes O
and O
methods O
, O
to O
implementing O
functions O
in O
native O
code O
and O
embedding O
SO O
libraries O
in O
C/C++ O
in O
the O
APK O
file O
, O
which O
requires O
the O
use O
of O
additional O
tools O
or O
dynamic O
analysis O
for O
deobfuscation O
, O
since O
most O
tools O
for O
static O
analysis O
of O
Android O
apps O
support O
only O
Dalvik O
bytecode O
. O
In O
some O
versions O
of O
Asacub B-Malware
, O
strings O
in O
the O
app O
are O
encrypted O
using O
the O
same O
algorithm O
as O
data O
sent O
to O
C O
& O
C O
, O
but O
with O
different O
keys O
. O
Example O
of O
using O
native O
code O
for O
obfuscation O
Examples O
of O
using O
string O
concatenation O
for O
obfuscation O
Example O
of O
encrypting O
strings O
in O
the O
Trojan O
Asacub B-Malware
distribution O
geography O
Asacub B-Malware
is O
primarily O
aimed O
at O
Russian O
users O
: O
98 O
% O
of O
infections O
( O
225,000 O
) O
occur O
in O
Russia O
, O
since O
the O
cybercriminals O
specifically O
target O
clients O
of O
a O
major O
Russian O
bank O
. O
The O
Trojan O
also O
hit O
users O
from O
Ukraine O
, O
Turkey O
, O
Germany O
, O
Belarus O
, O
Poland O
, O
Armenia O
, O
Kazakhstan O
, O
the O
US O
, O
and O
other O
countries O
. O
Conclusion O
The O
case O
of O
Asacub B-Malware
shows O
that O
mobile O
malware O
can O
function O
for O
several O
years O
with O
minimal O
changes O
to O
the O
distribution O
scheme O
. O
It O
is O
basically O
SMS O
spam O
: O
many O
people O
still O
follow O
suspicious O
links O
, O
install O
software O
from O
third-party O
sources O
, O
and O
give O
permissions O
to O
apps O
without O
a O
second O
thought O
. O
At O
the O
same O
time O
, O
cybercriminals O
are O
reluctant O
to O
change O
the O
method O
of O
communication O
with O
the O
C O
& O
C O
server O
, O
since O
this O
would O
require O
more O
effort O
and O
reap O
less O
benefit O
than O
modifying O
the O
executable O
file O
. O
The O
most O
significant O
change O
in O
this O
particular O
Trojan O
’ O
s O
history O
was O
the O
encryption O
of O
data O
sent O
between O
the O
device O
and O
C O
& O
C O
. O
That O
said O
, O
so O
as O
to O
hinder O
detection O
of O
new O
versions O
, O
the O
Trojan O
’ O
s O
APK O
file O
and O
the O
C O
& O
C O
server O
domains O
are O
changed O
regularly O
, O
and O
the O
Trojan O
download O
links O
are O
often O
one-time-use O
. O
IOCs O
C O
& O
C O
IP O
addresses O
: O
155.133.82.181 B-Indicator
155.133.82.240 B-Indicator
155.133.82.244 B-Indicator
185.234.218.59 B-Indicator
195.22.126.160 B-Indicator
195.22.126.163 B-Indicator
195.22.126.80 B-Indicator
195.22.126.81 B-Indicator
5.45.73.24 B-Indicator
5.45.74.130 B-Indicator
IP I-Indicator
addresses I-Indicator
from O
which O
the O
Trojan O
was O
downloaded O
: O
185.174.173.31 B-Indicator
185.234.218.59 B-Indicator
188.166.156.110 B-Indicator
195.22.126.160 B-Indicator
195.22.126.80 B-Indicator
195.22.126.81 B-Indicator
195.22.126.82 B-Indicator
195.22.126.83 B-Indicator
SHA256 O
: O
158c7688877853ffedb572ccaa8aa9eff47fa379338151f486e46d8983ce1b67 B-Indicator
3aedbe7057130cf359b9b57fa533c2b85bab9612c34697585497734530e7457d B-Indicator
f3ae6762df3f2c56b3fe598a9e3ff96ddf878c553be95bacbd192bd14debd637 B-Indicator
df61a75b7cfa128d4912e5cb648cfc504a8e7b25f6c83ed19194905fef8624c8 B-Indicator
c0cfd462ab21f6798e962515ac0c15a92036edd3e2e63639263bf2fd2a10c184 B-Indicator
d791e0ce494104e2ae0092bb4adc398ce740fef28fa2280840ae7f61d4734514 B-Indicator
38dcec47e2f4471b032a8872ca695044ddf0c61b9e8d37274147158f689d65b9 B-Indicator
27cea60e23b0f62b4b131da29fdda916bc4539c34bb142fb6d3f8bb82380fe4c B-Indicator
31edacd064debdae892ab0bc788091c58a03808997e11b6c46a6a5de493ed25d B-Indicator
87ffec0fe0e7a83e6433694d7f24cfde2f70fc45800aa2acb8e816ceba428951 B-Indicator
eabc604fe6b5943187c12b8635755c303c450f718cc0c8e561df22a27264f101 B-Indicator
Kernel O
Backdoor O
found O
in O
Gadgets O
Powered O
by O
Popular O
Chinese O
ARM B-System
Maker O
May O
12 O
, O
2016 O
Mohit O
Kumar O
How O
to O
Hack O
an O
Android B-System
device O
? O
It O
is O
possibly O
one O
of O
the O
most O
frequently O
asked O
questions O
on O
the O
Internet O
. O
Although O
it O
's O
not O
pretty O
simple O
to O
hack O
Android B-System
devices O
and O
gadgets O
, O
sometimes O
you O
just O
get O
lucky O
to O
find O
a O
backdoor O
access O
. O
Thanks O
to O
Allwinner B-Organization
, O
a O
Chinese O
ARM B-System
system-on-a-chip O
maker O
, O
which O
has O
recently O
been O
caught O
shipping O
a O
version O
of O
Linux B-System
Kernel O
with O
an O
incredibly O
simple O
and O
easy-to-use O
built-in O
backdoor O
. O
Chinese O
fabless O
semiconductor O
company O
Allwinner B-Organization
is O
a O
leading O
supplier O
of O
application O
processors O
that O
are O
used O
in O
many O
low-cost O
Android B-System
tablets O
, O
ARM-based B-Organization
PCs O
, O
set-top O
boxes O
, O
and O
other O
electronic O
devices O
worldwide O
. O
Simple O
Backdoor O
Exploit O
to O
Hack O
Android B-System
Devices O
All O
you O
need O
to O
do O
to O
gain O
root O
access O
of O
an O
affected O
Android B-System
device O
is… O
Send O
the O
text O
" O
rootmydevice O
'' O
to O
any O
undocumented O
debugging O
process O
. O
The O
local O
privileges O
escalation O
backdoor O
code O
for O
debugging O
ARM-powered B-System
Android B-System
devices O
managed O
to O
make O
its O
way O
in O
shipped O
firmware O
after O
firmware O
makers O
wrote O
their O
own O
kernel O
code O
underneath O
a O
custom O
Android B-System
build O
for O
their O
devices O
, O
though O
the O
mainstream O
kernel O
source O
is O
unaffected O
. O
The O
backdoor O
code O
is O
believed O
to O
have O
been O
left O
by O
mistake O
by O
the O
authors O
after O
completing O
the O
debugging O
process O
. O
For O
exploiting O
this O
issue O
, O
any O
process O
running O
with O
any O
UID O
can O
be O
converted O
into O
root O
easily O
by O
simply O
using O
the O
following O
command O
: O
echo O
" O
rootmydevice B-Indicator
'' O
> I-Indicator
/proc/sunxi_debug/sunxi_debug I-Indicator
The O
Linux B-Indicator
3.4-sunxi I-Indicator
kernel O
was O
originally O
designed O
to O
support O
the O
Android B-System
operating O
system O
on O
Allwinner B-Organization
ARM B-System
for O
tablets O
, O
but O
later O
it O
was O
used O
to O
port O
Linux B-System
to O
many O
Allwinner B-Organization
processors O
on O
boards O
like O
Banana B-System
Pi I-System
micro-PCs I-System
, O
Orange B-System
Pi I-System
, O
and O
other O
devices O
. O
At O
the O
forum O
of O
the O
Armbian B-System
operating O
system O
, O
a O
moderator O
who O
goes O
by O
the O
name O
Tkaiser O
noted O
that O
the O
backdoor O
code O
could O
remotely O
be O
exploitable O
" O
if O
combined O
with O
networked O
services O
that O
might O
allow O
access O
to O
/proc B-Indicator
. O
'' O
This O
security O
hole O
is O
currently O
present O
in O
every O
operating O
system O
image O
for O
A83T B-System
, O
H3 B-System
or O
H8 B-System
devices O
that O
rely O
on O
kernel B-System
3.4 I-System
, O
he O
added O
. O
This O
blunder O
made O
by O
the O
company O
has O
been O
frustrating O
to O
many O
developers O
. O
Allwinner B-Organization
has O
also O
been O
less O
transparent O
about O
the O
backdoor O
code O
. O
David O
Manouchehri O
released O
the O
information O
about O
the O
backdoor O
through O
its O
own O
Github B-Organization
account O
( O
Pastebin B-Organization
) O
and O
then O
apparently O
deleted O
it O
. O
Mobile O
Malware O
Evolution O
: O
2013 O
24 O
FEB O
2014 O
The O
mobile O
malware O
sector O
is O
growing O
rapidly O
both O
technologically O
and O
structurally O
. O
It O
is O
safe O
to O
say O
that O
today O
’ O
s O
cybercriminal O
is O
no O
longer O
a O
lone O
hacker O
but O
part O
of O
a O
serious O
business O
operation O
. O
There O
are O
various O
types O
of O
actors O
involved O
in O
the O
mobile O
malware O
industry O
: O
virus O
writers O
, O
testers O
, O
interface O
designers O
of O
both O
the O
malicious O
apps O
and O
the O
web O
pages O
they O
are O
distributed O
from O
, O
owners O
of O
the O
partner O
programs O
that O
spread O
the O
malware O
, O
and O
mobile O
botnet O
owners O
. O
This O
division O
of O
labor O
among O
the O
cybercriminals O
can O
also O
be O
seen O
in O
the O
behavior O
of O
their O
Trojans O
. O
In O
2013 O
, O
there O
was O
evidence O
of O
cooperation O
( O
most O
probably O
on O
a O
commercial O
basis O
) O
between O
different O
groups O
of O
virus O
writers O
. O
For O
example O
, O
the O
botnet O
Trojan-SMS.AndroidOS.Opfake.a B-Malware
, O
in O
addition O
to O
its O
own O
activity O
, O
also O
spread O
Backdoor.AndroidOS.Obad.a B-Malware
by O
sending O
spam O
containing O
a O
link O
to O
the O
malware O
to O
the O
victim O
’ O
s O
list O
of O
contacts O
. O
It O
is O
now O
clear O
that O
a O
distinct O
industry O
has O
developed O
and O
is O
becoming O
more O
focused O
on O
extracting O
profits O
, O
which O
is O
clearly O
evident O
from O
the O
functionality O
of O
the O
malware O
. O
2013 O
in O
figures O
A O
total O
of O
143,211 O
new O
modifications O
of O
malicious O
programs O
targeting O
mobile O
devices O
were O
detected O
in O
all O
of O
2013 O
( O
as O
of O
January O
1 O
, O
2014 O
) O
. O
In O
2013 O
, O
3,905,502 O
installation O
packages O
were O
used O
by O
cybercriminals O
to O
distribute O
mobile O
malware O
. O
Overall O
in O
2012-2013 O
we O
detected O
approximately O
10,000,000 O
unique O
malicious O
installation O
packages O
: O
Different O
installation O
packages O
can O
install O
programs O
with O
the O
same O
functionality O
that O
differ O
only O
in O
terms O
of O
the O
malicious O
app O
interface O
and O
, O
for O
instance O
, O
the O
content O
of O
the O
text O
messages O
it O
spreads O
. O
Android B-System
remains O
a O
prime O
target O
for O
malicious O
attacks O
. O
98.05 O
% O
of O
all O
malware O
detected O
in O
2013 O
targeted O
this O
platform O
, O
confirming O
both O
the O
popularity O
of O
this O
mobile O
OS O
and O
the O
vulnerability O
of O
its O
architecture O
. O
Most O
mobile O
malware O
is O
designed O
to O
steal O
users O
’ O
money O
, O
including O
SMS-Trojans O
, O
and O
lots O
of O
backdoors O
and O
Trojans O
. O
Over O
the O
year O
, O
the O
number O
of O
mobile O
malware O
modifications O
designed O
for O
phishing O
, O
the O
theft O
of O
credit O
card O
information O
and O
money O
increased O
by O
a O
factor O
of O
19.7 O
. O
In O
2013 O
, O
Kaspersky B-Organization
Lab I-Organization
mobile O
products O
prevented O
2,500 O
infections O
by O
banking O
Trojans O
. O
Methods O
and O
techniques O
2013 O
not O
only O
saw O
a O
radical O
increase O
in O
output O
from O
mobile O
virus O
writers O
but O
also O
saw O
them O
actively O
applying O
methods O
and O
technologies O
that O
allowed O
cybercriminals O
to O
use O
their O
malware O
more O
effectively O
. O
There O
were O
several O
distinct O
areas O
where O
mobile O
malware O
underwent O
advances O
. O
Distribution O
Cybercriminals O
made O
use O
of O
some O
exceptionally O
sophisticated O
methods O
to O
infect O
mobile O
devices O
. O
Infecting O
legal O
web O
resources O
help O
spread O
mobile O
malware O
via O
popular O
websites O
. O
More O
and O
more O
smartphone O
and O
tablet O
owners O
use O
their O
devices O
to O
access O
websites O
, O
unaware O
that O
even O
the O
most O
reputable O
resources O
can O
be O
hacked O
. O
According O
to O
our O
data O
, O
0.4 O
% O
of O
the O
websites O
visited O
by O
users O
of O
our O
products O
were O
compromised O
sites O
. O
Distribution O
via O
alternative O
app O
stores O
. O
In O
Asia O
there O
are O
numerous O
companies O
producing O
Android-based B-System
devices O
and O
Android B-System
apps O
, O
and O
many O
of O
them O
offer O
users O
their O
own O
app O
stores O
containing O
programs O
that O
can O
not O
be O
found O
in O
Google B-System
Play I-System
. O
The O
purely O
nominal O
control O
over O
the O
applications O
uploaded O
to O
these O
stores O
means O
attackers O
can O
conceal O
Trojans O
in O
apps O
made O
to O
look O
like O
innocent O
games O
or O
utilities O
. O
Distribution O
via O
botnets O
. O
As O
a O
rule O
, O
bots O
self-proliferate O
by O
sending O
out O
text O
messages O
with O
a O
malicious O
link O
to O
addresses O
in O
the O
victim O
’ O
s O
address O
book O
. O
We O
also O
registered O
one O
episode O
of O
mobile O
malware O
spreading O
via O
a O
third-party O
botnet O
. O
Resistance O
to O
anti-malware O
protection O
The O
ability O
of O
malicious O
software O
to O
operate O
continuously O
on O
the O
victim O
’ O
s O
mobile O
device O
is O
an O
important O
aspect O
of O
its O
development O
. O
The O
longer O
a O
Trojan O
“ O
lives O
” O
on O
a O
smartphone O
, O
the O
more O
money O
it O
will O
make O
for O
the O
owner O
. O
This O
is O
an O
area O
where O
virus O
writers O
are O
actively O
working O
, O
resulting O
in O
a O
large O
number O
of O
technological O
innovations O
. O
Criminals O
are O
increasingly O
using O
obfuscation O
, O
the O
deliberate O
act O
of O
creating O
complex O
code O
to O
make O
it O
difficult O
to O
analyze O
. O
The O
more O
complex O
the O
obfuscation O
, O
the O
longer O
it O
will O
take O
an O
antivirus O
solution O
to O
neutralize O
the O
malicious O
code O
. O
Tellingly O
, O
current O
virus O
writers O
have O
mastered O
commercial O
obfuscators O
. O
This O
implies O
they O
have O
made O
considerable O
investments O
. O
For O
example O
, O
one O
commercial O
obfuscator O
, O
which O
cost O
€350 O
, O
was O
used O
for O
Trojans O
and O
Opfak.bo B-Malware
Obad.a I-Malware
Android O
vulnerabilities O
are O
used O
by O
criminals O
for O
three O
reasons O
: O
to O
bypass O
the O
code O
integrity O
check O
when O
installing O
an O
application O
( O
vulnerability O
Master O
Key O
) O
; O
to O
enhance O
the O
rights O
of O
malicious O
applications O
, O
considerably O
extending O
their O
capabilities O
; O
and O
to O
make O
it O
more O
difficult O
to O
remove O
malware O
. O
For O
example O
, O
Svpeng B-Malware
uses O
a O
previously O
unknown O
vulnerability O
to O
protect O
itself O
from O
being O
removed O
manually O
or O
by O
the O
antivirus O
program O
. O
Cybercriminals O
also O
exploit O
the O
Master B-Vulnerability
Key I-Vulnerability
vulnerability I-Vulnerability
and O
have O
learned O
to O
embed O
unsigned O
executable O
files O
in O
Android B-System
installation O
packages O
. O
Digital O
signature O
verification O
can O
be O
bypassed O
by O
giving O
the O
malicious O
file O
exactly O
the O
same O
name O
as O
a O
legitimate O
file O
and O
placing O
it O
on O
the O
same O
level O
in O
the O
archive O
. O
The O
system O
verifies O
the O
signature O
of O
the O
legitimate O
file O
while O
installing O
the O
malicious O
file O
. O
Unfortunately O
, O
there O
is O
a O
specific O
feature O
of O
Android O
vulnerabilities O
that O
means O
it O
is O
only O
possible O
to O
get O
rid O
of O
them O
by O
receiving O
an O
update O
from O
the O
device O
manufacturers O
. O
However O
, O
many O
users O
are O
in O
no O
hurry O
to O
update O
the O
operating O
systems O
of O
their O
products O
. O
If O
a O
smartphone O
or O
tablet O
was O
released O
more O
than O
a O
year O
ago O
, O
it O
is O
probably O
no O
longer O
supported O
by O
the O
manufacturer O
and O
patching O
of O
vulnerabilities O
is O
no O
longer O
provided O
. O
In O
that O
case O
, O
the O
only O
help O
comes O
from O
an O
antivirus O
solution O
, O
for O
example O
, O
Kaspersky B-System
Internet I-System
Security I-System
for O
Android B-System
. O
Embedding O
malicious O
code O
in O
legitimate O
programs O
helps O
conceal O
infections O
from O
the O
victim O
. O
Of O
course O
, O
this O
does O
not O
mean O
the O
digital O
signature O
of O
the O
software O
developer O
can O
be O
used O
. O
However O
, O
due O
to O
the O
absence O
of O
certification O
centers O
verifying O
the O
digital O
signatures O
of O
Android O
programs O
, O
nothing O
prevents O
criminals O
from O
adding O
their O
own O
signature O
. O
As O
a O
result O
, O
a O
copy O
of O
Angry B-System
Birds I-System
installed O
from O
an O
unofficial O
app O
store O
or O
downloaded O
from O
a O
forum O
could O
easily O
contain O
malicious O
functionality O
. O
Capabilities O
and O
functionality O
In O
2013 O
, O
we O
detected O
several O
technological O
innovations O
developed O
and O
used O
by O
criminals O
in O
their O
malicious O
software O
. O
Below O
are O
descriptions O
of O
some O
of O
the O
most O
interesting O
. O
Control O
of O
malware O
from O
a O
single O
center O
provides O
maximum O
flexibility O
. O
Botnets O
can O
make O
considerably O
more O
money O
than O
autonomous O
Trojans O
. O
It O
comes O
as O
no O
surprise O
then O
that O
many O
SMS-Trojans O
include O
bot O
functionality O
. O
According O
to O
our O
estimates O
, O
about O
60 O
% O
of O
mobile O
malware O
are O
elements O
of O
both O
large O
and O
small O
mobile O
botnets O
. O
By O
using O
Google B-System
Cloud I-System
Messaging I-System
botnet O
owners O
can O
operate O
without O
a O
C O
& O
C O
server O
, O
thus O
eliminating O
the O
threat O
of O
the O
botnet O
being O
detected O
and O
blocked O
by O
law O
enforcement O
authorities O
. O
Google B-System
Cloud I-System
Messaging I-System
is O
designed O
to O
send O
short O
message O
( O
up O
to O
4 O
KB O
) O
to O
mobile O
devices O
via O
Google B-Organization
services O
. O
The O
developer O
simply O
has O
to O
register O
and O
receive O
a O
unique O
ID O
for O
his O
applications O
. O
The O
commands O
received O
via O
GCM B-System
can O
not O
be O
blocked O
immediately O
on O
an O
infected O
device O
. O
We O
have O
detected O
several O
malicious O
programs O
using O
GCM B-System
for O
command O
and O
control O
– O
the O
widespread O
Trojan-SMS.AndroidOS.FakeInst.a B-Malware
, O
Trojan-SMS.AndroidOS.Agent.ao B-Malware
, O
and O
Trojan-SMS.AndroidOS.OpFake.a B-Malware
among O
others O
. O
Google B-Organization
is O
actively O
combating O
this O
use O
of O
the O
service O
, O
responding O
quickly O
to O
reports O
from O
antivirus O
companies O
and O
blocking O
the O
IDs O
of O
cybercriminals O
. O
Attacks O
on O
Windows B-System
XP I-System
allows O
mobile O
malware O
to O
infect O
a O
PC O
after O
connecting O
a O
smartphone O
or O
tablet O
. O
In O
early O
2013 O
we O
detected O
two O
identical O
applications O
on O
Google B-System
Play I-System
that O
were O
allegedly O
designed O
for O
cleaning O
the O
operating O
system O
of O
Android-based B-System
devices O
from O
unnecessary O
processes O
. O
In O
fact O
, O
the O
applications O
are O
designed O
to O
download O
the O
autorun.inf B-Indicator
file I-Indicator
, O
an O
icon O
file O
and O
the O
win32-Trojan B-System
file O
, O
which O
the O
mobile O
malicious O
program O
locates O
in O
the O
root O
directory O
of O
an O
SD B-System
card I-System
. O
On O
connecting O
a O
smartphone O
in O
the O
USB B-System
drive I-System
emulation O
mode O
to O
a O
computer O
running O
Windows B-System
XP I-System
, O
the O
system O
automatically O
starts O
the O
Trojan O
( O
if O
AutoPlay O
on O
the O
external O
media O
is O
not O
disabled O
) O
and O
is O
infected O
. O
The O
Trojan O
allows O
the O
criminals O
to O
remotely O
control O
the O
victim O
’ O
s O
computer O
and O
is O
capable O
of O
recording O
sound O
from O
a O
microphone O
. O
We O
would O
like O
to O
emphasize O
that O
this O
method O
of O
attack O
only O
works O
on O
Windows B-System
XP I-System
and O
Android B-System
versions O
prior O
to O
2.2 O
. O
The O
most O
advanced O
mobile O
malicious O
programs O
today O
are O
Trojans O
targeting O
users O
’ O
bank O
accounts O
– O
the O
most O
attractive O
source O
of O
criminal O
earnings O
. O
Trend O
of O
the O
year O
: O
mobile O
banking O
Trojans O
2013 O
was O
marked O
by O
a O
rapid O
rise O
in O
the O
number O
of O
Android B-System
banking O
Trojans O
. O
The O
cyber O
industry O
of O
mobile O
malware O
is O
becoming O
more O
focused O
on O
making O
profits O
more O
effectively O
, O
i.e. O
, O
mobile O
phishing O
, O
theft O
of O
credit O
card O
information O
, O
money O
transfers O
from O
bank O
cards O
to O
mobile O
phones O
and O
from O
phones O
to O
the O
criminalas O
’ O
e-wallets O
. O
Cybercriminals O
have O
become O
obsessed O
by O
this O
method O
of O
illegal O
earnings O
: O
at O
the O
beginning O
of O
the O
year O
we O
knew O
only O
67 O
banking O
Trojans O
, O
but O
by O
the O
end O
of O
the O
year O
there O
were O
already O
1321 O
unique O
samples O
. O
Kaspersky B-System
Lab I-System
mobile O
products O
prevented O
2,500 O
infections O
by O
banking O
Trojans O
. O
mobile_treats_2013_04s O
The O
number O
of O
mobile O
banking O
Trojans O
in O
our O
collection O
Mobile O
banking O
Trojans O
can O
run O
together O
with O
Win-32 B-System
Trojans O
to O
bypass O
the O
two-factor O
authentication O
– O
mTAN O
theft O
( O
the O
theft O
of O
banking O
verification O
codes O
that O
banks O
send O
their O
customers O
in O
SMS O
messages O
) O
. O
However O
, O
in O
2013 O
, O
autonomous O
mobile O
banking O
Trojans O
developed O
further O
. O
Currently O
, O
such O
Trojans O
attack O
a O
limited O
number O
of O
bank O
customers O
, O
but O
it O
is O
expected O
that O
cybercriminals O
will O
invent O
new O
techniques O
that O
will O
allow O
them O
to O
expand O
the O
number O
and O
the O
geography O
of O
potential O
victims O
. O
mobile_treats_2013_05s O
Infections O
caused O
by O
mobile O
banking O
programs O
Today O
, O
the O
majority O
of O
banking O
Trojan O
attacks O
affect O
users O
in O
Russia O
and O
the O
CIS O
. O
However O
, O
this O
situation O
will O
not O
last O
long O
: O
given O
the O
cybercriminals O
’ O
interest O
in O
user O
bank O
accounts O
, O
the O
activity O
of O
mobile O
banking O
Trojans O
is O
expected O
to O
grow O
in O
other O
countries O
in O
2014 O
. O
As O
mentioned O
above O
, O
banking O
Trojans O
are O
perhaps O
the O
most O
complex O
of O
all O
mobile O
threats O
, O
and O
Svpeng B-Malware
is O
one O
of O
the O
most O
striking O
examples O
. O
Svpeng B-Malware
In O
mid-July O
, O
we O
detected O
Trojan-SMS.AndroidOS.Svpeng.a B-Malware
which O
, O
unlike O
its O
SMS O
Trojan O
counterparts O
, O
is O
focused O
on O
stealing O
money O
from O
the O
victiim O
’ O
s O
bank O
account O
rather O
than O
from O
his O
mobile O
phone O
. O
It O
can O
not O
act O
independently O
and O
operates O
strictly O
in O
accordance O
with O
commands O
received O
from O
the O
C O
& O
C O
server O
. O
This O
malicious O
program O
spreads O
via O
SMS O
spam O
and O
from O
compromised O
legitimate O
sites O
that O
redirect O
mobile O
users O
to O
a O
malicious O
resource O
. O
There O
the O
user O
is O
prompted O
to O
download O
and O
install O
a O
Trojan O
imitating O
an O
Adobe B-System
Flash I-System
Player I-System
update O
. O
Svpeng B-Malware
is O
capable O
of O
doing O
lots O
of O
things O
. O
It O
collects O
information O
about O
the O
smartphone O
( O
IMEI O
, O
country O
, O
service O
provider O
, O
operating O
system O
language O
) O
and O
sends O
it O
to O
the O
host O
via O
the O
HTTP O
POST O
request O
. O
This O
appears O
to O
be O
necessary O
to O
determine O
the O
number O
of O
banks O
the O
victim O
may O
use O
. O
Svpeng B-Malware
is O
only O
currently O
attacking O
clients O
of O
Russian O
banks O
. O
Typically O
, O
however O
, O
cybercriminals O
first O
test-run O
a O
technology O
on O
the O
Russian O
sector O
of O
the O
Internet O
and O
then O
roll O
it O
out O
globally O
, O
attacking O
users O
in O
other O
countries O
. O
It O
steals O
SMS O
messages O
and O
information O
about O
voice O
calls O
. O
It O
helps O
the O
attacker O
find O
out O
which O
banks O
the O
owner O
of O
the O
smartphone O
calls O
– O
the O
Trojan O
receives O
a O
list O
of O
bank O
phone O
numbers O
from O
its O
C O
& O
C O
server O
. O
It O
steals O
money O
from O
the O
victim O
’ O
s O
bank O
account O
. O
In O
Russia O
, O
some O
major O
banks O
offer O
their O
clients O
a O
special O
service O
that O
allows O
them O
to O
transfer O
money O
from O
their O
bank O
card O
to O
their O
mobile O
phone O
account O
. O
Customers O
have O
to O
send O
a O
set O
text O
message O
from O
their O
phone O
to O
a O
specific O
bank O
number O
. O
Svpeng B-Malware
sends O
the O
corresponding O
messages O
to O
the O
SMS O
services O
of O
two O
banks O
. O
Svpeng B-Malware
does O
this O
to O
check O
if O
the O
cards O
from O
these O
banks O
are O
attached O
to O
the O
number O
of O
the O
infected O
phone O
and O
to O
find O
out O
the O
account O
balance O
. O
If O
the O
phone O
is O
attached O
to O
a O
bank O
card O
, O
commands O
are O
sent O
from O
the O
C O
& O
C O
server O
with O
instructions O
to O
transfer O
money O
from O
the O
user O
’ O
s O
bank O
account O
to O
his/her O
mobile O
account O
. O
The O
cybercriminals O
then O
send O
this O
money O
to O
a O
digital O
wallet O
or O
to O
a O
premium O
number O
and O
cash O
it O
in O
. O
It O
steals O
logins O
and O
passwords O
to O
online O
banking O
accounts O
by O
substituting O
he O
window O
displayed O
by O
the O
bank O
application O
. O
Currently O
, O
this O
only O
affects O
Russian O
banks O
, O
but O
the O
technology O
behind O
Svpeng B-Malware
could O
easily O
be O
used O
to O
target O
other O
banking O
applications O
. O
It O
steals O
bank O
card O
information O
( O
the O
number O
, O
the O
expiry O
date O
, O
CVC2/CVV2 O
) O
imitating O
the O
process O
of O
registering O
the O
bank O
card O
with O
Google B-System
Play I-System
. O
If O
the O
user O
has O
launched O
Play B-System
Market I-System
, O
the O
Trojan O
intercepts O
the O
event O
and O
displays O
a O
window O
on O
top O
of O
the O
Google B-System
Play I-System
window O
, O
prompting O
the O
user O
to O
enter O
his/her O
bank O
card O
details O
in O
the O
fake O
window O
. O
The O
data O
entered O
by O
the O
user O
is O
sent O
to O
the O
cybercriminals O
. O
mobile_treats_2013_06s O
It O
extorts O
money O
from O
users O
by O
threatening O
to O
block O
the O
smartphone O
: O
it O
displays O
a O
message O
demanding O
$ O
500 O
to O
unblock O
the O
device O
. O
In O
actual O
fact O
, O
the O
Trojan O
does O
not O
block O
anything O
and O
the O
phone O
can O
be O
used O
without O
any O
problems O
. O
It O
hides O
traces O
of O
its O
activity O
by O
masking O
the O
outgoing O
and O
incoming O
text O
messages O
and O
blocking O
calls O
and O
messages O
from O
numbers O
belonging O
to O
the O
bank O
. O
The O
Trojan O
gets O
the O
list O
of O
bank O
phone O
numbers O
from O
its O
C O
& O
C O
server O
. O
It O
protects O
itself O
from O
deletion O
by O
requesting O
Device O
Administrator O
rights O
during O
the O
installation O
. O
As O
a O
result O
, O
the O
Trojan O
delete O
button O
in O
the O
list O
of O
applications O
becomes O
inactive O
, O
which O
may O
cause O
problems O
for O
inexperienced O
users O
. O
It O
is O
impossible O
to O
deprive O
it O
of O
these O
rights O
without O
the O
use O
of O
specialized O
tools O
( O
such O
as O
Kaspersky B-System
Internet I-System
Security I-System
for O
Android B-System
) O
. O
To O
protect O
itself O
from O
being O
removed O
, O
Svpeng B-Malware
uses O
a O
previously O
unknown O
vulnerability O
in O
Android B-System
. O
It O
uses O
the O
same O
trick O
to O
prevent O
the O
smartphone O
from O
being O
returned O
to O
its O
factory O
settings O
. O
The O
Trojan O
is O
distributed O
in O
Russia O
and O
CIS O
countries O
. O
But O
, O
as O
we O
have O
already O
mentioned O
, O
the O
criminals O
could O
easily O
turn O
their O
attention O
to O
users O
in O
other O
countries O
. O
Perkele B-Malware
and O
Wroba B-Malware
Foreign O
users O
have O
also O
been O
on O
the O
receiving O
end O
of O
several O
malicious O
innovations O
targeting O
bank O
accounts O
. O
The O
Perkele B-Malware
Android O
Trojan O
not O
only O
attacks O
Russian O
users O
but O
also O
clients O
of O
several O
European O
banks O
. O
It O
is O
of O
interest O
primarily O
because O
it O
operates O
in O
conjunction O
with O
various O
banking O
win32-Trojans B-System
. O
Its O
main O
task O
is O
to O
bypass O
the O
two-factor O
authentication O
of O
the O
client O
in O
the O
online O
banking O
system O
. O
Due O
to O
the O
specific O
nature O
of O
its O
activity O
, O
Perkele B-Malware
is O
distributed O
in O
a O
rather O
unusual O
way O
. O
When O
a O
user O
enters O
an O
Internet O
banking O
site O
on O
a O
computer O
infected O
by O
banking O
malware O
( O
ZeuS B-Malware
, O
Citadel B-Malware
) O
, O
a O
request O
about O
the O
smartphone O
number O
and O
type O
of O
operating O
system O
is O
injected O
into O
the O
code O
of O
the O
authentication O
page O
. O
This O
data O
is O
immediately O
sent O
to O
the O
cybercriminals O
and O
the O
computer O
displays O
the O
QR O
code O
containing O
a O
link O
to O
the O
alleged O
certificate O
of O
the O
online O
banking O
system O
. O
After O
scanning O
the O
QR O
code O
and O
installing O
a O
component O
downloaded O
from O
the O
link O
, O
the O
user O
infects O
his O
smartphone O
with O
the O
Trojan O
program O
that O
boasts O
functionality O
that O
is O
of O
great O
interest O
to O
the O
attackers O
. O
Perkele B-Malware
intercepts O
mTANs O
( O
confirmation O
codes O
for O
banking O
operations O
) O
sent O
by O
the O
bank O
via O
text O
message O
. O
By O
using O
the O
login O
and O
password O
stolen O
from O
the O
browser O
, O
the O
Windows O
Trojan O
initiates O
a O
fake O
transaction O
while O
Perkele B-Malware
intercepts O
( O
via O
the O
C O
& O
C O
server O
) O
the O
mTAN O
sent O
by O
the O
bank O
to O
the O
user O
. O
Money O
then O
disappears O
from O
the O
victim O
’ O
s O
account O
and O
is O
cashed O
in O
without O
the O
owner O
’ O
s O
knowledge O
. O
The O
Korean O
malware O
Wroba B-Malware
, O
in O
addition O
to O
the O
traditional O
vector O
of O
infection O
via O
file-sharing O
services O
, O
spreads O
via O
alternative O
app O
stores O
. O
Once O
it O
infects O
a O
device O
, O
Wroba B-Malware
behaves O
very O
aggressively O
. O
It O
searches O
for O
mobile O
banking O
applications O
, O
removes O
them O
and O
uploads O
counterfeit O
versions O
. O
From O
the O
outside O
, O
they O
are O
indistinguishable O
from O
the O
legitimate O
applications O
. O
However O
, O
they O
possess O
no O
banking O
functions O
, O
and O
merely O
steal O
the O
logins O
and O
passwords O
entered O
by O
users O
. O
ViperRAT B-Malware
: O
The O
Mobile O
APT O
Targeting O
The O
Israeli B-Organization
Defense I-Organization
Force I-Organization
That O
Should O
Be O
On O
Your O
Radar O
February O
16 O
, O
2017 O
ViperRAT B-Malware
is O
an O
active O
, O
advanced O
persistent O
threat O
( O
APT O
) O
that O
sophisticated O
threat O
actors O
are O
actively O
using O
to O
target O
and O
spy O
on O
the O
Israeli B-Organization
Defense I-Organization
Force.The I-Organization
threat O
actors O
behind O
the O
ViperRAT B-Malware
surveillanceware O
collect O
a O
significant O
amount O
of O
sensitive O
information O
off O
of O
the O
device O
, O
and O
seem O
most O
interested O
in O
exfiltrating O
images O
and O
audio O
content O
. O
The O
attackers O
are O
also O
hijacking O
the O
device O
camera O
to O
take O
pictures O
. O
Using O
data O
collected O
from O
the O
Lookout B-Organization
global O
sensor O
network O
, O
the O
Lookout O
research O
team O
was O
able O
to O
gain O
unique O
visibility O
into O
the O
ViperRAT B-Malware
malware O
, O
including O
11 O
new O
, O
unreported O
applications O
. O
We O
also O
discovered O
and O
analyzed O
live O
, O
misconfigured O
malicious O
command O
and O
control O
servers O
( O
C2 O
) O
, O
from O
which O
we O
were O
able O
to O
identify O
how O
the O
attacker O
gets O
new O
, O
infected O
apps O
to O
secretly O
install O
and O
the O
types O
of O
activities O
they O
are O
monitoring O
. O
In O
addition O
, O
we O
uncovered O
the O
IMEIs O
of O
the O
targeted O
individuals O
( O
IMEIs O
will O
not O
be O
shared O
publicly O
for O
the O
privacy O
and O
safety O
of O
the O
victims O
) O
as O
well O
as O
the O
types O
of O
exfiltrated O
content O
. O
In O
aggregate O
, O
the O
type O
of O
information O
stolen O
could O
let O
an O
attacker O
know O
where O
a O
person O
is O
, O
with O
whom O
they O
are O
associated O
( O
including O
contacts O
’ O
profile O
photos O
) O
, O
the O
messages O
they O
are O
sending O
, O
the O
websites O
they O
visit O
and O
search O
history O
, O
screenshots O
that O
reveal O
data O
from O
other O
apps O
on O
the O
device O
, O
the O
conversations O
they O
have O
in O
the O
presence O
of O
the O
device O
, O
and O
a O
myriad O
of O
images O
including O
anything O
at O
which O
device O
’ O
s O
camera O
is O
pointed O
. O
Lookout B-Organization
has O
determined O
ViperRAT B-Malware
is O
a O
very O
sophisticated O
threat O
that O
adds O
to O
the O
mounting O
evidence O
that O
targeted O
mobile O
attacks O
against O
governments O
and O
business O
is O
a O
real O
problem O
. O
Lookout B-Organization
researchers O
have O
been O
tracking O
this O
threat O
for O
the O
last O
month O
. O
Given O
that O
this O
is O
an O
active O
threat O
, O
we O
’ O
ve O
been O
working O
behind-the-scenes O
with O
our O
customers O
to O
ensure O
both O
personal O
and O
enterprise O
customers O
are O
protected O
from O
this O
threat O
and O
only O
decided O
to O
come O
forward O
with O
this O
information O
after O
the O
research O
team O
at O
Kaspersky B-Organization
released O
a O
report O
earlier O
today O
. O
Additionally O
, O
we O
have O
determined O
that O
though O
original O
reports O
of O
this O
story O
attribute O
this O
surveillanceware O
tool O
to O
Hamas B-Organization
, O
this O
may O
not O
be O
the O
case O
, O
as O
we O
demonstrate O
below O
. O
The O
increasing O
sophistication O
of O
surveillanceware O
The O
structure O
of O
the O
surveillanceware O
indicates O
it O
is O
very O
sophisticated O
. O
Analysis O
indicates O
there O
are O
currently O
two O
distinct O
variants O
of O
ViperRAT B-Malware
. O
The O
first O
variant O
is O
a O
“ O
first O
stage O
application O
, O
” O
that O
performs O
basic O
profiling O
of O
a O
device O
, O
and O
under O
certain O
conditions O
attempts O
to O
download O
and O
install O
a O
much O
more O
comprehensive O
surveillanceware O
component O
, O
which O
is O
the O
second O
variant O
. O
The O
first O
variant O
involves O
social O
engineering O
the O
target O
into O
downloading O
a O
trojanized O
app O
. O
Previous O
reports O
alleged O
this O
surveillanceware O
tool O
was O
deployed O
using O
‘ O
honey O
traps O
’ O
where O
the O
actor O
behind O
it O
would O
reach O
out O
to O
targets O
via O
fake O
social O
media O
profiles O
of O
young O
women O
. O
After O
building O
an O
initial O
rapport O
with O
targets O
, O
the O
actors O
behind O
these O
social O
media O
accounts O
would O
instruct O
victims O
to O
install O
an O
additional O
app O
for O
easier O
communication O
. O
Specifically O
, O
Lookout B-Organization
determined O
these O
were O
trojanized O
versions O
of O
the O
apps O
SR B-System
Chat I-System
and O
YeeCall B-System
Pro I-System
. O
We O
also O
uncovered O
ViperRAT B-Malware
in O
a O
billiards O
game O
, O
an O
Israeli O
Love O
Songs O
player O
, O
and O
a O
Move O
To O
iOS B-System
app O
. O
The O
second O
stage O
The O
second O
stage O
apps O
contain O
the O
surveillanceware O
capabilities O
. O
Lookout B-Organization
uncovered O
nine O
secondary O
payload O
applications O
: O
* O
These O
apps O
have O
not O
been O
previously O
reported O
and O
were O
discovered O
using O
data O
from O
the O
Lookout B-Organization
global O
sensor O
network O
, O
which O
collects O
app O
and O
device O
information O
from O
over O
100 O
million O
sensors O
to O
provide O
researchers O
and O
customers O
with O
a O
holistic O
look O
at O
the O
mobile O
threat O
ecosystem O
today O
. O
Naming O
additional O
payload O
applications O
as O
system O
updates O
is O
a O
clever O
technique O
used O
by O
malware O
authors O
to O
trick O
victims O
into O
believing O
a O
threat O
isn O
’ O
t O
present O
on O
their O
device O
. O
ViperRAT B-Malware
takes O
this O
one O
step O
further O
by O
using O
its O
dropper O
app O
to O
identify O
an O
appropriate O
second O
stage O
‘ O
update O
’ O
that O
may O
go O
unnoticed O
. O
For O
example O
, O
if O
a O
victim O
has O
Viber B-System
on O
their O
device O
, O
it O
will O
choose O
to O
retrieve O
the O
Viber B-System
Update I-System
second O
stage O
. O
If O
he O
doesn O
’ O
t O
have O
Viber O
, O
the O
generically-named O
System O
Updates O
app O
gets O
downloaded O
and O
installed O
instead O
. O
What O
was O
taken O
The O
actors O
behind O
ViperRAT B-Malware
seem O
to O
be O
particularly O
interested O
in O
image O
data O
. O
We O
were O
able O
to O
identify O
that O
8,929 O
files O
had O
been O
exfiltrated O
from O
compromised O
devices O
and O
that O
the O
overwhelming O
majority O
of O
these O
, O
97 O
percent O
, O
were O
highly O
likely O
encrypted O
images O
taken O
using O
the O
device O
camera O
. O
We O
also O
observed O
automatically O
generated O
files O
on O
the O
C2 O
, O
indicating O
the O
actor O
behind O
this O
campaign O
also O
issues O
commands O
to O
search O
for O
and O
exfiltrate O
PDF O
and O
Office O
documents O
. O
This O
should O
be O
highly O
alarming O
to O
any O
government O
agency O
or O
enterprise O
. O
We O
observed O
legitimate O
exfiltrated O
files O
of O
the O
following O
types O
of O
data O
: O
Contact O
information O
Compressed O
recorded O
audio O
in O
the O
Adaptive O
Multi-Rate O
( O
amr O
) O
file O
format O
Images O
captured O
from O
the O
device O
camera O
Images O
stored O
on O
both O
internal O
device O
and O
SDCard O
storage O
that O
are O
listed O
in O
the O
MediaStore O
Device O
geolocation O
information O
SMS O
content O
Chrome O
browser O
search O
history O
and O
bookmarks O
Call O
log O
information O
Cell O
tower O
information O
Device O
network O
metadata O
; O
such O
as O
phone O
number O
, O
device O
software O
version O
, O
network O
country O
, O
network O
operator O
, O
SIM O
country O
, O
SIM O
operator O
, O
SIM O
serial O
, O
IMSI O
, O
voice O
mail O
number O
, O
phone O
type O
, O
network O
type O
, O
data O
state O
, O
data O
activity O
, O
call O
state O
, O
SIM O
state O
, O
whether O
device O
is O
roaming O
, O
and O
if O
SMS O
is O
supported O
. O
Standard O
browser O
search O
history O
Standard O
browser O
bookmarks O
Device O
handset O
metadata O
; O
such O
as O
brand O
, O
display O
, O
hardware O
, O
manufacturer O
, O
product O
, O
serial O
, O
radio O
version O
, O
and O
SDK O
. O
Command O
and O
control O
API O
calls O
ViperRAT B-Malware
samples O
are O
capable O
of O
communicating O
to O
C2 O
servers O
through O
an O
exposed O
API O
as O
well O
as O
websockets O
. O
Below O
is O
a O
collection O
of O
API O
methods O
and O
a O
brief O
description O
around O
their O
purpose O
. O
On O
attribution O
Media O
reporting O
on O
ViperRAT B-Malware
thus O
far O
attributes O
this O
surveillanceware O
tool O
to O
Hamas B-Organization
. O
Israeli O
media O
published O
the O
first O
reports O
about O
the O
social O
networking O
and O
social O
engineering O
aspects O
of O
this O
campaign O
. O
However O
it O
’ O
s O
unclear O
whether O
organizations O
that O
later O
reported O
on O
ViperRAT B-Malware
performed O
their O
own O
independent O
research O
or O
simply O
based O
their O
content O
on O
the O
original O
Israeli O
report O
. O
Hamas B-Organization
is O
not O
widely O
known O
for O
having O
a O
sophisticated O
mobile O
capability O
, O
which O
makes O
it O
unlikely O
they O
are O
directly O
responsible O
for O
ViperRAT B-Malware
. O
ViperRAT B-Malware
has O
been O
operational O
for O
quite O
some O
time O
, O
with O
what O
appears O
to O
be O
a O
test O
application O
that O
surfaced O
in O
late O
2015 O
. O
Many O
of O
the O
default O
strings O
in O
this O
application O
are O
in O
Arabic O
, O
including O
the O
name O
. O
It O
is O
unclear O
whether O
this O
means O
early O
samples O
were O
targeting O
Arabic O
speakers O
or O
if O
the O
developers O
behind O
it O
are O
fluent O
in O
Arabic O
. O
This O
leads O
us O
to O
believe O
this O
is O
another O
actor O
. O
What O
this O
means O
for O
you O
All O
Lookout B-Organization
customers O
are O
protected O
from O
this O
threat O
. O
However O
, O
the O
existence O
of O
threats O
like O
ViperRAT B-Malware
and O
Pegasus B-Malware
, O
the O
most O
sophisticated O
piece O
of O
mobile O
surveillanceware O
we O
’ O
ve O
seen O
to O
date O
, O
are O
evidence O
that O
attackers O
are O
targeting O
mobile O
devices O
. O
Mobile O
devices O
are O
at O
the O
frontier O
of O
cyber O
espionage O
, O
and O
other O
criminal O
motives O
. O
Enterprise O
and O
government O
employees O
all O
use O
these O
devices O
in O
their O
day-to-day O
work O
, O
which O
means O
IT O
and O
security O
leaders O
within O
these O
organizations O
must O
prioritize O
mobile O
in O
their O
security O
strategies O
. O
Check B-Organization
Point I-Organization
researchers O
discovered O
another O
widespread O
malware O
campaign O
on O
Google B-System
Play I-System
, O
Google B-Organization
’ O
s O
official O
app O
store O
. O
The O
malware O
, O
dubbed O
“ O
Judy B-Malware
” O
, O
is O
an O
auto-clicking O
adware O
which O
was O
found O
on O
41 O
apps O
developed O
by O
a O
Korean O
company O
. O
The O
malware O
uses O
infected O
devices O
to O
generate O
large O
amounts O
of O
fraudulent O
clicks O
on O
advertisements O
, O
generating O
revenues O
for O
the O
perpetrators O
behind O
it O
. O
The O
malicious O
apps O
reached O
an O
astonishing O
spread O
between O
4.5 O
million O
and O
18.5 O
million O
downloads O
. O
Some O
of O
the O
apps O
we O
discovered O
resided O
on O
Google B-System
Play I-System
for O
several O
years O
, O
but O
all O
were O
recently O
updated O
. O
It O
is O
unclear O
how O
long O
the O
malicious O
code O
existed O
inside O
the O
apps O
, O
hence O
the O
actual O
spread O
of O
the O
malware O
remains O
unknown O
. O
We O
also O
found O
several O
apps O
containing O
the O
malware O
, O
which O
were O
developed O
by O
other O
developers O
on O
Google B-System
Play I-System
. O
The O
connection O
between O
the O
two O
campaigns O
remains O
unclear O
, O
and O
it O
is O
possible O
that O
one O
borrowed O
code O
from O
the O
other O
, O
knowingly O
or O
unknowingly O
. O
The O
oldest O
app O
of O
the O
second O
campaign O
was O
last O
updated O
in O
April O
2016 O
, O
meaning O
that O
the O
malicious O
code O
hid O
for O
a O
long O
time O
on O
the O
Play B-System
store I-System
undetected O
. O
These O
apps O
also O
had O
a O
large O
amount O
of O
downloads O
between O
4 O
and O
18 O
million O
, O
meaning O
the O
total O
spread O
of O
the O
malware O
may O
have O
reached O
between O
8.5 O
and O
36.5 O
million O
users O
. O
Similar O
to O
previous O
malware O
which O
infiltrated O
Google B-System
Play I-System
, O
such O
as O
FalseGuide B-Malware
and O
Skinner B-Malware
, O
Judy O
relies O
on O
the O
communication O
with O
its O
Command O
and O
Control O
server O
( O
C O
& O
C O
) O
for O
its O
operation O
. O
After O
Check B-Organization
Point I-Organization
notified O
Google B-Organization
about O
this O
threat O
, O
the O
apps O
were O
swiftly O
removed O
from O
the O
Play B-System
store I-System
. O
How O
Judy B-Malware
operates O
: O
To O
bypass O
Bouncer B-System
, O
Google B-System
Play I-System
’ O
s O
protection O
, O
the O
hackers O
create O
a O
seemingly O
benign O
bridgehead O
app O
, O
meant O
to O
establish O
connection O
to O
the O
victim O
’ O
s O
device O
, O
and O
insert O
it O
into O
the O
app O
store O
. O
Once O
a O
user O
downloads O
a O
malicious O
app O
, O
it O
silently O
registers O
receivers O
which O
establish O
a O
connection O
with O
the O
C O
& O
C O
server O
. O
The O
server O
replies O
with O
the O
actual O
malicious O
payload O
, O
which O
includes O
JavaScript O
code O
, O
a O
user-agent O
string O
and O
URLs O
controlled O
by O
the O
malware O
author O
. O
The O
malware O
opens O
the O
URLs O
using O
the O
user O
agent O
that O
imitates O
a O
PC O
browser O
in O
a O
hidden O
webpage O
and O
receives O
a O
redirection O
to O
another O
website O
. O
Once O
the O
targeted O
website O
is O
launched O
, O
the O
malware O
uses O
the O
JavaScript O
code O
to O
locate O
and O
click O
on O
banners O
from O
the O
Google B-System
ads I-System
infrastructure O
. O
Upon O
clicking O
the O
ads O
, O
the O
malware O
author O
receives O
payment O
from O
the O
website O
developer O
, O
which O
pays O
for O
the O
illegitimate O
clicks O
and O
traffic O
. O
The O
JavaScript O
code O
locates O
the O
targeted O
ads O
by O
searching O
for O
iframes O
which O
contain O
ads O
from O
Google B-System
ads I-System
infrastructure O
, O
as O
shown O
in O
the O
image O
below O
: O
The O
fraudulent O
clicks O
generate O
a O
large O
revenue O
for O
the O
perpetrators O
, O
especially O
since O
the O
malware O
reached O
a O
presumably O
wide O
spread O
. O
Who O
is O
behind O
Judy B-Malware
? O
The O
malicious O
apps O
are O
all O
developed O
by O
a O
Korean O
company O
named O
Kiniwini B-Organization
, O
registered O
on O
Google B-System
Play I-System
as O
ENISTUDIO B-Organization
corp I-Organization
. O
The O
company O
develops O
mobile O
apps O
for O
both O
Android B-System
and O
iOS B-System
platforms O
. O
It O
is O
quite O
unusual O
to O
find O
an O
actual O
organization O
behind O
mobile O
malware O
, O
as O
most O
of O
them O
are O
developed O
by O
purely O
malicious O
actors O
. O
It O
is O
important O
to O
note O
that O
the O
activity O
conducted O
by O
the O
malware O
is O
not O
borderline O
advertising O
, O
but O
definitely O
an O
illegitimate O
use O
of O
the O
users O
’ O
mobile O
devices O
for O
generating O
fraudulent O
clicks O
, O
benefiting O
the O
attackers O
. O
In O
addition O
to O
the O
clicking O
activity O
, O
Judy B-Malware
displays O
a O
large O
amount O
of O
advertisements O
, O
which O
in O
some O
cases O
leave O
users O
with O
no O
option O
but O
clicking O
on O
the O
ad O
itself O
. O
Although O
most O
apps O
have O
positive O
ratings O
, O
some O
of O
the O
users O
have O
noticed O
and O
reported O
Judy B-Malware
’ O
s O
suspicious O
activities O
, O
as O
seen O
in O
the O
images O
below O
: O
As O
seen O
in O
previous O
malware O
, O
such O
as O
DressCode B-Malware
, O
a O
high O
reputation O
does O
not O
necessarily O
indicate O
that O
the O
app O
is O
safe O
for O
use O
. O
Hackers O
can O
hide O
their O
apps O
’ O
real O
intentions O
or O
even O
manipulate O
users O
into O
leaving O
positive O
ratings O
, O
in O
some O
cases O
unknowingly O
. O
Users O
can O
not O
rely O
on O
the O
official O
app O
stores O
for O
their O
safety O
, O
and O
should O
implement O
advanced O
security O
protections O
capable O
of O
detecting O
and O
blocking O
zero-day O
mobile O
malware O
. O
PHA O
Family O
Highlights O
: O
Bread B-Malware
( O
and O
Friends O
) O
January O
9 O
, O
2020 O
In O
this O
edition O
of O
our O
PHA O
Family O
Highlights O
series O
we O
introduce O
Bread B-Malware
, O
a O
large-scale O
billing O
fraud O
family O
. O
We O
first O
started O
tracking O
Bread B-Malware
( O
also O
known O
as O
Joker B-Malware
) O
in O
early O
2017 O
, O
identifying O
apps O
designed O
solely O
for O
SMS O
fraud O
. O
As O
the O
Play B-System
Store I-System
has O
introduced O
new O
policies O
and O
Google B-System
Play I-System
Protect I-System
has O
scaled O
defenses O
, O
Bread B-Malware
apps O
were O
forced O
to O
continually O
iterate O
to O
search O
for O
gaps O
. O
They O
have O
at O
some O
point O
used O
just O
about O
every O
cloaking O
and O
obfuscation O
technique O
under O
the O
sun O
in O
an O
attempt O
to O
go O
undetected O
. O
Many O
of O
these O
samples O
appear O
to O
be O
designed O
specifically O
to O
attempt O
to O
slip O
into O
the O
Play B-System
Store I-System
undetected O
and O
are O
not O
seen O
elsewhere O
. O
In O
this O
post O
, O
we O
show O
how O
Google B-System
Play I-System
Protect I-System
has O
defended O
against O
a O
well O
organized O
, O
persistent O
attacker O
and O
share O
examples O
of O
their O
techniques O
. O
TL O
; O
DR O
Google B-System
Play I-System
Protect I-System
detected O
and O
removed O
1.7k O
unique O
Bread B-Malware
apps O
from O
the O
Play B-System
Store I-System
before O
ever O
being O
downloaded O
by O
users O
Bread B-Malware
apps O
originally O
performed O
SMS O
fraud O
, O
but O
have O
largely O
abandoned O
this O
for O
WAP O
billing O
following O
the O
introduction O
of O
new O
Play B-System
policies O
restricting O
use O
of O
the O
SEND_SMS O
permission O
and O
increased O
coverage O
by O
Google B-System
Play I-System
Protect I-System
More O
information O
on O
stats O
and O
relative O
impact O
is O
available O
in O
the O
Android B-System
Security O
2018 O
Year O
in O
Review O
report O
BILLING O
FRAUD O
Bread B-Malware
apps O
typically O
fall O
into O
two O
categories O
: O
SMS O
fraud O
( O
older O
versions O
) O
and O
toll O
fraud O
( O
newer O
versions O
) O
. O
Both O
of O
these O
types O
of O
fraud O
take O
advantage O
of O
mobile O
billing O
techniques O
involving O
the O
user O
’ O
s O
carrier O
. O
SMS O
Billing O
Carriers O
may O
partner O
with O
vendors O
to O
allow O
users O
to O
pay O
for O
services O
by O
SMS O
. O
The O
user O
simply O
needs O
to O
text O
a O
prescribed O
keyword O
to O
a O
prescribed O
number O
( O
shortcode O
) O
. O
A O
charge O
is O
then O
added O
to O
the O
user O
’ O
s O
bill O
with O
their O
mobile O
service O
provider O
. O
Toll O
Billing O
Carriers O
may O
also O
provide O
payment O
endpoints O
over O
a O
web O
page O
. O
The O
user O
visits O
the O
URL O
to O
complete O
the O
payment O
and O
enters O
their O
phone O
number O
. O
Verification O
that O
the O
request O
is O
coming O
from O
the O
user O
’ O
s O
device O
is O
completed O
using O
two O
possible O
methods O
: O
The O
user O
connects O
to O
the O
site O
over O
mobile O
data O
, O
not O
WiFi O
( O
so O
the O
service O
provider O
directly O
handles O
the O
connection O
and O
can O
validate O
the O
phone O
number O
) O
; O
or O
The O
user O
must O
retrieve O
a O
code O
sent O
to O
them O
via O
SMS O
and O
enter O
it O
into O
the O
web O
page O
( O
thereby O
proving O
access O
to O
the O
provided O
phone O
number O
) O
. O
Fraud O
Both O
of O
the O
billing O
methods O
detailed O
above O
provide O
device O
verification O
, O
but O
not O
user O
verification O
. O
The O
carrier O
can O
determine O
that O
the O
request O
originates O
from O
the O
user O
’ O
s O
device O
, O
but O
does O
not O
require O
any O
interaction O
from O
the O
user O
that O
can O
not O
be O
automated O
. O
Malware O
authors O
use O
injected O
clicks O
, O
custom O
HTML O
parsers O
and O
SMS O
receivers O
to O
automate O
the O
billing O
process O
without O
requiring O
any O
interaction O
from O
the O
user O
. O
STRING O
& O
DATA O
OBFUSCATION O
Bread O
apps O
have O
used O
many O
innovative O
and O
classic O
techniques O
to O
hide O
strings O
from O
analysis O
engines O
. O
Here O
are O
some O
highlights O
. O
Standard O
Encryption O
Frequently O
, O
Bread O
apps O
take O
advantage O
of O
standard O
crypto O
libraries O
in O
` O
java.util.crypto B-Indicator
` O
. O
We O
have O
discovered O
apps O
using O
AES O
, O
Blowfish O
, O
and O
DES O
as O
well O
as O
combinations O
of O
these O
to O
encrypt O
their O
strings O
. O
Custom O
Encryption O
Other O
variants O
have O
used O
custom-implemented O
encryption O
algorithms O
. O
Some O
common O
techniques O
include O
: O
basic O
XOR O
encryption O
, O
nested O
XOR O
and O
custom O
key-derivation O
methods O
. O
Some O
variants O
have O
gone O
so O
far O
as O
to O
use O
a O
different O
key O
for O
the O
strings O
of O
each O
class O
. O
Split O
Strings O
Encrypted O
strings O
can O
be O
a O
signal O
that O
the O
code O
is O
trying O
to O
hide O
something O
. O
Bread B-Malware
has O
used O
a O
few O
tricks O
to O
keep O
strings O
in O
plaintext O
while O
preventing O
basic O
string O
matching O
. O
Going O
one O
step O
further O
, O
these O
substrings O
are O
sometimes O
scattered O
throughout O
the O
code O
, O
retrieved O
from O
static O
variables O
and O
method O
calls O
. O
Various O
versions O
may O
also O
change O
the O
index O
of O
the O
split O
( O
e.g O
. O
“ O
.clic O
” O
and O
“ O
k O
( O
) O
; O
” O
) O
. O
Delimiters O
Another O
technique O
to O
obfuscate O
unencrypted O
strings O
uses O
repeated O
delimiters O
. O
A O
short O
, O
constant O
string O
of O
characters O
is O
inserted O
at O
strategic O
points O
to O
break O
up O
keywords O
: O
At O
runtime O
, O
the O
delimiter O
is O
removed O
before O
using O
the O
string O
: O
API O
OBFUSCATION O
SMS O
and O
toll O
fraud O
generally O
requires O
a O
few O
basic O
behaviors O
( O
for O
example O
, O
disabling O
WiFi O
or O
accessing O
SMS O
) O
, O
which O
are O
accessible O
by O
a O
handful O
of O
APIs O
. O
Given O
that O
there O
are O
a O
limited O
number O
of O
behaviors O
required O
to O
identify O
billing O
fraud O
, O
Bread B-Malware
apps O
have O
had O
to O
try O
a O
wide O
variety O
of O
techniques O
to O
mask O
usage O
of O
these O
APIs O
. O
Reflection O
Most O
methods O
for O
hiding O
API O
usage O
tend O
to O
use O
Java O
reflection O
in O
some O
way O
. O
In O
some O
samples O
, O
Bread B-Malware
has O
simply O
directly O
called O
the O
Reflect O
API O
on O
strings O
decrypted O
at O
runtime O
. O
JNI O
Bread B-Malware
has O
also O
tested O
our O
ability O
to O
analyze O
native O
code O
. O
In O
one O
sample O
, O
no O
SMS-related O
code O
appears O
in O
the O
DEX O
file O
, O
but O
there O
is O
a O
native O
method O
registered O
. O
Two O
strings O
are O
passed O
into O
the O
call O
, O
the O
shortcode O
and O
keyword O
used O
for O
SMS O
billing O
( O
getter O
methods O
renamed O
here O
for O
clarity O
) O
. O
In O
the O
native O
library O
, O
it O
stores O
the O
strings O
to O
access O
the O
SMS O
API O
. O
The O
nativesend O
method O
uses O
the O
Java O
Native O
Interface O
( O
JNI O
) O
to O
fetch O
and O
call O
the O
Android B-System
SMS O
API O
. O
The O
following O
is O
a O
screenshot O
from O
IDA O
with O
comments O
showing O
the O
strings O
and O
JNI O
functions O
. O
WebView O
JavaScript O
Interface O
Continuing O
on O
the O
theme O
of O
cross-language O
bridges O
, O
Bread B-Malware
has O
also O
tried O
out O
some O
obfuscation O
methods O
utilizing O
JavaScript O
in O
WebViews O
. O
The O
following O
method O
is O
declared O
in O
the O
DEX O
. O
Without O
context O
, O
this O
method O
does O
not O
reveal O
much O
about O
its O
intended O
behavior O
, O
and O
there O
are O
no O
calls O
made O
to O
it O
anywhere O
in O
the O
DEX O
. O
However O
, O
the O
app O
does O
create O
a O
WebView O
and O
registers O
a O
JavaScript O
interface O
to O
this O
class O
. O
This O
gives O
JavaScript O
run O
in O
the O
WebView O
access O
to O
this O
method O
. O
The O
app O
loads O
a O
URL O
pointing O
to O
a O
Bread-controlled O
server O
. O
The O
response O
contains O
some O
basic O
HTML O
and O
JavaScript O
. O
In O
green O
, O
we O
can O
see O
the O
references O
to O
the O
SMS O
API O
. O
In O
red O
, O
we O
see O
those O
values O
being O
passed O
into O
the O
suspicious O
Java O
method O
through O
the O
registered O
interface O
. O
Now O
, O
using O
these O
strings O
method1 O
can O
use O
reflection O
to O
call O
sendTextMessage O
and O
process O
the O
payment O
. O
PACKING O
In O
addition O
to O
implementing O
custom O
obfuscation O
techniques O
, O
apps O
have O
used O
several O
commercially O
available O
packers O
including O
: O
Qihoo360 B-System
, O
AliProtect B-System
and O
SecShell B-System
. O
More O
recently O
, O
we O
have O
seen O
Bread-related B-Malware
apps O
trying O
to O
hide O
malicious O
code O
in O
a O
native O
library O
shipped O
with O
the O
APK O
. O
Earlier O
this O
year O
, O
we O
discovered O
apps O
hiding O
a O
JAR O
in O
the O
data O
section O
of O
an O
ELF O
file O
which O
it O
then O
dynamically O
loads O
using O
DexClassLoader O
. O
The O
figure O
below O
shows O
a O
fragment O
of O
encrypted O
JAR O
stored O
in O
.rodata O
section O
of O
a O
shared O
object O
shipped O
with O
the O
APK O
as O
well O
as O
the O
XOR O
key O
used O
for O
decryption O
. O
After O
we O
blocked O
those O
samples O
, O
they O
moved O
a O
significant O
portion O
of O
malicious O
functionality O
into O
the O
native O
library O
, O
which O
resulted O
in O
a O
rather O
peculiar O
back O
and O
forth O
between O
Dalvik O
and O
native O
code O
: O
COMMAND O
& O
CONTROL O
Dynamic O
Shortcodes O
& O
Content O
Early O
versions O
of O
Bread O
utilized O
a O
basic O
command O
and O
control O
infrastructure O
to O
dynamically O
deliver O
content O
and O
retrieve O
billing O
details O
. O
In O
the O
example O
server O
response O
below O
, O
the O
green O
fields O
show O
text O
to O
be O
shown O
to O
the O
user O
. O
The O
red O
fields O
are O
used O
as O
the O
shortcode O
and O
keyword O
for O
SMS O
billing O
. O
State O
Machines O
Since O
various O
carriers O
implement O
the O
billing O
process O
differently O
, O
Bread B-Malware
has O
developed O
several O
variants O
containing O
generalized O
state O
machines O
implementing O
all O
possible O
steps O
. O
At O
runtime O
, O
the O
apps O
can O
check O
which O
carrier O
the O
device O
is O
connected O
to O
and O
fetch O
a O
configuration O
object O
from O
the O
command O
and O
control O
server O
. O
The O
configuration O
contains O
a O
list O
of O
steps O
to O
execute O
with O
URLs O
and O
JavaScript O
. O
The O
steps O
implemented O
include O
: O
Load O
a O
URL O
in O
a O
WebView O
Run O
JavaScript O
in O
WebView O
Toggle O
WiFi O
state O
Toggle O
mobile O
data O
state O
Read/modify O
SMS O
inbox O
Solve O
captchas O
Captchas O
One O
of O
the O
more O
interesting O
states O
implements O
the O
ability O
to O
solve O
basic O
captchas O
( O
obscured O
letters O
and O
numbers O
) O
. O
First O
, O
the O
app O
creates O
a O
JavaScript O
function O
to O
call O
a O
Java O
method O
, O
getImageBase64 O
, O
exposed O
to O
WebView O
using O
addJavascriptInterface O
. O
The O
value O
used O
to O
replace O
GET_IMG_OBJECT O
comes O
from O
the O
JSON O
configuration O
. O
The O
app O
then O
uses O
JavaScript O
injection O
to O
create O
a O
new O
script O
in O
the O
carrier O
’ O
s O
web O
page O
to O
run O
the O
new O
function O
. O
The O
base64-encoded O
image O
is O
then O
uploaded O
to O
an O
image O
recognition O
service O
. O
If O
the O
text O
is O
retrieved O
successfully O
, O
the O
app O
uses O
JavaScript O
injection O
again O
to O
submit O
the O
HTML O
form O
with O
the O
captcha O
answer O
. O
CLOAKING O
Client-side O
Carrier O
Checks O
In O
our O
basic O
command O
& O
control O
example O
above O
, O
we O
didn O
’ O
t O
address O
the O
( O
incorrectly O
labeled O
) O
“ O
imei O
” O
field O
. O
This O
contains O
the O
Mobile O
Country O
Code O
( O
MCC O
) O
and O
Mobile O
Network O
Code O
( O
MNC O
) O
values O
that O
the O
billing O
process O
will O
work O
for O
. O
In O
this O
example O
, O
the O
server O
response O
contains O
several O
values O
for O
Thai O
carriers O
. O
The O
app O
checks O
if O
the O
device O
’ O
s O
network O
matches O
one O
of O
those O
provided O
by O
the O
server O
. O
If O
it O
does O
, O
it O
will O
commence O
with O
the O
billing O
process O
. O
If O
the O
value O
does O
not O
match O
, O
the O
app O
skips O
the O
“ O
disclosure O
” O
page O
and O
billing O
process O
and O
brings O
the O
user O
straight O
to O
the O
app O
content O
. O
In O
some O
versions O
, O
the O
server O
would O
only O
return O
valid O
responses O
several O
days O
after O
the O
apps O
were O
submitted O
. O
Server-side O
Carrier O
Checks O
In O
the O
JavaScript O
bridge O
API O
obfuscation O
example O
covered O
above O
, O
the O
server O
supplied O
the O
app O
with O
the O
necessary O
strings O
to O
complete O
the O
billing O
process O
. O
However O
, O
analysts O
may O
not O
always O
see O
the O
indicators O
of O
compromise O
in O
the O
server O
’ O
s O
response O
. O
In O
this O
example O
, O
the O
requests O
to O
the O
server O
take O
the O
following O
form O
: O
Here O
, O
the O
“ O
operator O
” O
query O
parameter O
is O
the O
Mobile O
Country O
Code O
and O
Mobile O
Network O
Code O
. O
The O
server O
can O
use O
this O
information O
to O
determine O
if O
the O
user O
’ O
s O
carrier O
is O
one O
of O
Bread B-Malware
’ O
s O
targets O
. O
If O
not O
, O
the O
response O
is O
scrubbed O
of O
the O
strings O
used O
to O
complete O
the O
billing O
fraud O
. O
MISLEADING O
USERS O
Bread B-Malware
apps O
sometimes O
display O
a O
pop-up O
to O
the O
user O
that O
implies O
some O
form O
of O
compliance O
or O
disclosure O
, O
showing O
terms O
and O
conditions O
or O
a O
confirm O
button O
. O
However O
, O
the O
actual O
text O
would O
often O
only O
display O
a O
basic O
welcome O
message O
. O
Other O
versions O
included O
all O
the O
pieces O
needed O
for O
a O
valid O
disclosure O
message O
. O
However O
, O
there O
are O
still O
two O
issues O
here O
: O
The O
numbers O
to O
contact O
for O
cancelling O
the O
subscription O
are O
not O
real O
The O
billing O
process O
commences O
even O
if O
you O
don O
’ O
t O
hit O
the O
“ O
Confirm O
” O
button O
Even O
if O
the O
disclosure O
here O
displayed O
accurate O
information O
, O
the O
user O
would O
often O
find O
that O
the O
advertised O
functionality O
of O
the O
app O
did O
not O
match O
the O
actual O
content O
. O
Bread B-Malware
apps O
frequently O
contain O
no O
functionality O
beyond O
the O
billing O
process O
or O
simply O
clone O
content O
from O
other O
popular O
apps O
. O
VERSIONING O
Bread B-Malware
has O
also O
leveraged O
an O
abuse O
tactic O
unique O
to O
app O
stores O
: O
versioning O
. O
Some O
apps O
have O
started O
with O
clean O
versions O
, O
in O
an O
attempt O
to O
grow O
user O
bases O
and O
build O
the O
developer O
accounts O
’ O
reputations O
. O
Only O
later O
is O
the O
malicious O
code O
introduced O
, O
through O
an O
update O
. O
Interestingly O
, O
early O
“ O
clean O
” O
versions O
contain O
varying O
levels O
of O
signals O
that O
the O
updates O
will O
include O
malicious O
code O
later O
. O
Some O
are O
first O
uploaded O
with O
all O
the O
necessary O
code O
except O
the O
one O
line O
that O
actually O
initializes O
the O
billing O
process O
. O
Others O
may O
have O
the O
necessary O
permissions O
, O
but O
are O
missing O
the O
classes O
containing O
the O
fraud O
code O
. O
And O
others O
have O
all O
malicious O
content O
removed O
, O
except O
for O
log O
comments O
referencing O
the O
payment O
process O
. O
All O
of O
these O
methods O
attempt O
to O
space O
out O
the O
introduction O
of O
possible O
signals O
in O
various O
stages O
, O
testing O
for O
gaps O
in O
the O
publication O
process O
. O
However O
, O
GPP O
does O
not O
treat O
new O
apps O
and O
updates O
any O
differently O
from O
an O
analysis O
perspective O
. O
FAKE O
REVIEWS O
When O
early O
versions O
of O
apps O
are O
first O
published O
, O
many O
five O
star O
reviews O
appear O
with O
comments O
like O
: O
“ O
So O
.. O
good O
.. O
” O
“ O
very O
beautiful O
” O
Later O
, O
1 O
star O
reviews O
from O
real O
users O
start O
appearing O
with O
comments O
like O
: O
“ O
Deception O
” O
“ O
The O
app O
is O
not O
honest O
… O
” O
SUMMARY O
Sheer O
volume O
appears O
to O
be O
the O
preferred O
approach O
for O
Bread B-Malware
developers O
. O
At O
different O
times O
, O
we O
have O
seen O
three O
or O
more O
active O
variants O
using O
different O
approaches O
or O
targeting O
different O
carriers O
. O
Within O
each O
variant O
, O
the O
malicious O
code O
present O
in O
each O
sample O
may O
look O
nearly O
identical O
with O
only O
one O
evasion O
technique O
changed O
. O
Sample O
1 O
may O
use O
AES-encrypted B-Organization
strings O
with O
reflection O
, O
while O
Sample O
2 O
( O
submitted O
on O
the O
same O
day O
) O
will O
use O
the O
same O
code O
but O
with O
plaintext O
strings O
. O
At O
peak O
times O
of O
activity O
, O
we O
have O
seen O
up O
to O
23 O
different O
apps O
from O
this O
family O
submitted O
to O
Play B-System
in O
one O
day O
. O
At O
other O
times O
, O
Bread B-Malware
appears O
to O
abandon O
hope O
of O
making O
a O
variant O
successful O
and O
we O
see O
a O
gap O
of O
a O
week O
or O
longer O
before O
the O
next O
variant O
. O
This O
family O
showcases O
the O
amount O
of O
resources O
that O
malware O
authors O
now O
have O
to O
expend O
. O
Google B-System
Play I-System
Protect I-System
is O
constantly O
updating O
detection O
engines O
and O
warning O
users O
of O
malicious O
apps O
installed O
on O
their O
device O
. O
SELECTED O
SAMPLES O
Package O
Name O
SHA-256 O
Digest O
com.rabbit.artcamera B-Indicator
18c277c7953983f45f2fe6ab4c7d872b2794c256604e43500045cb2b2084103f B-Indicator
org.horoscope.astrology.predict B-Indicator
6f1a1dbeb5b28c80ddc51b77a83c7a27b045309c4f1bff48aaff7d79dfd4eb26 B-Indicator
com.theforest.rotatemarswallpaper B-Indicator
4e78a26832a0d471922eb61231bc498463337fed8874db5f70b17dd06dcb9f09 B-Indicator
com.jspany.temp B-Indicator
0ce78efa764ce1e7fb92c4de351ec1113f3e2ca4b2932feef46d7d62d6ae87f5 B-Indicator
com.hua.ru.quan B-Indicator
780936deb27be5dceea20a5489014236796a74cc967a12e36cb56d9b8df9bc86 B-Indicator
com.rongnea.udonood B-Indicator
8b2271938c524dd1064e74717b82e48b778e49e26b5ac2dae8856555b5489131 B-Indicator
com.mbv.a.wp B-Indicator
01611e16f573da2c9dbc7acdd445d84bae71fecf2927753e341d8a5652b89a68 B-Indicator
com.pho.nec.sg B-Indicator
b4822eeb71c83e4aab5ddfecfb58459e5c5e10d382a2364da1c42621f58e119b B-Indicator
Exobot B-Malware
( O
Marcher B-Malware
) O
- O
Android B-System
banking O
Trojan O
on O
the O
rise O
February O
2017 O
Introduction O
The O
past O
months O
many O
different O
banking O
Trojans O
for O
the O
Android B-System
platform O
have O
received O
media O
attention O
. O
One O
of O
these O
, O
called O
Marcher B-Malware
( O
aka O
Exobot B-Malware
) O
, O
seems O
to O
be O
especially O
active O
with O
different O
samples O
appearing O
on O
a O
daily O
basis O
. O
This O
malware O
variant O
also O
appears O
to O
be O
technically O
superior O
to O
many O
other O
banking O
Trojans O
being O
able O
to O
use O
its O
overlay O
attack O
even O
on O
Android B-System
6 I-System
, O
which O
has O
technical O
improvements O
compared O
to O
the O
previous O
Android B-System
versions O
to O
prevent O
such O
attacks O
. O
The O
main O
infection O
vector O
is O
a O
phishing O
attack O
using O
SMS/MMS O
. O
The O
social O
engineering O
message O
includes O
a O
link O
that O
leads O
to O
a O
fake O
version O
of O
a O
popular O
app O
, O
using O
names O
like O
Runtastic B-System
, O
WhatsApp B-System
or O
Netflix B-System
. O
On O
installation O
, O
the O
app O
requests O
the O
user O
to O
provide O
SMS O
storage O
access O
and O
high O
Android B-System
privileges O
such O
as O
Device O
Admin O
. O
Other O
infection O
vectors O
include O
pornographic O
websites O
serving O
apps O
called O
Adobe B-System
Flash I-System
or O
YouPorn B-System
. O
The O
Marcher B-Malware
banking O
malware O
uses O
two O
main O
attack O
vectors O
. O
The O
first O
attack O
vector O
is O
to O
compromise O
the O
out O
of O
band O
authentication O
for O
online O
banks O
that O
rely O
on O
SMS O
using O
SMS O
forwarding O
. O
The O
second O
attack O
vector O
, O
the O
overlay O
attack O
, O
shows O
a O
customized O
phishing O
window O
whenever O
a O
targeted O
application O
is O
started O
on O
the O
device O
. O
The O
overlay O
window O
is O
often O
indistinguishable O
from O
the O
expected O
screen O
( O
such O
as O
a O
login O
screen O
for O
a O
banking O
app O
) O
and O
is O
used O
to O
steal O
the O
victim O
’ O
s O
banking O
credentials O
. O
The O
target O
list O
and O
bank O
specific O
fake O
login O
pages O
can O
be O
dynamically O
updated O
via O
their O
C2 O
panel O
( O
dashboard O
back-end O
) O
which O
significantly O
increases O
the O
adaptability O
and O
scalability O
of O
this O
attack O
. O
In O
addition O
, O
this O
type O
of O
Android B-System
banking O
malware O
does O
not O
require O
the O
device O
to O
be O
rooted O
or O
the O
app O
to O
have O
any O
specific O
Android B-System
permission O
( O
besides O
android.permission.INTERNET B-Indicator
to O
retrieve O
the O
overlay O
contents O
and O
send O
its O
captured O
data O
) O
. O
The O
many O
changes O
we O
see O
in O
the O
way O
the O
attacks O
are O
performed O
show O
that O
attackers O
are O
heavily O
experimenting O
to O
find O
the O
best O
way O
of O
infecting O
a O
mobile O
device O
and O
abusing O
existing O
functionality O
to O
perform O
successful O
phishing O
attacks O
. O
The O
next O
stage O
in O
device O
infection O
could O
be O
the O
use O
of O
exploit O
kits O
and O
malvertising O
, O
which O
would O
be O
quite O
effective O
due O
the O
many O
Android B-Vulnerability
vulnerabilities I-Vulnerability
and O
consumers O
with O
unpatched B-Vulnerability
devices I-Vulnerability
. O
In O
addition O
future O
Trojans O
could O
leverage O
root O
exploits O
to O
make O
them O
almost O
impossible O
to O
remove O
and O
give O
malicious O
actors O
the O
ability O
to O
hook O
generic O
low O
level O
API O
’ O
s O
that O
are O
used O
by O
all O
( O
banking O
) O
applications O
, O
just O
like O
the O
attack O
vector O
as O
has O
been O
used O
on O
the O
desktop O
platform O
for O
years O
. O
Technical O
Analysis O
Permissions O
Marcher B-Malware
’ O
s O
APK O
size O
is O
fairly O
small O
( O
only O
683KB O
for O
sample O
eb8f02fc30ec49e4af1560e54b53d1a7 B-Indicator
) O
, O
much O
smaller O
than O
most O
legitimate O
apps O
and O
other O
popular O
mobile O
malware O
samples O
. O
This O
sample O
only O
includes O
Dalvik O
bytecode O
and O
resources O
without O
any O
native O
libraries O
. O
The O
package O
name O
( O
vyn.hhsdzgvoexobmkygffzwuewrbikzud B-Indicator
) O
and O
its O
many O
activities O
and O
services O
have O
randomized O
names O
, O
probably O
to O
make O
it O
a O
bit O
more O
difficult O
to O
detect O
the O
package O
using O
blacklisting O
. O
The O
set O
of O
permissions O
required O
by O
Marcher B-Malware
according O
to O
the O
manifest O
is O
as O
follows O
: O
∗ O
android.permission.CHANGE_NETWORK_STATE B-Indicator
( O
change O
network O
connectivity O
state O
) O
∗ O
android.permission.SEND_SMS B-Indicator
( O
send O
SMS O
messages O
) O
∗ O
android.permission.USES_POLICY_FORCE_LOCK B-Indicator
( O
lock O
the O
device O
) O
∗ O
android.permission.RECEIVE_BOOT_COMPLETED B-Indicator
( O
start O
malware O
when O
device O
boots O
) O
∗ O
android.permission.INTERNET B-Indicator
( O
communicate O
with O
the O
internet O
) O
∗ O
android.permission.VIBRATE B-Indicator
( O
control O
the O
vibrator O
) O
∗ O
android.permission.ACCESS_WIFI_STATE B-Indicator
( O
view O
information O
about O
the O
status O
of O
Wi-Fi O
) O
∗ O
android.permission.WRITE_SMS B-Indicator
( O
edit/delete O
SMS O
) O
∗ O
android.permission.ACCESS_NETWORK_STATE B-Indicator
( O
view O
the O
status O
of O
all O
networks O
) O
∗ O
android.permission.WAKE_LOCK B-Indicator
( O
prevent O
the O
phone O
from O
going O
to O
sleep O
) O
∗ O
android.permission.GET_TASKS B-Indicator
( O
retrieve O
running O
applications O
) O
∗ O
android.permission.CALL_PHONE B-Indicator
( O
call O
phone O
numbers O
) O
∗ O
android.permission.WRITE_SETTINGS B-Indicator
( O
read/write O
global O
system O
settings O
) O
∗ O
android.permission.RECEIVE_SMS B-Indicator
( O
intercept O
SMS O
messages O
) O
∗ O
android.permission.READ_PHONE_STATE B-Indicator
( O
read O
phone O
details O
of O
the O
device O
such O
as O
phone O
number O
and O
serial O
number O
) O
∗ O
android.permission.CHANGE_WIFI_STATE B-Indicator
( O
connect O
to O
and O
disconnect O
from O
Wi-Fi O
networks O
and O
make O
changes O
to O
configured O
networks O
) O
∗ O
android.permission.READ_CONTACTS B-Indicator
( O
read O
all O
contact O
data O
) O
* O
android.permission.READ_SMS B-Indicator
( O
read O
SMS O
messages O
) O
Obviously O
a O
fairly O
significant O
list O
of O
permissions O
of O
which O
many O
are O
suspicious O
, O
especially O
when O
combined O
. O
Runtastic B-System
sample O
permission O
prompt O
Runtastic B-System
sample O
permission O
prompt O
Checking O
foreground O
app O
Marcher B-Malware
is O
one O
of O
the O
few O
Android O
banking O
Trojans O
to O
use O
the O
AndroidProcesses O
library O
, O
which O
enables O
the O
application O
to O
obtain O
the O
name O
of O
the O
Android B-System
package O
that O
is O
currently O
running O
in O
the O
foreground O
. O
This O
library O
is O
used O
because O
it O
uses O
the O
only O
( O
publicly O
known O
) O
way O
to O
retrieve O
this O
information O
on O
Android B-System
6 I-System
( O
using O
the O
process O
OOM O
score O
read O
from O
the O
/proc O
directory O
) O
. O
When O
the O
current O
app O
on O
the O
foreground O
matches O
with O
an O
app O
targeted O
by O
the O
malware O
, O
the O
Trojan O
will O
show O
the O
corresponding O
phishing O
overlay O
, O
making O
the O
user O
think O
it O
is O
the O
app O
that O
was O
just O
started O
. O
Dynamic O
overlays O
When O
victims O
open O
up O
a O
targeted O
app O
, O
Marcher B-Malware
smoothly O
displays O
an O
overlay O
, O
a O
customized O
WebView O
, O
looks O
in O
its O
application O
preferences O
( O
main_prefs.xml O
) O
and O
decides O
which O
specified O
URL O
is O
needed O
for O
the O
targeted O
app O
. O
The O
complete O
list O
of O
apps O
can O
be O
seen O
below O
. O
The O
phishing O
pages O
shown O
in O
the O
overlay O
use O
Ajax O
calls O
to O
communicate O
with O
a O
PHP O
back-end O
which O
stores O
all O
user O
input O
. O
The O
C2 O
backend O
url O
looks O
like O
this O
: O
https B-Indicator
: I-Indicator
//evilhost/c2folder/njs2/ I-Indicator
? I-Indicator
fields I-Indicator
[ I-Indicator
] I-Indicator
. O
There O
is O
no O
way O
to O
access O
the O
original O
app O
again O
even O
if O
victims O
terminate O
the O
overlay O
process O
and O
reopen O
app O
, O
until O
credit O
card O
( O
name O
, O
number O
, O
expiry O
date O
, O
security O
code O
) O
and/or O
bank O
information O
( O
PIN O
, O
VBV O
passcode O
, O
date O
of O
birth O
, O
etc O
. O
) O
are O
filled O
in O
and O
verified O
. O
The O
information O
is O
then O
stored O
in O
local O
app O
database O
as O
well O
as O
sent O
to O
the O
backend O
. O
Agent B-Malware
Smith I-Malware
: O
A O
New O
Species O
of O
Mobile O
Malware O
July O
10 O
, O
2019 O
Check B-Organization
Point I-Organization
Researchers O
recently O
discovered O
a O
new O
variant O
of O
mobile O
malware O
that O
quietly O
infected O
around O
25 O
million O
devices O
, O
while O
the O
user O
remains O
completely O
unaware O
. O
Disguised O
as O
Google B-Organization
related O
app O
, O
the O
core O
part O
of O
malware O
exploits O
various O
known O
Android B-Vulnerability
vulnerabilities I-Vulnerability
and O
automatically O
replaces O
installed O
apps O
on O
the O
device O
with O
malicious O
versions O
without O
the O
user O
’ O
s O
interaction O
. O
This O
unique O
on-device O
, O
just-in-time O
( O
JIT O
) O
approach O
inspired O
researchers O
to O
dub O
this O
malware O
as O
“ O
Agent B-Malware
Smith I-Malware
” O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
currently O
uses O
its O
broad O
access O
to O
the O
device O
’ O
s O
resources O
to O
show O
fraudulent O
ads O
for O
financial O
gain O
. O
This O
activity O
resembles O
previous O
campaigns O
such O
as O
Gooligan B-Malware
, O
HummingBad B-Malware
and O
CopyCat B-Malware
. O
The O
primary O
targets O
, O
so O
far O
, O
are O
based O
in O
India O
though O
other O
Asian O
countries O
such O
as O
Pakistan O
and O
Bangladesh O
are O
also O
affected O
. O
In O
a O
much-improved O
Android B-System
security O
environment O
, O
the O
actors O
behind O
Agent B-Malware
Smith I-Malware
seem O
to O
have O
moved O
into O
the O
more O
complex O
world O
of O
constantly O
searching O
for O
new O
loopholes O
, O
such O
as O
Janus B-Vulnerability
, O
Bundle B-Vulnerability
and O
Man-in-the-Disk B-Vulnerability
, O
to O
achieve O
a O
3-stage O
infection O
chain O
, O
in O
order O
to O
build O
a O
botnet O
of O
controlled O
devices O
to O
earn O
profit O
for O
the O
perpetrator O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
is O
possibly O
the O
first O
campaign O
seen O
that O
ingrates O
and O
weaponized O
all O
these O
loopholes O
and O
are O
described O
in O
detail O
below O
. O
In O
this O
case O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
is O
being O
used O
to O
for O
financial O
gain O
through O
the O
use O
of O
malicious O
advertisements O
. O
However O
, O
it O
could O
easily O
be O
used O
for O
far O
more O
intrusive O
and O
harmful O
purposes O
such O
as O
banking O
credential O
theft O
. O
Indeed O
, O
due O
to O
its O
ability O
to O
hide O
it O
’ O
s O
icon O
from O
the O
launcher O
and O
impersonates O
any O
popular O
existing O
apps O
on O
a O
device O
, O
there O
are O
endless O
possibilities O
for O
this O
sort O
of O
malware O
to O
harm O
a O
user O
’ O
s O
device O
. O
Check B-Organization
Point I-Organization
Research O
has O
submitted O
data O
to O
Google B-Organization
and O
law O
enforcement O
units O
to O
facilitate O
further O
investigation O
. O
As O
a O
result O
, O
information O
related O
to O
the O
malicious O
actor O
is O
tentatively O
redacted O
in O
this O
publication O
. O
Check B-Organization
Point I-Organization
has O
worked O
closely O
with O
Google B-Organization
and O
at O
the O
time O
of O
publishing O
, O
no O
malicious O
apps O
remain O
on O
the O
Play B-System
Store I-System
. O
Encounter O
In O
early O
2019 O
, O
the O
Check B-Organization
Point I-Organization
Research O
team O
observed O
a O
surge O
of O
Android B-System
malware O
attack O
attempts O
against O
users O
in O
India O
which O
had O
strong O
characteristics O
of O
Janus B-Vulnerability
vulnerability O
abuse O
; O
All O
samples O
our O
team O
collected O
during O
preliminary O
investigation O
had O
the O
ability O
to O
hide O
their O
app O
icons O
and O
claim O
to O
be O
Google B-Organization
related O
updaters O
or O
vending O
modules O
( O
a O
key O
component O
of O
Google B-System
Play I-System
framework O
) O
. O
Upon O
further O
analysis O
it O
became O
clear O
this O
application O
was O
as O
malicious O
as O
they O
come O
and O
initially O
resembled O
the O
CopyCat B-Malware
malware O
, O
discovered O
by O
Check B-Organization
Point I-Organization
Research O
back O
in O
April O
2016 O
. O
As O
the O
research O
progressed O
, O
it O
started O
to O
reveal O
unique O
characteristics O
which O
made O
us O
believe O
we O
were O
looking O
at O
an O
all-new O
malware O
campaign O
found O
in O
the O
wild O
. O
After O
a O
series O
of O
technical O
analysis O
( O
which O
is O
covered O
in O
detail O
below O
) O
and O
heuristic O
threat O
hunting O
, O
we O
discovered O
that O
a O
complete O
“ O
Agent B-Malware
Smith I-Malware
” O
infection O
has O
three O
main O
phases O
: O
A O
dropper O
app O
lures O
victim O
to O
install O
itself O
voluntarily O
. O
The O
initial O
dropper O
has O
a O
weaponized O
Feng O
Shui O
Bundle O
as O
encrypted O
asset O
files O
. O
Dropper O
variants O
are O
usually O
barely O
functioning O
photo O
utility O
, O
games O
, O
or O
sex O
related O
apps O
. O
The O
dropper O
automatically O
decrypts O
and O
installs O
its O
core O
malware O
APK O
which O
later O
conducts O
malicious O
patching O
and O
app O
updates O
. O
The O
core O
malware O
is O
usually O
disguised O
as O
Google B-Organization
Updater O
, O
Google B-Organization
Update O
for O
U O
or O
“ O
com.google.vending B-Indicator
” O
. O
The O
core O
malware O
’ O
s O
icon O
is O
hidden O
. O
The O
core O
malware O
extracts O
the O
device O
’ O
s O
installed O
app O
list O
. O
If O
it O
finds O
apps O
on O
its O
prey O
list O
( O
hard-coded O
or O
sent O
from O
C O
& O
C O
server O
) O
, O
it O
will O
extract O
the O
base O
APK O
of O
the O
target O
innocent O
app O
on O
the O
device O
, O
patch O
the O
APK O
with O
malicious O
ads O
modules O
, O
install O
the O
APK O
back O
and O
replace O
the O
original O
one O
as O
if O
it O
is O
an O
update O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
repacks O
its O
prey O
apps O
at O
smali/baksmali O
code O
level O
. O
During O
the O
final O
update O
installation O
process O
, O
it O
relies O
on O
the O
Janus B-Vulnerability
vulnerability O
to O
bypass O
Android B-System
’ O
s O
APK O
integrity O
checks O
. O
Upon O
kill O
chain O
completion O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
will O
then O
hijack O
compromised O
user O
apps O
to O
show O
ads O
. O
In O
certain O
situations O
, O
variants O
intercept O
compromised O
apps O
’ O
original O
legitimate O
ads O
display O
events O
and O
report O
back O
to O
the O
intended O
ad-exchange O
with O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
hacker O
’ O
s O
ad O
IDs O
. O
Our O
intelligence O
shows O
“ O
Agent B-Malware
Smith I-Malware
” O
droppers O
proliferate O
through O
third-party O
app O
store O
“ O
9Apps B-System
” O
, O
a O
UC O
team O
backed O
store O
, O
targeted O
mostly O
at O
Indian O
( O
Hindi O
) O
, O
Arabic O
, O
and O
Indonesian O
users O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
itself O
, O
though O
, O
seems O
to O
target O
mainly O
India O
users O
. O
Unlike O
previously O
discovered O
non O
Google B-System
Play I-System
centric O
campaigns O
whose O
victims O
almost O
exclusively O
come O
from O
less O
developed O
countries O
and O
regions O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
successfully O
penetrated O
into O
noticeable O
number O
of O
devices O
in O
developed O
countries O
such O
as O
Saudi O
Arabia O
, O
UK O
and O
US O
. O
Technical O
Analysis O
“ O
Agent B-Malware
Smith I-Malware
” O
has O
a O
modular O
structure O
and O
consists O
of O
the O
following O
modules O
: O
Loader O
Core O
Boot O
Patch O
AdSDK O
Updater O
As O
stated O
above O
, O
the O
first O
step O
of O
this O
infection O
chain O
is O
the O
dropper O
. O
The O
dropper O
is O
a O
repacked O
legitimate O
application O
which O
contains O
an O
additional O
piece O
of O
code O
– O
“ O
loader O
” O
. O
The O
loader O
has O
a O
very O
simple O
purpose O
, O
extract O
and O
run O
the O
“ O
core O
” O
module O
of O
“ O
Agent B-Malware
Smith I-Malware
” O
. O
The O
“ O
core O
” O
module O
communicates O
with O
the O
C O
& O
C O
server O
, O
receiving O
the O
predetermined O
list O
of O
popular O
apps O
to O
scan O
the O
device O
for O
. O
If O
any O
application O
from O
that O
list O
was O
found O
, O
it O
utilizes O
the O
Janus B-Vulnerability
vulnerability O
to O
inject O
the O
“ O
boot O
” O
module O
into O
the O
repacked O
application O
. O
After O
the O
next O
run O
of O
the O
infected O
application O
, O
the O
“ O
boot O
” O
module O
will O
run O
the O
“ O
patch O
” O
module O
, O
which O
hooks O
the O
methods O
from O
known O
ad O
SDKs O
to O
its O
own O
implementation O
. O
Figure O
1 O
: O
‘ O
Agent B-Malware
Smith I-Malware
’ O
s O
modular O
structure O
Technical O
Analysis O
– O
Loader O
Module O
The O
“ O
loader O
” O
module O
, O
as O
stated O
above O
, O
extracts O
and O
runs O
the O
“ O
core O
” O
module O
. O
While O
the O
“ O
core O
” O
module O
resides O
inside O
the O
APK O
file O
, O
it O
is O
encrypted O
and O
disguised O
as O
a O
JPG O
file O
– O
the O
first O
two O
bytes O
are O
actually O
the O
magic O
header O
of O
JPG O
files O
, O
while O
the O
rest O
of O
the O
data O
is O
encoded O
with O
an O
XOR O
cipher O
. O
Figure O
2 O
: O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
jpg O
file O
structure O
After O
the O
extraction O
, O
the O
“ O
loader O
” O
module O
adds O
the O
code O
to O
the O
application O
while O
using O
the O
legitimate O
mechanism O
by O
Android B-System
to O
handle O
large O
DEX O
files O
. O
Figure O
3 O
: O
Loading O
core O
malicious O
code O
into O
the O
benign O
application O
Once O
the O
“ O
core O
” O
module O
is O
extracted O
and O
loaded O
, O
the O
“ O
loader O
” O
uses O
the O
reflection O
technique O
to O
initialize O
and O
start O
the O
“ O
core O
” O
module O
. O
Figure O
4 O
: O
Loader O
calls O
initialization O
method O
Technical O
Analysis O
– O
Core O
Module O
With O
the O
main O
purpose O
of O
spreading O
the O
infection O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
implements O
in O
the O
“ O
core O
” O
module O
: O
A O
series O
of O
‘ O
Bundle B-Vulnerability
’ O
vulnerabilities O
, O
which O
is O
used O
to O
install O
applications O
without O
the O
victim O
’ O
s O
awareness O
. O
The O
Janus B-Vulnerability
vulnerability O
, O
which O
allows O
the O
actor O
to O
replace O
any O
application O
with O
an O
infected O
version O
. O
The O
“ O
core O
” O
module O
contacts O
the O
C O
& O
C O
server O
, O
trying O
to O
get O
a O
fresh O
list O
of O
applications O
to O
search O
for O
, O
or O
if O
that O
fails O
, O
use O
a O
default O
app O
list O
: O
whatsapp B-System
lenovo.anyshare.gps B-Indicator
mxtech.videoplayer.ad B-Indicator
jio.jioplay.tv B-Indicator
jio.media.jiobeats B-Indicator
jiochat.jiochatapp B-Indicator
jio.join B-Indicator
good.gamecollection B-Indicator
opera.mini.native B-Indicator
startv.hotstar B-Indicator
meitu.beautyplusme B-Indicator
domobile.applock B-Indicator
touchtype.swiftkey B-Indicator
flipkart.android B-Indicator
cn.xender B-Indicator
eterno O
truecaller O
For O
each O
application O
on O
the O
list O
, O
the O
“ O
core O
” O
module O
checks O
for O
a O
matching O
version O
and O
MD5 O
hash O
of O
the O
installed O
application O
, O
and O
also O
checks O
for O
the O
application O
running O
in O
the O
user-space O
. O
If O
all O
conditions O
are O
met O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
tries O
to O
infect O
the O
application O
. O
The O
“ O
core O
” O
module O
will O
use O
one O
of O
two O
methods O
to O
infect O
the O
application O
– O
Decompile O
and O
Binary O
. O
The O
decompile O
method O
is O
based O
on O
the O
fact O
that O
Android B-System
applications O
are O
Java-based O
, O
meaning O
it O
is O
possible O
to O
recompile O
it O
. O
Therefore O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
decompiles O
both O
the O
original O
application O
and O
the O
malicious O
payload O
and O
fuses O
them O
together O
. O
Figure O
5 O
: O
core O
module O
mixes O
malicious O
payload O
with O
the O
original O
application O
While O
decompiling O
the O
original O
app O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
has O
the O
opportunity O
to O
modify O
the O
methods O
inside O
, O
replace O
some O
of O
the O
methods O
in O
the O
original O
application O
that O
handles O
advertisement O
with O
its O
own O
code O
and O
focus O
on O
methods O
communicating O
with O
‘ O
AdMob B-System
’ O
, O
‘ O
Facebook B-System
’ O
, O
‘ O
MoPub B-System
’ O
and O
‘ O
Unity B-System
Ads I-System
’ O
. O
Figure O
6 O
: O
Targeted O
ad O
network O
Figure O
7 O
: O
Injection O
example O
After O
all O
of O
the O
required O
changes O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
compiles O
the O
application O
and O
builds O
a O
DEX O
file O
containing O
both O
the O
original O
code O
of O
the O
original O
application O
and O
the O
malicious O
payload O
. O
In O
some O
cases O
, O
the O
decompilation O
process O
will O
fail O
, O
and O
“ O
Agent B-Malware
Smith I-Malware
” O
will O
try O
another O
method O
for O
infecting O
the O
original O
application O
– O
A O
binary O
patch O
, O
which O
simply O
provides O
a O
binary O
file O
of O
the O
“ O
boot O
” O
module O
of O
“ O
Agent B-Malware
Smith I-Malware
” O
. O
Once O
the O
payload O
is O
prepared O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
uses O
it O
to O
build O
another O
APK O
file O
, O
exploiting O
the O
Janus B-Vulnerability
vulnerability O
: O
Figure O
8 O
: O
The O
new O
infected O
APK O
file O
structure O
Solely O
injecting O
the O
code O
of O
the O
loader O
is O
not O
enough O
. O
As O
“ O
Agent B-Malware
Smith I-Malware
” O
uses O
a O
modular O
approach O
, O
and O
as O
stated O
earlier O
, O
the O
original O
loader O
extracts O
everything O
from O
the O
assets O
, O
the O
usage O
of O
the O
Janus B-Vulnerability
vulnerability O
can O
only O
change O
the O
code O
of O
the O
original O
application O
, O
not O
the O
resources O
. O
This O
means O
that O
the O
only O
thing O
possible O
in O
this O
case O
is O
to O
replace O
its O
DEX O
file O
. O
To O
overcome O
this O
issue O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
found O
another O
solution O
. O
Seeing O
as O
the O
system O
loader O
of O
the O
DEX O
files O
( O
ART O
) O
fully O
ignores O
everything O
that O
goes O
after O
the O
data O
section O
, O
the O
patcher O
writes O
all O
of O
its O
resources O
right O
there O
. O
This O
action O
changes O
the O
original O
file O
size O
of O
the O
DEX O
file O
, O
which O
makes O
the O
malicious O
resources O
a O
part O
of O
the O
DEX O
file O
, O
a O
section O
that O
is O
ignored O
by O
the O
signature O
validation O
process O
. O
Figure O
9 O
: O
Malware O
secretly O
adds O
malicious O
resources O
to O
the O
DEX O
file O
Now O
, O
after O
the O
alteration O
of O
the O
original O
application O
, O
Android B-System
’ O
s O
package O
manager O
will O
think O
that O
this O
is O
an O
update O
for O
the O
application O
signed O
by O
the O
same O
certificate O
, O
but O
in O
reality O
, O
it O
will O
execute O
the O
malicious O
DEX O
file O
. O
Even O
now O
, O
this O
is O
still O
not O
enough O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
needs O
to O
be O
updated/installed O
without O
the O
user O
’ O
s O
consent O
. O
To O
achieve O
this O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
utilizes O
a O
series O
of O
1-day B-Vulnerability
vulnerabilities I-Vulnerability
, O
which O
allows O
any O
application O
to O
run O
an O
activity O
inside O
a O
system O
application O
, O
even O
if O
this O
activity O
is O
not O
exported O
. O
The O
malicious O
application O
sends O
a O
request O
to O
choose O
a O
network O
account O
, O
a O
specific O
account O
that O
can O
only O
be O
processed O
by O
authentication O
services O
exported O
by O
the O
malicious O
application O
. O
The O
system O
service O
‘ O
AccountManagerService O
’ O
looks O
for O
the O
application O
that O
can O
process O
this O
request O
. O
While O
doing O
so O
, O
it O
will O
reach O
a O
service O
exported O
by O
“ O
Agent B-Malware
Smith I-Malware
” O
, O
and O
sends O
out O
an O
authentication O
request O
that O
would O
lead O
to O
a O
call O
to O
the O
‘ O
addAccount O
’ O
method O
. O
Then O
, O
a O
request O
is O
formed O
in O
such O
a O
way O
that O
an O
activity O
that O
installs O
the O
application O
is O
called O
, O
bypassing O
all O
security O
checks O
. O
Figure O
10 O
: O
The O
algorithm O
of O
the O
malicious O
update O
, O
while O
“ O
Agent B-Malware
Smith I-Malware
” O
updates O
application O
If O
all O
that O
has O
failed O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
turns O
to O
Man-in-the-Disk B-Vulnerability
vulnerability O
for O
‘ O
SHAREit B-System
’ O
or O
‘ O
Xender B-System
’ O
applications O
. O
This O
is O
a O
very O
simple O
process O
, O
which O
is O
replacing O
their O
update O
file O
on O
SD O
card O
with O
its O
own O
malicious O
payload O
. O
Figure O
11 O
: O
‘ O
Agent B-Malware
Smith I-Malware
’ O
uses O
man-in-disk B-Vulnerability
to O
install O
the O
malicious O
update O
Technical O
Analysis O
– O
Boot O
Module O
The O
“ O
boot O
” O
module O
is O
basically O
another O
“ O
loader O
” O
module O
, O
but O
this O
time O
it O
’ O
s O
executed O
in O
the O
infected O
application O
. O
The O
purpose O
of O
this O
module O
is O
to O
extract O
and O
execute O
a O
malicious O
payload O
– O
the O
“ O
patch O
” O
module O
. O
The O
infected O
application O
contains O
its O
payload O
inside O
the O
DEX O
file O
. O
All O
that O
is O
needed O
is O
to O
get O
the O
original O
size O
of O
the O
DEX O
file O
and O
read O
everything O
that O
comes O
after O
this O
offset O
. O
Figure O
12 O
: O
Boot O
module O
After O
the O
patch O
module O
is O
extracted O
, O
the O
“ O
boot O
” O
module O
executes O
it O
, O
using O
the O
same O
method O
described O
in O
the O
“ O
loader O
” O
module O
. O
The O
“ O
boot O
” O
module O
has O
placeholder O
classes O
for O
the O
entry O
points O
of O
the O
infected O
applications O
. O
This O
allows O
the O
“ O
boot O
” O
module O
to O
execute O
the O
payloads O
when O
the O
infected O
application O
is O
started O
. O
Figure O
13 O
: O
placeholder O
classes O
in O
Boot O
module O
Technical O
Analysis O
– O
Patch O
Module O
When O
“ O
Agent B-Malware
Smith I-Malware
” O
has O
reached O
its O
goal O
– O
a O
malicious O
payload O
running O
inside O
the O
original O
application O
, O
with O
hooks O
on O
various O
methods O
– O
at O
this O
point O
, O
everything O
lies O
with O
maintaining O
the O
required O
code O
in O
case O
of O
an O
update O
for O
the O
original O
application O
. O
While O
investing O
a O
lot O
of O
resources O
in O
the O
development O
of O
this O
malware O
, O
the O
actor O
behind O
“ O
Agent B-Malware
Smith I-Malware
” O
does O
not O
want O
a O
real O
update O
to O
remove O
all O
of O
the O
changes O
made O
, O
so O
here O
is O
where O
the O
“ O
patch O
” O
module O
comes O
in O
to O
play O
With O
the O
sole O
purpose O
of O
disabling O
automatic O
updates O
for O
the O
infected O
application O
, O
this O
module O
observes O
the O
update O
directory O
for O
the O
original O
application O
and O
removes O
the O
file O
once O
it O
appears O
. O
Another O
trick O
in O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
arsenal O
is O
to O
change O
the O
settings O
of O
the O
update O
timeout O
, O
making O
the O
original O
application O
wait O
endlessly O
for O
the O
update O
check O
. O
Figure O
14 O
: O
disabling O
infected O
apps O
auto-update O
Figure O
15 O
: O
changing O
the O
settings O
of O
the O
update O
timeout O
The O
Ad O
Displaying O
Payload O
Following O
all O
of O
the O
above O
, O
now O
is O
the O
time O
to O
take O
a O
look O
into O
the O
actual O
payload O
that O
displays O
ads O
to O
the O
victim O
. O
In O
the O
injected O
payload O
, O
the O
module O
implements O
the O
method O
‘ O
callActivityOnCreate O
’ O
. O
At O
any O
time O
an O
infected O
application O
will O
create O
an O
activity O
, O
this O
method O
will O
be O
called O
, O
and O
call O
‘ O
requestAd O
’ O
from O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
code O
. O
“ O
Agent B-Malware
Smith I-Malware
” O
will O
replace O
the O
original O
application O
’ O
s O
activities O
with O
an O
in-house O
SDK O
’ O
s O
activity O
, O
which O
will O
show O
the O
banner O
received O
from O
the O
server O
. O
In O
the O
case O
of O
the O
infected O
application O
not O
specified O
in O
the O
code O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
will O
simply O
show O
ads O
on O
the O
activity O
being O
loaded O
. O
Figure O
16 O
: O
integrating O
an O
in-house O
ad O
SDK O
Figure O
17 O
: O
replacing O
original O
app O
activities O
with O
the O
malicious O
ad O
SDK O
activity O
Figure O
18 O
: O
the O
malware O
showing O
ads O
on O
any O
activity O
being O
loaded O
Connecting O
the O
Dots O
As O
our O
malware O
sample O
analysis O
took O
the O
team O
closer O
to O
reveal O
the O
“ O
Agent O
Smith O
” O
campaign O
in O
its O
entirety O
and O
it O
is O
here O
that O
the O
C O
& O
C O
server O
investigation O
enters O
the O
center O
stage O
. O
We O
started O
with O
most O
frequently O
used O
C O
& O
C O
domains O
“ O
a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.com I-Indicator
” O
, O
“ O
a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.net I-Indicator
” O
, O
and O
“ O
a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.org I-Indicator
” O
. O
Among O
multiple O
sub-domains O
, O
“ O
ad.a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.org I-Indicator
” O
and O
“ O
gd.a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.org I-Indicator
” O
both O
historically O
resolved O
to O
the O
same O
suspicious O
IP O
address O
. O
The O
reverse O
DNS O
history O
of O
this O
IP O
brought O
“ O
ads.i B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
e.com I-Indicator
” O
into O
our O
attention O
. O
An O
extended O
malware O
hunting O
process O
returned O
to O
us O
a O
large O
set O
of O
“ O
Agent B-Malware
Smith I-Malware
” O
dropper O
variants O
which O
helped O
us O
further O
deduce O
a O
relation O
among O
multiple O
C O
& O
C O
server O
infrastructures O
. O
In O
a O
different O
period O
of O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
, O
droppers O
and O
core O
modules O
used O
various O
combinations O
of O
the O
“ O
a O
* O
* O
* O
d O
” O
and O
“ O
i O
* O
* O
* O
e O
” O
domains O
for O
malicious O
operations O
such O
as O
prey O
list O
query O
, O
patch O
request O
and O
ads O
request O
. O
With O
a O
bit O
of O
luck O
, O
we O
managed O
to O
find O
logs O
in O
which O
the O
evidence O
showed O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
C O
& O
C O
front O
end O
routinely O
distributes O
a O
workload O
between O
“ O
w.h B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
g.com I-Indicator
” O
and O
“ O
tt.a B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
d.net I-Indicator
” O
. O
An O
in-depth O
understanding O
of O
the O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
campaign O
C O
& O
C O
infrastructure O
enabled O
us O
to O
reach O
the O
conclusion O
that O
the O
owner O
of O
“ B-Indicator
i I-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
e.com I-Indicator
” O
, O
“ O
h B-Indicator
* I-Indicator
* I-Indicator
* I-Indicator
g.com I-Indicator
” O
is O
the O
group O
of O
hackers O
behind O
“ O
Agent B-Malware
Smith I-Malware
” O
. O
Figure O
19 O
: O
C O
& O
C O
infrastructure O
diagram O
The O
Infection O
Landscape O
“ O
Agent B-Malware
Smith I-Malware
” O
droppers O
show O
a O
very O
greedy O
infection O
tactic O
. O
It O
’ O
s O
not O
enough O
for O
this O
malware O
family O
to O
swap O
just O
one O
innocent O
application O
with O
an O
infected O
double O
. O
It O
does O
so O
for O
each O
and O
every O
app O
on O
the O
device O
as O
long O
as O
the O
package O
names O
are O
on O
its O
prey O
list O
. O
Over O
time O
, O
this O
campaign O
will O
also O
infect O
the O
same O
device O
, O
repeatedly O
, O
with O
the O
latest O
malicious O
patches O
. O
This O
lead O
us O
to O
estimate O
there O
to O
be O
over O
2.8 O
billion O
infections O
in O
total O
, O
on O
around O
25 O
Million O
unique O
devices O
, O
meaning O
that O
on O
average O
, O
each O
victim O
would O
have O
suffered O
roughly O
112 O
swaps O
of O
innocent O
applications O
. O
As O
an O
initial O
attack O
vector O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
abuses O
the O
9Apps B-System
market O
– O
with O
over O
360 O
different O
dropper O
variants O
. O
To O
maximize O
profit O
, O
variants O
with O
“ O
MinSDK O
” O
or O
“ O
OTA O
” O
SDK O
are O
present O
to O
further O
infect O
victims O
with O
other O
adware O
families O
. O
The O
majority O
of O
droppers O
in O
9Apps B-System
are O
games O
, O
while O
the O
rest O
fall O
into O
categories O
of O
adult O
entertainment O
, O
media O
player O
, O
photo O
utilities O
, O
and O
system O
utilities O
. O
Figure O
20 O
: O
dropper O
app O
category O
distribution O
Among O
the O
vast O
number O
of O
variants O
, O
the O
top O
5 O
most O
infectious O
droppers O
alone O
have O
been O
downloaded O
more O
than O
7.8 O
million O
times O
of O
the O
infection O
operations O
against O
innocent O
applications O
: O
Figure O
21 O
: O
Top O
5 O
most O
infectious O
droppers O
The O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
is O
primarily O
targeted O
at O
Indian O
users O
, O
who O
represent O
59 O
% O
of O
the O
impacted O
population O
. O
Unlike O
previously O
seen O
non-GP O
( O
Google B-System
Play I-System
) O
centric O
malware O
campaigns O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
has O
a O
significant O
impact O
upon O
not O
only O
developing O
countries O
but O
also O
some O
developed O
countries O
where O
GP O
is O
readily O
available O
. O
For O
example O
, O
the O
US O
( O
with O
around O
303k O
infections O
) O
, O
Saudi O
Arabia O
( O
245k O
) O
, O
Australia O
( O
141k O
) O
and O
the O
UK O
( O
137k O
) O
. O
Figure O
22 O
: O
world O
infection O
heat O
map O
Considering O
that O
India O
is O
by O
far O
the O
most O
infected O
county O
by O
“ O
Agent B-Malware
Smith I-Malware
” O
, O
overall O
compromised O
device O
brand O
distribution O
is O
heavily O
influenced O
by O
brand O
popularity O
among O
Indian O
Android B-System
users O
: O
Figure O
23 O
: O
infected O
brand O
distribution O
While O
most O
infections O
occurred O
on O
devices O
running O
Android B-System
5 I-System
and I-System
6 I-System
, O
we O
also O
see O
a O
considerable O
number O
of O
successful O
attacks O
against O
newer O
Android B-System
versions O
. O
It O
is O
a O
worrying O
observation O
. O
AOSP O
patched O
the O
Janus B-Vulnerability
vulnerability O
since O
version O
7 O
by O
introducing O
APK O
Signature O
Scheme O
V2 O
. O
However O
, O
in O
order O
to O
block O
Janus B-Vulnerability
abuse O
, O
app O
developers O
need O
to O
sign O
their O
apps O
with O
the O
new O
scheme O
so O
that O
Android B-System
framework O
security O
component O
could O
conduct O
integrity O
checks O
with O
enhanced O
features O
. O
Figure O
25 O
: O
infected O
Android B-System
version O
distribution O
To O
further O
analyze O
“ O
Agent B-Malware
Smith I-Malware
” O
’ O
s O
infection O
landscape O
, O
we O
dived O
into O
the O
top O
10 O
infected O
countries O
: O
Country O
Total O
Devices O
Total O
Infection O
Event O
Count O
Avg O
. O
App O
Swap O
Per O
Device O
Avg O
. O
Droppers O
Per O
Device O
Avg O
. O
Months O
Device O
Remained O
Infected O
India O
15,230,123 O
2,017,873,249 O
2.6 O
1.7 O
2.1 O
Bangladesh O
2,539,913 O
208,026,886 O
2.4 O
1.5 O
2.2 O
Pakistan O
1,686,216 O
94,296,907 O
2.4 O
1.6 O
2 O
Indonesia O
572,025 O
67,685,983 O
2 O
1.5 O
2.2 O
Nepal O
469,274 O
44,961,341 O
2.4 O
1.6 O
2.4 O
US O
302,852 O
19,327,093 O
1.7 O
1.4 O
1.8 O
Nigeria O
287,167 O
21,278,498 O
2.4 O
1.3 O
2.3 O
Hungary O
282,826 O
7,856,064 O
1.7 O
1.3 O
1.7 O
Saudi O
Arabia O
245,698 O
18,616,259 O
2.3 O
1.6 O
1.9 O
Myanmar O
234,338 O
9,729,572 O
1.5 O
1.4 O
1.9 O
“ O
Agent B-Malware
Smith I-Malware
” O
Timeline O
Early O
signs O
of O
activity O
from O
the O
actor O
behind O
“ O
Agent O
Smith O
” O
can O
be O
traced O
back O
to O
January O
2016 O
. O
We O
classify O
this O
40-month O
period O
into O
three O
main O
stages O
. O
January O
2016 O
– O
May O
2018 O
: O
In O
this O
stage O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
hackers O
started O
to O
try O
out O
9Apps O
as O
a O
distribution O
channel O
for O
their O
adware O
. O
During O
this O
period O
, O
malware O
samples O
display O
some O
typical O
adware O
characteristics O
such O
as O
unnecessary O
permission O
requirements O
and O
pop-up O
windows B-System
. O
During O
this O
time O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
hackers O
eventually O
built O
up O
a O
vast O
number O
of O
app O
presence O
on O
9Apps B-System
, O
which O
later O
would O
serve O
as O
publication O
channels O
for O
evolved O
droppers O
. O
However O
, O
samples O
don O
’ O
t O
have O
key O
capabilities O
to O
infect O
innocent O
apps O
on O
victim O
devices O
yet O
. O
May O
2018 O
to O
April O
2019 O
: O
This O
is O
the O
actual O
mature O
stage O
of O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
. O
From O
early O
2018 O
prior O
to O
May O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
hackers O
started O
to O
experiment O
with O
Bundle O
Feng O
Shui O
, O
the O
key O
tool O
which O
gives O
“ O
Agent B-Malware
Smith I-Malware
” O
malware O
family O
capabilities O
to O
infect O
innocent O
apps O
on O
the O
device O
. O
A O
series O
of O
pilot O
runs O
were O
executed O
. O
After O
some O
major O
upgrade O
, O
by O
mid-June O
, O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
reached O
its O
peak O
. O
Its O
dropper O
family O
finished O
integration O
with O
Bundle O
Feng O
Shui O
and O
campaign O
C O
& O
C O
infrastructure O
was O
shifted O
to O
AWS B-System
cloud O
. O
The O
Campaign O
achieved O
exponential O
growth O
from O
June O
to O
December O
2018 O
with O
the O
infection O
number O
staying O
stable O
into O
early O
2019 O
. O
Post-April O
2019 O
: O
Starting O
from O
early O
2019 O
, O
the O
new O
infection O
rate O
of O
“ O
Agent B-Malware
Smith I-Malware
” O
dropped O
significantly O
. O
From O
early O
April O
, O
hackers O
started O
to O
build O
a O
new O
major O
update O
to O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
under O
the O
name O
“ O
leechsdk O
” O
. O
Figure O
26 O
: O
“ O
Agent B-Malware
Smith I-Malware
” O
Campaign O
timeline O
Greater O
“ O
Agent B-Malware
Smith I-Malware
” O
Campaign O
Discovery O
Orchestrating O
a O
successful O
9Apps B-System
centric O
malware O
campaign O
, O
the O
actor O
behind O
“ O
Agent B-Malware
Smith I-Malware
” O
established O
solid O
strategies O
in O
malware O
proliferation O
and O
payload O
delivery O
. O
The O
actor O
also O
built O
solid O
backend O
infrastructures O
which O
can O
handle O
high O
volume O
concurrent O
requests O
. O
During O
our O
extended O
threat O
hunting O
, O
we O
uncovered O
11 O
apps O
on O
the O
Google B-System
Play I-System
store I-System
that O
contain O
a O
malicious O
yet O
dormant O
SDK O
related O
to O
“ O
Agent B-Malware
Smith I-Malware
” O
actor O
. O
This O
discovery O
indicates O
the O
actor O
’ O
s O
ambition O
in O
expanding O
operations O
into O
Google B-System
Play I-System
store O
with O
previous O
success O
experience O
from O
the O
main O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
. O
Instead O
of O
embedding O
core O
malware O
payload O
in O
droppers O
, O
the O
actor O
switches O
to O
a O
more O
low-key O
SDK O
approach O
. O
In O
the O
dangerous O
module O
lies O
a O
kill O
switch O
logic O
which O
looks O
for O
the O
keyword O
“ O
infect O
” O
. O
Once O
the O
keyword O
is O
present O
, O
the O
SDK O
will O
switch O
from O
innocent O
ads O
server O
to O
malicious O
payload O
delivery O
ones O
. O
Hence O
, O
we O
name O
this O
new O
spin-off O
campaign O
as O
Jaguar O
Kill O
Switch O
. O
The O
below O
code O
snippet O
is O
currently O
isolated O
and O
dormant O
. O
In O
the O
future O
, O
it O
will O
be O
invoked O
by O
malicious O
SDK O
during O
banner O
ads O
display O
. O
Figure O
26 O
: O
the O
kill O
switch O
code O
snippet O
Evidence O
implies O
that O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
actor O
is O
currently O
laying O
the O
groundwork O
, O
increasing O
its O
Google B-System
Play I-System
penetration O
rate O
and O
waiting O
for O
the O
right O
timing O
to O
kick O
off O
attacks O
. O
By O
the O
time O
of O
this O
publication O
, O
two O
Jaguar O
Kill O
Switch O
infected O
app O
has O
reached O
10 O
million O
downloads O
while O
others O
are O
still O
in O
their O
early O
stages O
. O
Check B-Organization
Point I-Organization
Research O
reported O
these O
dangerous O
apps O
to O
Google B-Organization
upon O
discovery O
. O
Currently O
, O
all O
bespoke O
apps O
have O
been O
taken O
down O
from O
the O
Google B-System
Play I-System
store O
. O
Figure O
28 O
: O
Jaguar O
Kill O
Switch O
infected O
GP O
apps O
Peek O
Into O
the O
Actor O
Based O
on O
all O
of O
the O
above O
, O
we O
connected O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
to O
a O
Chinese O
internet O
company O
located O
in O
Guangzhou O
whose O
front O
end O
legitimate O
business O
is O
to O
help O
Chinese O
Android B-System
developers O
publish O
and O
promote O
their O
apps O
on O
overseas O
platforms O
. O
Various O
recruitment O
posts O
on O
Chinese O
job O
sites O
and O
Chinese B-System
National I-System
Enterprise I-System
Credit I-System
Information I-System
Public I-System
System I-System
( I-System
NECIPS I-System
) I-System
data O
led O
us O
one O
step O
further O
, O
linking O
the O
actor O
to O
its O
legal O
entity O
name O
. O
Interestingly O
, O
we O
uncovered O
several O
expired O
job O
posting O
of O
Android B-System
reverse O
engineer O
from O
the O
actor O
’ O
s O
front O
business O
published O
in O
2018 O
and O
2019 O
. O
It O
seems O
that O
the O
people O
who O
filled O
these O
roles O
are O
key O
to O
“ O
Agent B-Malware
Smith I-Malware
’ O
s O
success O
, O
yet O
not O
quite O
necessary O
for O
actor O
’ O
s O
legitimate O
side O
of O
business O
. O
With O
a O
better O
understanding O
of O
the O
“ O
Agent B-Malware
Smith I-Malware
” O
actor O
than O
we O
had O
in O
the O
initial O
phase O
of O
campaign O
hunting O
, O
we O
examined O
the O
list O
of O
target O
innocent O
apps O
once O
again O
and O
discovered O
the O
actor O
’ O
s O
unusual O
practices O
in O
choosing O
targets O
. O
It O
seems O
, O
“ O
Agent B-Malware
Smith I-Malware
” O
prey O
list O
does O
not O
only O
have O
popular O
yet O
Janus B-Vulnerability
vulnerable O
apps O
to O
ensure O
high O
proliferation O
, O
but O
also O
contain O
competitor O
apps O
of O
actor O
’ O
s O
legitimate O
business O
arm O
to O
suppress O
competition O
. O
Conclusion O
Although O
the O
actor O
behind O
“ O
Agent B-Malware
Smith I-Malware
” O
decided O
to O
make O
their O
illegally O
acquired O
profit O
by O
exploiting O
the O
use O
of O
ads O
, O
another O
actor O
could O
easily O
take O
a O
more O
intrusive O
and O
harmful O
route O
. O
With O
the O
ability O
to O
hide O
its O
icon O
from O
the O
launcher O
and O
hijack O
popular O
existing O
apps O
on O
a O
device O
, O
there O
are O
endless O
possibilities O
to O
harm O
a O
user O
’ O
s O
digital O
even O
physical O
security O
. O
Today O
this O
malware O
shows O
unwanted O
ads O
, O
tomorrow O
it O
could O
steal O
sensitive O
information O
; O
from O
private O
messages O
to O
banking O
credentials O
and O
much O
more O
. O
The O
“ O
Agent B-Malware
Smith I-Malware
” O
campaign O
serves O
as O
a O
sharp O
reminder O
that O
effort O
from O
system O
developers O
alone O
is O
not O
enough O
to O
build O
a O
secure O
Android B-System
eco-system O
. O
It O
requires O
attention O
and O
action O
from O
system O
developers O
, O
device O
manufacturers O
, O
app O
developers O
, O
and O
users O
, O
so O
that O
vulnerability O
fixes O
are O
patched O
, O
distributed O
, O
adopted O
and O
installed O
in O
time O
. O
It O
is O
also O
another O
example O
for O
why O
organizations O
and O
consumers O
alike O
should O
have O
an O
advanced O
mobile O
threat O
prevention O
solution O
installed O
on O
the O
device O
to O
protect O
themselves O
against O
the O
possibility O
of O
unknowingly O
installing O
malicious O
apps O
, O
even O
from O
trusted O
app O
stores O
. O
Dvmap B-Malware
: O
the O
first O
Android B-System
malware O
with O
code O
injection O
08 O
JUN O
2017 O
In O
April O
2017 O
we O
started O
observing O
new O
rooting O
malware O
being O
distributed O
through O
the O
Google B-System
Play I-System
Store I-System
. O
Unlike O
other O
rooting O
malware O
, O
this O
Trojan O
not O
only O
installs O
its O
modules O
into O
the O
system O
, O
it O
also O
injects O
malicious O
code O
into O
the O
system O
runtime O
libraries O
. O
Kaspersky B-Organization
Lab I-Organization
products O
detect O
it O
as O
Trojan.AndroidOS.Dvmap.a B-Indicator
. O
The O
distribution O
of O
rooting O
malware O
through O
Google B-System
Play I-System
is O
not O
a O
new O
thing O
. O
For O
example O
, O
the O
Ztorg B-Malware
Trojan I-Malware
has O
been O
uploaded O
to O
Google B-System
Play I-System
almost O
100 O
times O
since O
September O
2016 O
. O
But O
Dvmap B-Malware
is O
very O
special O
rooting O
malware O
. O
It O
uses O
a O
variety O
of O
new O
techniques O
, O
but O
the O
most O
interesting O
thing O
is O
that O
it O
injects O
malicious O
code O
into O
the O
system O
libraries O
– O
libdmv.so B-Indicator
or O
libandroid_runtime.so B-Indicator
. O
This O
makes O
Dvmap B-Malware
the O
first O
Android B-System
malware O
that O
injects O
malicious O
code O
into O
the O
system O
libraries O
in O
runtime O
, O
and O
it O
has O
been O
downloaded O
from O
the O
Google B-System
Play I-System
Store I-System
more O
than O
50,000 O
times O
. O
Kaspersky B-Organization
Lab I-Organization
reported O
the O
Trojan O
to O
Google B-Organization
, O
and O
it O
has O
now O
been O
removed O
from O
the O
store O
. O
To O
bypass O
Google B-System
Play I-System
Store I-System
security O
checks O
, O
the O
malware O
creators O
used O
a O
very O
interesting O
method O
: O
they O
uploaded O
a O
clean O
app O
to O
the O
store O
at O
the O
end O
of O
March O
, O
2017 O
, O
and O
would O
then O
update O
it O
with O
a O
malicious O
version O
for O
short O
period O
of O
time O
. O
Usually O
they O
would O
upload O
a O
clean O
version O
back O
on O
Google B-System
Play I-System
the O
very O
same O
day O
. O
They O
did O
this O
at O
least O
5 O
times O
between O
18 O
April O
and O
15 O
May O
. O
All O
the O
malicious O
Dvmap B-Malware
apps O
had O
the O
same O
functionality O
. O
They O
decrypt O
several O
archive O
files O
from O
the O
assets O
folder O
of O
the O
installation O
package O
, O
and O
launch O
an O
executable O
file O
from O
them O
with O
the O
name O
“ O
start. O
” O
The O
interesting O
thing O
is O
that O
the O
Trojan O
supports O
even O
the O
64-bit O
version O
of O
Android B-System
, O
which O
is O
very O
rare O
. O
All O
encrypted O
archives O
can O
be O
divided O
into O
two O
groups O
: O
the O
first O
comprises O
Game321.res B-Indicator
, O
Game322.res B-Indicator
, O
Game323.res B-Indicator
and O
Game642.res B-Indicator
– O
and O
these O
are O
used O
in O
the O
initial O
phase O
of O
infection O
, O
while O
the O
second O
group O
: O
Game324.res B-Indicator
and O
Game644.res B-Indicator
, O
are O
used O
in O
the O
main O
phase O
. O
Initial O
phase O
During O
this O
phase O
, O
the O
Trojan O
tries O
to O
gain O
root O
rights O
on O
the O
device O
and O
to O
install O
some O
modules O
. O
All O
archives O
from O
this O
phase O
contain O
the O
same O
files O
except O
for O
one O
called O
“ O
common O
” O
. O
This O
is O
a O
local O
root O
exploit O
pack O
, O
and O
the O
Trojan O
uses O
4 O
different O
exploit O
pack O
files O
, O
3 O
for O
32-bit O
systems O
and O
1 O
for O
64-bit-systems O
. O
If O
these O
files O
successfully O
gain O
root O
rights O
, O
the O
Trojan O
will O
install O
several O
tools O
into O
the O
system O
. O
It O
will O
also O
install O
the O
malicious O
app O
“ O
com.qualcmm.timeservices. B-Indicator
” O
These O
archives O
contain O
the O
file O
“ O
.root.sh B-Indicator
” O
which O
has O
some O
comments O
in O
Chinese O
: O
Main O
phase O
In O
this O
phase O
, O
the O
Trojan O
launches O
the O
“ O
start O
” O
file O
from O
Game324.res B-Indicator
or O
Game644.res B-Indicator
. O
It O
will O
check O
the O
version O
of O
Android B-System
installed O
and O
decide O
which O
library O
should O
be O
patched O
. O
For O
Android B-System
4.4.4 I-System
and O
older O
, O
the O
Trojan O
will O
patch O
method O
_Z30dvmHeapSourceStartupBeforeForkv O
from O
libdvm.so B-Indicator
, O
and O
for O
Android B-System
5 O
and O
newer O
it O
will O
patch O
method O
nativeForkAndSpecialize O
from O
libandroid_runtime.so B-Indicator
. O
Both O
of O
these O
libraries O
are O
runtime O
libraries O
related O
to O
Dalvik B-System
and O
ART B-System
runtime O
environments O
. O
Before O
patching O
, O
the O
Trojan O
will O
backup O
the O
original O
library O
with O
a O
name O
bak_ O
{ O
original O
name O
} O
. O
During O
patching O
, O
the O
Trojan O
will O
overwrite O
the O
existing O
code O
with O
malicious O
code O
so O
that O
all O
it O
can O
do O
is O
execute O
/system/bin/ip B-Indicator
. O
This O
could O
be O
very O
dangerous O
and O
cause O
some O
devices O
to O
crash O
following O
the O
overwrite O
. O
Then O
the O
Trojan O
will O
put O
the O
patched O
library O
back O
into O
the O
system O
directory O
. O
After O
that O
, O
the O
Trojan O
will O
replace O
the O
original O
/system/bin/ip B-Indicator
with O
a O
malicious O
one O
from O
the O
archive O
( O
Game324.res B-Indicator
or O
Game644.res B-Indicator
) O
. O
In O
doing O
so O
, O
the O
Trojan O
can O
be O
sure O
that O
its O
malicious O
module O
will O
be O
executed O
with O
system O
rights O
. O
But O
the O
malicious O
ip O
file O
does O
not O
contain O
any O
methods O
from O
the O
original O
ip O
file O
. O
This O
means O
that O
all O
apps O
that O
were O
using O
this O
file O
will O
lose O
some O
functionality O
or O
even O
start O
crashing O
. O
Malicious O
module O
“ O
ip O
” O
This O
file O
will O
be O
executed O
by O
the O
patched O
system O
library O
. O
It O
can O
turn O
off O
“ O
VerifyApps O
” O
and O
enable O
the O
installation O
of O
apps O
from O
3rd O
party O
stores O
by O
changing O
system O
settings O
. O
Furthermore O
, O
it O
can O
grant O
the O
“ O
com.qualcmm.timeservices B-Indicator
” O
app O
Device O
Administrator O
rights O
without O
any O
interaction O
with O
the O
user O
, O
just O
by O
running O
commands O
. O
It O
is O
a O
very O
unusual O
way O
to O
get O
Device O
Administrator O
rights O
. O
Malicious O
app O
com.qualcmm.timeservices B-Indicator
As O
I O
mentioned O
before O
, O
in O
the O
“ O
initial O
phase O
” O
, O
the O
Trojan O
will O
install O
the O
“ O
com.qualcmm.timeservices B-Indicator
” O
app O
. O
Its O
main O
purpose O
is O
to O
download O
archives O
and O
execute O
the O
“ O
start O
” O
binary O
from O
them O
. O
During O
the O
investigation O
, O
this O
app O
was O
able O
to O
successfully O
connect O
to O
the O
command O
and O
control O
server O
, O
but O
it O
received O
no O
commands O
. O
So O
I O
don O
’ O
t O
know O
what O
kind O
of O
files O
will O
be O
executed O
, O
but O
they O
could O
be O
malicious O
or O
advertising O
files O
. O
Conclusions O
This O
Trojan O
was O
distributed O
through O
the O
Google B-System
Play I-System
Store I-System
and O
uses O
a O
number O
of O
very O
dangerous O
techniques O
, O
including O
patching O
system O
libraries O
. O
It O
installs O
malicious O
modules O
with O
different O
functionality O
into O
the O
system O
. O
It O
looks O
like O
its O
main O
purpose O
is O
to O
get O
into O
the O
system O
and O
execute O
downloaded O
files O
with O
root O
rights O
. O
But O
I O
never O
received O
such O
files O
from O
their O
command O
and O
control O
server O
. O
These O
malicious O
modules O
report O
to O
the O
attackers O
about O
every O
step O
they O
are O
going O
to O
make O
. O
So O
I O
think O
that O
the O
authors O
are O
still O
testing O
this O
malware O
, O
because O
they O
use O
some O
techniques O
which O
can O
break O
the O
infected O
devices O
. O
But O
they O
already O
have O
a O
lot O
of O
infected O
users O
on O
whom O
to O
test O
their O
methods O
. O
I O
hope O
that O
by O
uncovering O
this O
malware O
at O
such O
an O
early O
stage O
, O
we O
will O
be O
able O
to O
prevent O
a O
massive O
and O
dangerous O
attack O
when O
the O
attackers O
are O
ready O
to O
actively O
use O
their O
methods O
. O
MD5 O
43680D1914F28E14C90436E1D42984E2 B-Indicator
20D4B9EB9377C499917C4D69BF4CCEBE B-Indicator
First O
widely O
distributed O
Android B-System
bootkit O
Malware O
infects O
more O
than O
350,000 O
Devices O
January O
29 O
, O
2014 O
In O
the O
last O
quarter O
of O
2013 O
, O
sale O
of O
a O
Smartphone O
with O
ANDROID B-System
operating O
system O
has O
increased O
and O
every O
second O
person O
you O
see O
is O
a O
DROID B-System
user O
. O
A O
Russian O
security O
firm O
'Doctor O
Web B-Organization
' O
identified O
the O
first O
mass O
distributed O
Android B-System
bootkit O
malware O
called O
'Android.Oldboot O
' O
, O
a O
piece O
of O
malware O
that O
's O
designed O
to O
re-infect O
devices O
after O
reboot O
, O
even O
if O
you O
delete O
all O
working O
components O
of O
it O
. O
The O
bootkit O
Android.Oldboot B-Malware
has O
infected O
more O
than O
350,000 O
android B-System
users O
in O
China O
, O
Spain O
, O
Italy O
, O
Germany O
, O
Russia O
, O
Brazil O
, O
the O
USA O
and O
some O
Southeast O
Asian O
countries O
. O
China O
seems O
to O
a O
mass O
victim O
of O
this O
kind O
of O
malware O
having O
a O
92 O
% O
share O
. O
A O
Bootkit O
is O
a O
rootkit O
malware O
variant O
which O
infects O
the O
device O
at O
start-up O
and O
may O
encrypt O
disk O
or O
steal O
data O
, O
remove O
the O
application O
, O
open O
connection O
for O
Command O
and O
controller O
. O
A O
very O
unique O
technique O
is O
being O
used O
to O
inject O
this O
Trojan O
into O
an O
Android B-System
system O
where O
an O
attacker O
places O
a O
component O
of O
it O
into O
the O
boot O
partition O
of O
the O
file O
system O
and O
modify O
the O
'init O
' O
script O
( O
initialize O
the O
operating O
system O
) O
to O
re-load O
the O
malware O
as O
you O
switch O
on O
your O
android B-System
. O
When O
you O
start O
your O
device O
, O
this O
script O
loads O
the O
Trojan O
'imei_chk O
' O
( O
detects O
it O
as O
Android.Oldboot.1 B-Indicator
) O
which O
extract O
two O
files O
libgooglekernel.so B-Indicator
( O
Android.Oldboot.2 B-Indicator
) O
and O
GoogleKernel.apk B-Indicator
( O
Android.Oldboot.1.origin B-Indicator
) O
, O
copy O
them O
respectively O
in O
/system/lib B-Indicator
and I-Indicator
/system/app I-Indicator
. O
Android.Oldboot B-Malware
acts O
as O
a O
system O
service O
and O
connects O
to O
the O
command-and-controller O
server O
using O
libgooglekernel.so B-Indicator
library O
and O
receives O
commands O
to O
download O
, O
remove O
installed O
apps O
, O
and O
install O
malicious O
apps O
. O
Since O
it O
becomes O
a O
part O
of O
the O
boot O
partition O
, O
formatting O
the O
device O
will O
not O
solve O
the O
problem O
. O
The O
researchers O
believe O
that O
the O
devices O
somehow O
had O
the O
malware O
pre-loaded O
at O
the O
time O
of O
shipping O
from O
the O
manufacturer O
, O
or O
was O
likely O
distributed O
inside O
modified O
Android B-System
firmware O
. O
So O
, O
users O
should O
beware O
of O
certain O
modified O
Android B-System
firmware O
. O
Two O
weeks O
ago O
, O
Some O
Chinese O
Security O
Researchers O
have O
also O
detected O
a O
bootkit O
called O
'Oldboot O
' O
, O
possibly O
the O
same O
malware O
or O
another O
variant O
of O
it O
. O
" O
Due O
to O
the O
special O
RAM O
disk O
feature O
of O
Android B-System
devices O
' O
boot O
partition O
, O
all O
current O
mobile O
antivirus O
products O
in O
the O
world O
ca O
n't O
completely O
remove O
this O
Trojan O
or O
effectively O
repair O
the O
system O
. O
'' O
" O
According O
to O
our O
statistics O
, O
as O
of O
today O
, O
there O
're O
more O
than O
500 O
, O
000 O
Android B-System
devices O
infected O
by O
this O
bootkit O
in O
China O
in O
last O
six O
months O
. O
The O
Android B-System
malware O
Android.Oldboot B-Malware
is O
almost O
impossible O
to O
remove O
, O
not O
even O
with O
formatting O
your O
device O
. O
But O
if O
your O
device O
is O
not O
from O
a O
Chinese O
manufacturer O
, O
then O
chances O
that O
you O
are O
a O
victim O
of O
it O
, O
are O
very O
less O
. O
This O
bootkit O
is O
not O
the O
first O
of O
this O
kind O
. O
Two O
years O
back O
, O
in O
the O
month O
of O
March O
we O
reported O
, O
NQ B-Organization
Mobile I-Organization
Security I-Organization
Research O
Center O
uncovered O
the O
world O
's O
first O
Android B-System
bootkit O
malware O
called O
'DKFBootKit O
' O
, O
that O
replaces O
certain O
boot O
processes O
and O
can O
begin O
running O
even O
before O
the O
system O
is O
completely O
booted O
up O
. O
But O
Android.Oldboot B-Malware
malware O
is O
a O
bit O
more O
dangerous O
because O
even O
if O
you O
remove O
all O
working O
components O
of O
it O
from O
your O
android B-System
successfully O
, O
the O
component O
imei_chk B-Indicator
will O
persist O
in O
a O
protected O
boot O
memory O
area O
and O
hence O
will O
reinstall O
itself O
on O
next O
boot O
and O
continuously O
infect O
the O
Smartphone O
. O
Users O
are O
recommended O
to O
install O
apps O
from O
authorized O
stores O
such O
as O
Google B-System
Play I-System
, O
disable O
installation O
of O
apps O
from O
'Unknown O
Sources O
' O
and O
for O
a O
better O
security O
install O
a O
reputed O
security O
application O
. O
You O
can O
also O
try O
to O
re-flash O
your O
device O
with O
its O
original O
ROM O
. O
After O
flashing O
, O
the O
bootkit O
will O
be O
removed O
. O
FrozenCell B-Malware
: O
Multi-Platform O
Surveillance O
Campaign O
Against O
Palestinians O
October O
5 O
, O
2017 O
FrozenCell B-Malware
has O
been O
seen O
masquerading O
as O
various O
well O
known O
social O
media O
and O
chat O
applications O
as O
well O
as O
an O
app O
likely O
only O
used O
by O
Palestinian O
or O
Jordanian O
students O
sitting O
their O
2016 O
general O
exams O
. O
Lookout B-Organization
researchers O
have O
discovered O
a O
new O
mobile O
surveillanceware O
family O
, O
FrozenCell B-Malware
. O
The O
threat O
is O
likely O
targeting O
employees O
of O
various O
Palestinian O
government O
agencies O
, O
security O
services O
, O
Palestinian O
students O
, O
and O
those O
affiliated O
with O
the O
Fatah B-Organization
political O
party O
. O
FrozenCell B-Malware
is O
the O
mobile O
component O
of O
a O
multi-platform O
attack O
we O
've O
seen O
a O
threat O
actor O
known O
as O
" O
Two-tailed B-Malware
Scorpion/APT-C-23 I-Malware
, O
'' O
use O
to O
spy O
on O
victims O
through O
compromised O
mobile O
devices O
and O
desktops O
. O
The O
desktop O
components O
of O
this O
attack O
, O
previously O
discovered O
by O
Palo B-Organization
Alto I-Organization
Network I-Organization
, O
are O
known O
as O
KasperAgent B-Malware
and O
Micropsia B-Malware
. O
We O
discovered O
561MB O
of O
exfiltrated O
data O
from O
24 O
compromised O
Android B-System
devices O
while O
investigating O
this O
threat O
. O
More O
data O
is O
appearing O
daily O
, O
leading O
us O
to O
believe O
the O
actors O
are O
still O
highly O
active O
. O
We O
are O
continuing O
to O
watch O
it O
closely O
. O
This O
threat O
is O
another O
proof O
point O
that O
attackers O
are O
clearly O
incorporating O
the O
mobile O
device O
into O
their O
surveillance O
campaigns O
as O
a O
primary O
attack O
vector O
. O
Government O
agencies O
and O
enterprises O
should O
look O
at O
this O
threat O
as O
an O
example O
of O
the O
kind O
of O
spying O
that O
is O
now O
possible O
given O
how O
ubiquitous O
mobile O
devices O
are O
in O
the O
workplace O
. O
Attackers O
are O
keenly O
aware O
of O
the O
information O
they O
can O
derive O
from O
these O
devices O
and O
are O
using O
multi-stage O
( O
phishing O
+ O
an O
executable O
) O
, O
multi-platform O
( O
Android B-System
+ O
desktop O
) O
attacks O
to O
accomplish O
their O
spying O
. O
All O
Lookout B-Organization
customers O
are O
protected O
from O
this O
threat O
. O
What O
it O
does O
FrozenCell B-Malware
masquerades O
as O
fake O
updates O
to O
chat O
applications O
like O
Facebook B-System
, O
WhatsApp B-System
, O
Messenger B-System
, O
LINE B-System
, O
and O
LoveChat B-System
. O
We O
also O
detected O
it O
in O
apps O
targeted O
toward O
specific O
Middle O
Eastern O
demographics O
. O
For O
example O
, O
the O
actors O
behind O
FrozenCell B-Malware
used O
a O
spoofed O
app O
called O
Tawjihi B-Indicator
2016 I-Indicator
, O
which O
Jordanian O
or O
Palestinian O
students O
would O
ordinarily O
use O
during O
their O
general O
secondary O
examination O
. O
Once O
installed O
on O
a O
device O
FrozenCell B-Malware
is O
capable O
of O
: O
Recording O
calls O
Retrieving O
generic O
phone O
metadata O
( O
e.g. O
, O
cell O
location O
, O
mobile O
country O
code O
, O
mobile O
network O
code O
) O
Geolocating O
a O
device O
Extracting O
SMS O
messages O
Retrieving O
a O
victim O
's O
accounts O
Exfiltrating O
images O
Downloading O
and O
installing O
additional O
applications O
Searching O
for O
and O
exfiltrating O
pdf O
, O
doc O
, O
docx O
, O
ppt O
, O
pptx O
, O
xls O
, O
and O
xlsx O
file O
types O
Retrieving O
contacts O
The O
graph O
below O
represents O
a O
split O
of O
the O
types O
of O
data O
from O
only O
one O
misconfigured O
command O
and O
control O
server O
( O
out O
of O
over O
37 O
servers O
) O
. O
This O
is O
only O
a O
small O
picture O
of O
the O
threat O
actor O
's O
operations O
. O
Split O
of O
exfiltrated O
data O
Some O
noteworthy O
files O
identified O
in O
content O
taken O
from O
compromised O
devices O
include O
passport O
photos O
, O
audio O
recordings O
of O
calls O
, O
other O
images O
, O
and O
a O
PDF O
document O
with O
data O
on O
484 O
individuals O
. O
The O
PDF O
lists O
dates O
of O
birth O
, O
gender O
, O
passport O
numbers O
, O
and O
names O
. O
Potential O
targets O
The O
actors O
behind O
FrozenCell B-Malware
used O
an O
online O
service O
that O
geolocates O
mobile O
devices O
based O
on O
nearby O
cell O
towers O
to O
track O
targets O
. O
This O
data O
shows O
a O
distinct O
concentration O
of O
infected O
devices O
beaconing O
from O
Gaza O
, O
Palestine O
. O
Map O
of O
potential O
targets O
Early O
samples O
of O
FrozenCell B-Malware
used O
an O
online O
service O
for O
storing O
geolocation O
information O
of O
infected O
devices O
. O
Analysis O
of O
this O
telemetry O
shows O
infected O
devices O
are O
completely O
based O
in O
Gaza O
, O
Palestine O
. O
It O
has O
not O
been O
confirmed O
whether O
these O
are O
from O
test O
devices O
or O
the O
devices O
of O
victims O
. O
We O
were O
also O
able O
to O
link O
the O
FrozenCell B-Malware
's O
Android B-System
infrastructure O
to O
numerous O
desktop O
samples O
that O
are O
part O
of O
the O
larger O
multi-platform O
attack O
. O
It O
appears O
the O
attackers O
sent O
malicious O
executables O
though O
phishing O
campaigns O
impersonating O
individuals O
associated O
with O
the O
Palestinian B-Organization
Security I-Organization
Services I-Organization
, O
the O
General B-Organization
Directorate I-Organization
of I-Organization
Civil I-Organization
Defence I-Organization
- O
Ministry B-Organization
of I-Organization
the I-Organization
Interior I-Organization
, O
and O
the O
7th O
Fateh O
Conference O
of O
the O
Palestinian B-Organization
National I-Organization
Liberation I-Organization
Front I-Organization
( O
held O
in O
late O
2016 O
) O
. O
The O
titles O
and O
contents O
of O
these O
files O
suggest O
that O
the O
actor O
targeted O
individuals O
affiliated O
with O
these O
government O
agencies O
and O
the O
Fatah B-Organization
political O
party O
. O
Some O
malicious O
files O
associated O
with O
these O
samples O
were O
titled O
the O
following O
: O
Council_of_ministres_decision O
Minutes O
of O
the O
Geneva O
Meeting O
on O
Troops O
Summary O
of O
today O
's O
meetings.doc.exe B-Indicator
The O
most O
important O
points O
of O
meeting O
the O
memory O
of O
the O
late O
President O
Abu O
Omar O
may O
Allah O
have O
mercy O
on O
him O
- O
Paper O
No O
. O
1 O
Fadi O
Alsalamin O
scandal O
with O
an O
Israeli O
officer O
- O
exclusive O
- O
watched O
before O
the O
deletion O
- O
Fadi O
Elsalameen O
The O
details O
of O
the O
assassination O
of O
President O
Arafat_06-12-2016_docx O
Quds.rar B-Indicator
Many O
of O
these O
executables O
are O
associated O
with O
various O
short O
links O
created O
using O
Bit.ly B-System
, O
a O
URL O
shortening O
service O
. O
After O
analyzing O
the O
traffic O
associated O
with O
these O
short O
links O
, O
we O
determined O
that O
each O
one O
was O
associated O
with O
a O
referral O
path O
from O
mail.mosa.pna.ps B-Indicator
. O
MOSA B-Organization
is O
the O
Palestinian O
Directorate O
of O
Social O
Development O
whose O
mandate O
is O
to O
achieve O
comprehensive O
development O
, O
social O
security O
, O
and O
economic O
growth O
for O
Palestinian O
families O
, O
according O
to O
publicly O
available O
information O
on O
this O
ministry O
. O
Infrastructure O
At O
the O
time O
of O
writing O
the O
following O
domains O
have O
either O
been O
used O
by O
this O
family O
or O
are O
currently O
active O
. O
We O
expect O
this O
list O
to O
grow O
given O
that O
this O
actor O
has O
changed O
its O
infrastructure O
numerous O
times O
in O
2017 O
. O
cecilia-gilbert B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
comgooogel I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
orgmary-crawley I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
commydriveweb I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
comrose-sturat I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
infokalisi I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
xyzdebra-morgan I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
comarnani I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
infoacount-manager I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
infogooogel-drive I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
commediauploader I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
meacount-manager I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
netupload404 I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
clubupload999 I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
infoal-amalhumandevelopment I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
commargaery I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
coupload202 I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
comgo-mail-accounts I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
comupload101 I-Indicator
[ B-Indicator
. I-Indicator
] I-Indicator
netsybil-parks I-Indicator
[ O
. O
] O
infodavos-seaworth O
[ O
. O
] O
infoupload999 O
[ O
. O
] O
orgacount-manager O
[ O
. O
] O
comlila-tournai O
[ O
. O
] O
comaccount-manager O
[ O
. O
] O
orgmediauploader O
[ O
. O
] O
infokalisi O
[ O
. O
] O
orgaryastark O
[ O
. O
] O
infomavis-dracula O
[ O
. O
] O
comkalisi O
[ O
. O
] O
infogoogle-support-team O
[ O
. O
] O
com9oo91e O
[ O
. O
] O
comuseraccount O
[ O
. O
] O
websiteaccounts-fb B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
comakashipro I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
comfeteh-asefa I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
comlagertha-lothbrok I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
info I-Indicator
OpSec O
fails O
and O
use O
of O
cryptography O
While O
looking O
at O
this O
infrastructure O
, O
we O
identified O
that O
one O
of O
these O
domains O
has O
directory O
indexing O
enabled O
. O
This O
mistake O
in O
operational O
security O
allowed O
us O
to O
gain O
visibility O
into O
exfiltrated O
content O
for O
a O
number O
of O
devices O
. O
Continued O
mirroring O
suggests O
it O
is O
likely O
a O
regularly O
cleaned O
staging O
server O
. O
We O
sourced O
the O
over O
561MB O
of O
exfiltrated O
data O
from O
this O
domain O
alone O
, O
all O
of O
which O
we O
found O
to O
be O
7z O
compressed O
and O
password O
protected O
. O
Password O
generation O
for O
compressed O
files O
takes O
place O
client-side O
with O
each O
device O
using O
a O
unique O
key O
in O
most O
scenarios O
. O
Key O
information O
consists O
of O
an O
MD5 O
hash O
of O
the O
device O
's O
Android B-System
ID O
, O
the O
device O
manufacturer O
, O
and O
the O
device O
model O
with O
each O
separated O
by O
an O
underscore O
. O
Visually O
, O
this O
can O
be O
represented O
as O
follows O
: O
Android B-System
ID O
When O
combined O
with O
our O
analysis O
of O
indexed O
directories O
on O
C2 O
infrastructure O
, O
we O
were O
able O
to O
easily O
automate O
the O
generation O
of O
the O
password O
used O
by O
each O
device O
and O
, O
in O
turn O
, O
successfully O
decompress O
all O
exfiltrated O
content O
from O
compromised O
devices O
. O
Indexed O
directories O
on O
C2 O
infrastructure O
While O
exfiltrated O
content O
is O
encrypted O
, O
information O
used O
to O
generate O
the O
password O
is O
plainly O
visible O
in O
the O
top O
level O
directories O
for O
each O
device O
. O
Taking O
this O
information O
from O
directory O
listings O
, O
like O
the O
one O
shown O
above O
, O
allowed O
for O
the O
decryption O
of O
all O
content O
. O
In O
this O
case O
, O
FrozenCell B-Malware
has O
primarily O
netted O
the O
actors O
behind O
it O
with O
recorded O
outbound O
calls O
followed O
closely O
by O
images O
and O
recorded O
incoming O
calls O
. O
FrozenCell B-Malware
is O
part O
of O
a O
very O
successful O
, O
multi-platform O
surveillance O
campaign O
. O
Attackers O
are O
growing O
smarter O
, O
targeting O
individuals O
through O
the O
devices O
and O
the O
services O
they O
use O
most O
. O
Government O
agencies O
and O
enterprises O
should O
plan O
to O
be O
hit O
from O
all O
angles O
- O
cloud O
services O
, O
mobile O
devices O
, O
laptops O
- O
in O
order O
to O
build O
comprehensive O
security O
strategies O
that O
work O
. O
TUESDAY O
, O
MAY O
19 O
, O
2020 O
The O
wolf O
is O
back O
... O
NEWS O
SUMMARY O
Thai O
Android B-System
devices O
and O
users O
are O
being O
targeted O
by O
a O
modified O
version O
of O
DenDroid B-Malware
we O
are O
calling O
" O
WolfRAT B-Malware
, O
'' O
now O
targeting O
messaging O
apps O
like O
WhatsApp B-System
, O
Facebook B-System
Messenger I-System
and O
Line B-System
. O
We O
assess O
with O
high O
confidence O
that O
this O
modified O
version O
is O
operated O
by O
the O
infamous O
Wolf B-Organization
Research I-Organization
. O
This O
actor O
has O
shown O
a O
surprising O
level O
of O
amateur O
actions O
, O
including O
code O
overlaps O
, O
open-source O
project O
copy/paste O
, O
classes O
never O
being O
instanced O
, O
unstable O
packages O
and O
unsecured O
panels O
. O
EXECUTIVE O
SUMMARY O
Cisco B-Organization
Talos I-Organization
has O
discovered O
a O
new O
Android O
malware O
based O
on O
a O
leak O
of O
the O
DenDroid B-Malware
malware O
family O
. O
We O
named O
this O
malware O
" O
WolfRAT B-Malware
'' O
due O
to O
strong O
links O
between O
this O
malware O
( O
and O
the O
command O
and O
control O
( O
C2 O
) O
infrastructure O
) O
and O
Wolf B-Organization
Research I-Organization
, O
an O
infamous O
organization O
that O
developed O
interception O
and O
espionage-based O
malware O
and O
was O
publicly O
described O
by O
CSIS O
during O
Virus O
Bulletin O
2018 O
. O
We O
identified O
infrastructure O
overlaps O
and O
string O
references O
to O
previous O
Wolf B-Organization
Research I-Organization
work O
. O
The O
organization O
appears O
to O
be O
shut O
down O
, O
but O
the O
threat O
actors O
are O
still O
very O
active O
. O
We O
identified O
campaigns O
targeting O
Thai O
users O
and O
their O
devices O
. O
Some O
of O
the O
C2 O
servers O
are O
located O
in O
Thailand O
. O
The O
panels O
also O
contain O
Thai O
JavaScript O
comments O
and O
the O
domain O
names O
also O
contain O
references O
to O
Thai O
food O
, O
a O
tactic O
commonly O
employed O
to O
entice O
users O
to O
click/visit O
these O
C2 O
panels O
without O
much O
disruption O
. O
We O
identified O
a O
notable O
lack O
of O
sophistication O
in O
this O
investigation O
such O
as O
copy/paste O
, O
unstable O
code O
, O
dead O
code O
and O
panels O
that O
are O
freely O
open O
. O
What O
's O
new O
? O
WolfRAT B-Malware
is O
based O
on O
a O
previously O
leaked O
malware O
named O
DenDroid B-Malware
. O
The O
new O
malware O
appears O
to O
be O
linked O
to O
the O
infamous O
Wolf B-Organization
Research I-Organization
organization O
and O
targets O
Android B-System
devices O
located O
in O
Thailand O
. O
How O
did O
it O
work O
? O
The O
malware O
mimics O
legit O
services O
such O
as O
Google B-Organization
service O
, O
GooglePlay B-System
or O
Flash B-System
update O
. O
The O
malware O
is O
not O
really O
advanced O
and O
is O
based O
on O
a O
lot O
of O
copy/paste O
from O
public O
sources O
available O
on O
the O
Internet O
. O
The O
C2 O
infrastructure O
contains O
a O
lack O
of O
sophistication O
such O
as O
open O
panels O
, O
reuse O
of O
old O
servers O
publicly O
tagged O
as O
malicious… O
So O
what O
? O
After O
being O
publicly O
denounced O
by O
CSIS B-Organization
Group I-Organization
— O
a O
threat O
intelligence O
company O
in O
Denmark O
— O
Wolf B-Organization
Research I-Organization
was O
closed O
and O
a O
new O
organization O
named O
LokD B-Organization
was O
created O
. O
This O
new O
organization O
seems O
to O
work O
on O
securing O
Android B-Organization
devices O
. O
However O
, O
thanks O
to O
the O
infrastructure O
sharing O
and O
forgotten O
panel O
names O
, O
we O
assess O
with O
high O
confidence O
that O
this O
actor O
is O
still O
active O
, O
it O
is O
still O
developing O
malware O
and O
has O
been O
using O
it O
from O
mid-June O
to O
today O
. O
On O
the O
C2 O
panel O
, O
we O
found O
a O
potential O
link O
between O
Wolf B-Organization
Research I-Organization
and O
another O
Cyprus O
organization O
named O
Coralco B-Organization
Tech I-Organization
. O
This O
organization O
is O
also O
working O
on O
interception O
technology O
. O
LINKS O
TO O
WOLF O
INTELLIGENCE O
During O
the O
Virus O
Bulletin O
conference O
in O
2018 O
, O
CSIS B-Organization
researchers O
Benoît O
Ancel O
and O
Aleksejs O
Kuprins O
did O
a O
presentation O
on O
Wolf B-Organization
Research I-Organization
and O
the O
offensive O
arsenal O
developed O
by O
the O
organization O
. O
They O
mentioned O
an O
Android B-System
, O
iOS B-System
and O
Windows B-System
remote O
access O
tool O
( O
RAT O
) O
. O
Their O
findings O
showed O
that O
Wolf O
is O
headquartered O
in O
Germany O
with O
offices O
in O
Cyprus O
, O
Bulgaria O
, O
Romania O
, O
India O
and O
( O
possibly O
) O
the O
U.S O
. O
The O
organization O
was O
closed O
after O
the O
CSIS B-Organization
presentation O
. O
However O
, O
the O
director O
created O
a O
new O
organization O
in O
Cyprus O
named O
LokD B-Organization
. O
This O
new O
organization O
proposed O
the O
creation O
of O
a O
more O
secure O
Android B-System
phone O
. O
Based O
on O
the O
organization O
website O
, O
it O
also O
proposes O
services O
and O
developed O
zero-day B-Vulnerability
vulnerabilities I-Vulnerability
to O
test O
their O
own O
products O
: O
Zero-day O
research O
from O
lokd.com B-Organization
We O
can O
see O
that O
the O
organization O
owner O
still O
has O
an O
interest O
in O
Android B-System
devices O
. O
Based O
on O
infrastructure O
overlaps O
and O
leaked O
information O
, O
we O
assess O
with O
high O
confidence O
that O
the O
malware O
we O
identified O
and O
present O
in O
this O
paper O
is O
linked O
to O
Wolf B-Organization
Research I-Organization
. O
One O
of O
the O
samples O
( O
e19823a1ba4a0e40cf459f4a0489fc257720cc0d71ecfb7ad94b3ca86fbd85d1 B-Indicator
) O
uses O
the O
C2 O
server O
svcws B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ponethus I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
. O
Based O
on O
our O
research O
and O
Benoît O
Ancel O
's O
tracker O
, O
this O
C2 O
was O
used O
by O
Wolf B-Organization
Intelligence I-Organization
: O
Additionally O
, O
we O
identified O
two O
empty O
panels O
on O
a O
C2 O
server O
. O
The O
new O
one O
with O
the O
title O
" O
Coralco O
Archimedes O
, O
'' O
and O
an O
older O
version O
with O
the O
title O
" O
Wolf O
Intelligence O
: O
'' O
New O
panel O
Old O
panel O
The O
new O
panel O
name O
contains O
" O
Coralco O
'' O
in O
its O
name O
. O
Coralco B-Organization
Tech I-Organization
is O
an O
organization O
located O
in O
Cyprus O
and O
providing O
interception O
tools O
. O
We O
can O
not O
say O
for O
sure O
if O
Wolf B-Organization
Research I-Organization
and O
Coralco B-Organization
Tech I-Organization
are O
linked O
, O
but O
this O
panel O
name O
, O
their O
offerings O
and O
the O
panel O
layout O
would O
suggest O
it O
should O
be O
considered O
suspiciously O
linked O
. O
Coralco O
Tech O
's O
services O
description O
. O
VICTIMOLOGY O
ON O
THE O
IDENTIFIED O
CAMPAIGNS O
The O
campaigns O
we O
analyzed O
targeted O
Android B-System
devices O
in O
Thailand O
. O
The O
C2 O
server O
domain O
is O
linked O
to O
Thai O
food O
: O
Nampriknum B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net I-Indicator
: O
Nam O
Phrik O
Num O
Somtum B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
: O
Som O
Tum O
We O
also O
identified O
comments O
in O
Thai O
on O
the O
C2 O
infrastructure O
mentioned O
in O
the O
previous O
chapter O
: O
MALWARE O
DenDroid B-Malware
The O
Android B-System
malware O
is O
based O
on O
the O
DenDroid B-Malware
Android O
malware O
. O
Several O
analysis O
reports O
were O
published O
on O
this O
malware O
in O
2014 O
and O
, O
finally O
, O
the O
source O
code O
was O
leaked O
in O
2015 O
. O
The O
original O
leak O
is O
no O
longer O
available O
on O
github.com O
, O
but O
a O
copy O
can O
be O
found O
here O
. O
The O
table O
below O
shows O
the O
commands O
available O
to O
the O
operator O
for O
tasking O
on O
infected O
devices O
. O
This O
malware O
is O
simplistic O
in O
comparison O
to O
some O
modern-day O
Android B-System
malware O
. O
The O
best O
example O
of O
that O
is O
that O
it O
does O
n't O
take O
advantage O
of O
the O
accessibility O
framework O
, O
collecting O
information O
on O
non-rooted O
devices O
. O
The O
commands O
are O
self-explanatory O
and O
show O
the O
features O
included O
in O
the O
malware O
. O
Some O
of O
them O
like O
takephoto O
, O
takevideo O
, O
recordaudio O
, O
getsentsms O
and O
uploadpictures O
are O
focused O
on O
espionage O
activities O
. O
Others O
like O
transferbot O
, O
promptupdate O
and O
promptuninstall O
are O
meant O
to O
help O
the O
operator O
manage O
the O
malware O
. O
Version O
# O
1 O
: O
June O
2019 O
— O
Domain O
: O
databit B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
During O
our O
investigation O
, O
we O
identified O
at O
least O
four O
major O
releases O
of O
the O
RAT O
. O
The O
permissions O
on O
the O
first O
version O
of O
the O
malware O
lay O
out O
the O
foundations O
of O
a O
spying O
trojan O
. O
Permissions O
The O
package O
name O
follows O
the O
original O
style O
name O
used O
on O
DenDroid B-Malware
. O
The O
code O
is O
obfuscated O
but O
not O
packed O
. O
This O
malware O
also O
contains O
a O
screen O
recorder O
. O
This O
feature O
is O
implemented O
using O
another O
open-source O
software O
package O
that O
can O
be O
found O
here O
. O
The O
service O
is O
implemented O
in O
the O
class O
com.serenegiant.service.ScreenRecorderService B-Indicator
which O
is O
declared O
in O
the O
package O
manifest O
. O
During O
our O
analysis O
of O
this O
sample O
, O
we O
did O
notice O
that O
the O
class O
itself O
is O
never O
called O
or O
used O
by O
the O
malware O
. O
It O
remains O
available O
within O
the O
source O
code O
but O
no O
method O
of O
use O
takes O
place O
. O
Version O
# O
2 O
: O
June O
- O
Aug. O
2019 O
— O
Domain O
: O
somtum B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
This O
is O
the O
first O
version O
that O
shows O
the O
code O
organization O
evolution O
that O
will O
continue O
to O
be O
used O
on O
all O
other O
functions O
throughout O
this O
malware O
. O
Code O
structure O
Obviously O
, O
this O
code O
is O
not O
obfuscated O
when O
compared O
with O
the O
previous O
version O
it O
becomes O
clear O
that O
this O
is O
the O
same O
code O
base O
. O
One O
of O
the O
first O
changes O
that O
stands O
out O
is O
that O
the O
screen O
recording O
feature O
mentioned O
in O
the O
previous O
sample O
has O
been O
removed O
. O
A O
new O
class O
was O
added O
called O
com.utils.RestClient B-Indicator
. O
This O
class O
is O
based O
on O
public O
code O
belonging O
to O
the O
package O
praeda.muzikmekan B-Indicator
, O
which O
can O
be O
found O
here O
among O
other O
places O
. O
Just O
like O
in O
previous O
examples O
, O
the O
malware O
author O
does O
not O
use O
this O
package O
. O
Missing O
permissions O
The O
lack O
of O
the O
READ_FRAME_BUFFER O
permission O
can O
be O
justified O
by O
the O
removal O
of O
the O
screen O
record O
feature O
. O
The O
ACCESS_SUPERUSER O
may O
have O
been O
removed O
because O
it O
was O
deprecated O
upon O
the O
release O
of O
Android B-System
5.0 I-System
Lollipop B-System
which O
happened O
in O
2014 O
. O
The O
reality O
is O
that O
the O
RAT O
permissions O
can O
be O
implemented O
just O
with O
the O
permissions O
declared O
on O
the O
manifest O
, O
thus O
there O
is O
no O
need O
for O
higher O
permissions O
. O
Version O
# O
3 O
: O
Sept. O
- O
Dec. O
2019 O
— O
Domain O
: O
ponethus B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
Given O
that O
there O
is O
some O
overlap O
in O
the O
previous O
two O
versions O
, O
it O
came O
as O
no O
surprise O
to O
us O
that O
we O
finally O
identified O
a O
sample O
which O
is O
an O
evolution O
based O
on O
both O
previous O
versions O
. O
This O
sample O
is O
clearly O
a O
mix O
between O
the O
two O
. O
This O
is O
also O
the O
first O
version O
where O
the O
package O
name O
changes O
into O
something O
that O
a O
less O
aware O
user O
may O
be O
tricked O
by O
, O
com.android.playup B-Indicator
. O
This O
version O
brings O
back O
the O
ACCESS_SUPERUSER O
and O
READ_FRAME_BUFFER O
permissions O
. O
However O
, O
this O
time O
, O
the O
permission O
is O
actually O
used O
. O
WhatsApp B-System
message O
capture O
The O
service O
com.serenegiant.service.ScreenRecorderService B-Indicator
, O
is O
invoked O
by O
the O
ScreenRecorderActivity O
. O
Upon O
creation O
, O
this O
activity O
launches O
a O
thread O
that O
will O
loop O
on O
a O
50-second O
interval O
. O
In O
the O
first O
iteration O
, O
the O
screen O
recording O
is O
started O
and O
will O
only O
stop O
when O
the O
RAT O
determines O
that O
WhatsApp B-System
is O
not O
running O
. O
It O
's O
restarted O
in O
the O
next O
cycle O
independently O
based O
on O
if O
WhatsApp B-System
is O
running O
. O
In O
this O
version O
, O
the O
developer O
added O
more O
classes O
from O
the O
same O
package O
. O
Even O
though O
we O
could O
not O
find O
indications O
of O
being O
in O
use O
, O
two O
stand O
out O
. O
Bluetooth O
— O
which O
allows O
the O
interaction O
with O
the O
Bluetooth O
interface O
, O
and O
net/deacon O
— O
which O
implements O
a O
beaconing O
system O
based O
on O
UDP O
. O
Android B-System
shell O
A O
new O
package O
was O
added O
that O
allows O
the O
execution O
of O
commands O
in O
the O
Android B-System
shell O
. O
Again O
, O
this O
package O
source O
code O
is O
publicly O
available O
and O
can O
be O
found O
here O
. O
One O
of O
the O
uses O
the O
malware O
gives O
to O
this O
package O
is O
the O
execution O
of O
the O
command O
" O
dumpsys O
'' O
to O
determine O
if O
certain O
activities O
are O
running O
. O
Check O
if O
chat O
apps O
are O
running O
In O
the O
above O
example O
, O
the O
malware O
is O
searching O
for O
Line O
, O
Facebook B-System
Messenger I-System
and O
WhatsApp B-System
activities O
. O
This O
is O
part O
of O
a O
class O
called O
CaptureService O
, O
which O
already O
existed O
in O
the O
previous O
version O
but O
it O
was O
not O
duly O
implemented O
. O
Previous O
version O
The O
capture O
service O
class O
implements O
the O
chat O
applications O
interception O
. O
Upon O
creation O
the O
class O
will O
start O
to O
take O
screenshots O
that O
will O
be O
stopped O
and O
uploaded O
to O
the O
C2 O
once O
the O
service O
ca O
n't O
find O
the O
targeted O
applications O
running O
. O
The O
core O
of O
this O
functionality O
is O
also O
based O
on O
an O
open-source O
project O
that O
can O
be O
found O
here O
. O
Another O
novelty O
is O
a O
VPN-related O
package O
, O
which O
is O
based O
on O
OrbotVPN B-System
. O
Once O
again O
, O
it O
does O
n't O
seem O
to O
actually O
be O
in O
use O
. O
The O
same O
happens O
with O
the O
package O
squareup.otto B-Indicator
, O
which O
is O
an O
open-source O
bus O
implementation O
focused O
on O
Android B-System
implementation O
. O
Both O
sources O
can O
be O
found O
here O
and O
here O
. O
Version O
# O
4 O
: O
April O
2020 O
— O
Domain O
: O
nampriknum.net B-Indicator
Following O
the O
same O
pattern O
, O
this O
version O
has O
some O
added O
features O
and O
others O
, O
which O
were O
not O
in O
use O
, O
removed O
. O
First O
of O
all O
the O
new O
package O
name O
is O
com.google.services B-Indicator
, O
which O
can O
easily O
be O
confused O
with O
a O
legitimate O
Google B-Organization
service O
. O
The O
VPN O
package O
is O
no O
longer O
present O
, O
further O
reinforcing O
our O
conclusion O
that O
it O
was O
not O
in O
use O
. O
WolfRAT B-Malware
application O
screen O
The O
Google B-System
GMS I-System
and O
Firebase B-System
service O
has O
been O
added O
, O
however O
, O
no O
configuration O
has O
been O
found O
, O
even O
though O
services O
seem O
to O
be O
referenced O
in O
the O
of O
a O
new O
class O
. O
The O
new O
class O
is O
called O
NotificationListener O
and O
extends O
the O
NotificationListenerService O
class O
. O
This O
would O
allow O
the O
RAT O
to O
receive O
system O
notifications O
. O
Notification O
handling O
method O
The O
class O
is O
only O
implemented O
in O
debug O
mode O
, O
pushing O
all O
captured O
information O
into O
the O
log O
. O
The O
usage O
of O
the O
PlusShare B-System
API O
in O
2020 O
denotes O
some O
unprofessional O
development O
, O
since O
this O
is O
the O
API O
to O
access O
Google+ B-Organization
. O
This O
service O
, O
along O
with O
the O
API O
, O
was O
fully O
decommissioned O
in O
March O
2019 O
. O
This O
version O
adds O
one O
significant O
class O
— O
it O
requests O
DEVICE_ADMIN O
privileges O
. O
Device O
admin O
policies O
Looking O
at O
the O
policy O
's O
definition O
, O
we O
can O
see O
that O
it O
lists O
all O
the O
available O
policies O
even O
if O
most O
of O
them O
are O
deprecated O
on O
Android B-System
10.0 I-System
and O
their O
usage O
results O
in O
a O
security O
exception O
. O
The O
code O
implementation O
again O
seems O
that O
it O
has O
been O
added O
for O
testing O
purposes O
only O
. O
Versions O
overview O
The O
DenDroid B-Malware
code O
base O
was O
kept O
to O
such O
an O
extent O
that O
even O
the O
original O
base64-encoded O
password O
was O
kept O
. O
Original O
password O
The O
main O
service O
follows O
the O
same O
structure O
as O
the O
first O
version O
, O
the O
anti-analysis O
features O
are O
primitive O
, O
only O
checking O
the O
emulator O
environment O
without O
any O
kind O
of O
packing O
or O
obfuscation O
. O
The O
malware O
will O
start O
the O
main O
service O
if O
all O
the O
requested O
permissions O
and O
the O
device O
admin O
privileges O
are O
granted O
. O
Otherwise O
, O
it O
will O
launch O
an O
ACTION_APPLICATION_SETTINGS O
intent O
trying O
to O
trick O
the O
user O
to O
grant O
the O
permissions O
. O
Each O
sample O
contains O
a O
userId O
hardcoded O
, O
meaning O
that O
each O
sample O
can O
only O
be O
used O
in O
a O
victim O
. O
It O
seems O
, O
however O
, O
if O
the O
same O
victim O
has O
more O
than O
one O
device O
the O
malware O
can O
be O
reused O
since O
the O
IMEI O
is O
sent O
along O
with O
each O
data O
exfiltration O
. O
It O
is O
clear O
that O
this O
RAT O
is O
under O
intense O
development O
, O
however O
, O
the O
addition O
and O
removal O
of O
packages O
, O
along O
with O
the O
huge O
quantity O
of O
unused O
code O
and O
usage O
of O
deprecated O
and O
old O
techniques O
denotes O
an O
amateur O
development O
methodology O
. O
CONCLUSION O
We O
witness O
actors O
continually O
using O
open-source O
platforms O
, O
code O
and O
packages O
to O
create O
their O
own O
software O
. O
Some O
are O
carried O
out O
well O
, O
others O
, O
like O
WolfRAT B-Malware
, O
are O
designed O
with O
an O
overload O
of O
functionality O
in O
mind O
as O
opposed O
to O
factoring O
any O
sensible O
approach O
to O
the O
development O
aspect O
. O
After O
all O
, O
a O
working O
product O
is O
often O
more O
important O
than O
a O
stable O
product O
. O
We O
watched O
WolfRAT B-Malware
evolve O
through O
various O
iterations O
which O
shows O
that O
the O
actor O
wanted O
to O
ensure O
functional O
improvements O
— O
perhaps O
they O
had O
deadlines O
to O
meet O
for O
their O
customers O
, O
but O
with O
no O
thought O
given O
to O
removing O
old O
code O
blocks O
, O
classes O
, O
etc O
. O
throughout O
the O
Android B-System
package O
. O
WolfRAT B-Malware
is O
a O
specifically O
targeted O
RAT O
which O
we O
assess O
to O
be O
aimed O
at O
Thai O
individuals O
and O
, O
based O
on O
previous O
work O
from O
Wolf B-Organization
Research I-Organization
, I-Organization
most O
likely O
used O
as O
an O
intelligence-gathering O
tool O
or O
interception O
tool O
. O
This O
can O
be O
packaged O
and O
" O
sold O
'' O
in O
many O
different O
ways O
to O
customers O
. O
A O
" O
Tracking O
tool O
'' O
or O
an O
" O
Admin O
tool O
'' O
are O
often O
cited O
for O
these O
kinds O
of O
tools O
for O
" O
commercial O
'' O
or O
" O
enterprise O
'' O
usage O
. O
Wolf I-Malware
Research I-Organization
claimed O
to O
shut O
down O
their O
operations O
but O
we O
clearly O
see O
that O
their O
previous O
work O
continues O
under O
another O
guise O
. O
The O
ability O
to O
carry O
out O
these O
types O
of O
intelligence-gathering O
activities O
on O
phones O
represents O
a O
huge O
score O
for O
the O
operator O
. O
The O
chat O
details O
, O
WhatsApp B-System
records O
, O
messengers O
and O
SMSs O
of O
the O
world O
carry O
some O
sensitive O
information O
which O
people O
often O
forget O
when O
communicating O
with O
their O
devices O
. O
We O
see O
WolfRAT B-Malware
specifically O
targeting O
a O
highly O
popular O
encrypted O
chat O
app O
in O
Asia O
, O
Line B-System
, O
which O
suggests O
that O
even O
a O
careful O
user O
with O
some O
awareness O
around O
end-to-end O
encryption O
chats O
would O
still O
be O
at O
the O
mercy O
of O
WolfRAT B-Malware
and O
it O
's O
prying O
eyes O
. O
IOCS O
Hashes O
139edb1bc033725539b117f50786f3d3362ed45845c57fe1f82e7ed72b044367 B-Indicator
e19823a1ba4a0e40cf459f4a0489fc257720cc0d71ecfb7ad94b3ca86fbd85d1 B-Indicator
e19823a1ba4a0e40cf459f4a0489fc257720cc0d71ecfb7ad94b3ca86fbd85d1 B-Indicator
e5f346d8f312cc1f93c2c6af611e2f50805c528934786ea173cabc6a39b14cda B-Indicator
1849a50a6ac9b3eec51492745eeb14765fe2e78488d476b0336d8e41c2c581d4 B-Indicator
d328fca14c4340fcd4a15e47562a436085e6b1bb5376b5ebd83d3e7218db64e7 B-Indicator
59b9809dba857c5969f23f460a2bf0a337a71622a79671066675ec0acf89c810 B-Indicator
120474682ea439eb0b28274c495d9610a73d892a4b8feeff268c670570db97e2 B-Indicator
ed234e61849dcb95223676abe2312e1378d6130c0b00851d82cda545b946ec83 B-Indicator
27410d4019251a70d38f0635277f931fb73f67ac9f2e1f3b475ce680ebfde12a B-Indicator
6e6c210535b414c5aa2dd9e67f5153feeb43a8ac8126d8e249e768f501323a3e B-Indicator
4a32ced20df7001da7d29edc31ca76e13eef0c9b355f62c44888853435e9794f B-Indicator
ac5abaebd9f516b8b389450f7d27649801d746fb14963b848f9d6dad0a505e66 B-Indicator
3a45d7a16937d4108b5b48f44d72bb319be645cbe15f003dc9e77fd52f45c065 B-Indicator
Domains O
cvcws B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ponethus I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
svc B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ponethus I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
www B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ponethus I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
webmail B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ponethus I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
com I-Indicator
nampriknum B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net I-Indicator
www B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
nampriknum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net I-Indicator
svc B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
nampriknum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net I-Indicator
svcws B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
nampriknum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
net I-Indicator
svc B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
somtum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
svcws B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
somtum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
www B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
somtum I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
somtum B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
shop B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
databit I-Indicator
[ I-Indicator
. I-Indicator
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today I-Indicator
svc B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
databit I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
test B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
databit I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
www B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
databit I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
admin B-Indicator
[ I-Indicator
.databit I-Indicator
[ I-Indicator
.today I-Indicator
cendata B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
svc B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cendata I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
svcws B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cendata I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
www B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cendata I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
today I-Indicator
PHA O
Family O
Highlights O
: O
Zen B-Malware
and O
its O
cousins O
January O
11 O
, O
2019 O
Google B-System
Play I-System
Protect I-System
detects O
Potentially O
Harmful O
Applications O
( O
PHAs O
) O
which O
Google B-System
Play I-System
Protect I-System
defines O
as O
any O
mobile O
app O
that O
poses O
a O
potential O
security O
risk O
to O
users O
or O
to O
user O
data—commonly O
referred O
to O
as O
" O
malware O
. O
'' O
in O
a O
variety O
of O
ways O
, O
such O
as O
static O
analysis O
, O
dynamic O
analysis O
, O
and O
machine O
learning O
. O
While O
our O
systems O
are O
great O
at O
automatically O
detecting O
and O
protecting O
against O
PHAs O
, O
we O
believe O
the O
best O
security O
comes O
from O
the O
combination O
of O
automated O
scanning O
and O
skilled O
human O
review O
. O
With O
this O
blog O
series O
we O
will O
be O
sharing O
our O
research O
analysis O
with O
the O
research O
and O
broader O
security O
community O
, O
starting O
with O
the O
PHA O
family O
, O
Zen B-Malware
. O
Zen B-Malware
uses O
root O
permissions O
on O
a O
device O
to O
automatically O
enable O
a O
service O
that O
creates O
fake O
Google B-Organization
accounts O
. O
These O
accounts O
are O
created O
by O
abusing O
accessibility O
services O
. O
Zen B-Malware
apps O
gain O
access O
to O
root O
permissions O
from O
a O
rooting O
trojan O
in O
its O
infection O
chain O
. O
In O
this O
blog O
post O
, O
we O
do O
not O
differentiate O
between O
the O
rooting O
component O
and O
the O
component O
that O
abuses O
root O
: O
we O
refer O
to O
them O
interchangeably O
as O
Zen B-Malware
. O
We O
also O
describe O
apps O
that O
we O
think O
are O
coming O
from O
the O
same O
author O
or O
a O
group O
of O
authors O
. O
All O
of O
the O
PHAs O
that O
are O
mentioned O
in O
this O
blog O
post O
were O
detected O
and O
removed O
by O
Google B-System
Play I-System
Protect I-System
. O
Background O
Uncovering O
PHAs O
takes O
a O
lot O
of O
detective O
work O
and O
unraveling O
the O
mystery O
of O
how O
they O
're O
possibly O
connected O
to O
other O
apps O
takes O
even O
more O
. O
PHA O
authors O
usually O
try O
to O
hide O
their O
tracks O
, O
so O
attribution O
is O
difficult O
. O
Sometimes O
, O
we O
can O
attribute O
different O
apps O
to O
the O
same O
author O
based O
on O
a O
small O
, O
unique O
pieces O
of O
evidence O
that O
suggest O
similarity O
, O
such O
as O
a O
repetition O
of O
an O
exceptionally O
rare O
code O
snippet O
, O
asset O
, O
or O
a O
particular O
string O
in O
the O
debug O
logs O
. O
Every O
once O
in O
a O
while O
, O
authors O
leave O
behind O
a O
trace O
that O
allows O
us O
to O
attribute O
not O
only O
similar O
apps O
, O
but O
also O
multiple O
different O
PHA O
families O
to O
the O
same O
group O
or O
person O
. O
However O
, O
the O
actual O
timeline O
of O
the O
creation O
of O
different O
variants O
is O
unclear O
. O
In O
April O
2013 O
, O
we O
saw O
the O
first O
sample O
, O
which O
made O
heavy O
use O
of O
dynamic O
code O
loading O
( O
i.e. O
, O
fetching O
executable O
code O
from O
remote O
sources O
after O
the O
initial O
app O
is O
installed O
) O
. O
Dynamic O
code O
loading O
makes O
it O
impossible O
to O
state O
what O
kind O
of O
PHA O
it O
was O
. O
This O
sample O
displayed O
ads O
from O
various O
sources O
. O
More O
recent O
variants O
blend O
rooting O
capabilities O
and O
click O
fraud O
. O
As O
rooting O
exploits O
on O
Android B-System
become O
less O
prevalent O
and O
lucrative O
, O
PHA O
authors O
adapt O
their O
abuse O
or O
monetization O
strategy O
to O
focus O
on O
tactics O
like O
click O
fraud O
. O
This O
post O
does O
n't O
follow O
the O
chronological O
evolution O
of O
Zen B-Malware
, O
but O
instead O
covers O
relevant O
samples O
from O
least O
to O
most O
complex O
. O
Apps O
with O
a O
custom-made O
advertisement O
SDK O
The O
simplest O
PHA O
from O
the O
author O
's O
portfolio O
used O
a O
specially O
crafted O
advertisement O
SDK O
to O
create O
a O
proxy O
for O
all O
ads-related O
network O
traffic O
. O
By O
proxying O
all O
requests O
through O
a O
custom O
server O
, O
the O
real O
source O
of O
ads O
is O
opaque O
. O
This O
example O
shows O
one O
possible O
implementation O
of O
this O
technique O
. O
This O
approach O
allows O
the O
authors O
to O
combine O
ads O
from O
third-party O
advertising O
networks O
with O
ads O
they O
created O
for O
their O
own O
apps O
. O
It O
may O
even O
allow O
them O
to O
sell O
ad O
space O
directly O
to O
application O
developers O
. O
The O
advertisement O
SDK O
also O
collects O
statistics O
about O
clicks O
and O
impressions O
to O
make O
it O
easier O
to O
track O
revenue O
. O
Selling O
the O
ad O
traffic O
directly O
or O
displaying O
ads O
from O
other O
sources O
in O
a O
very O
large O
volume O
can O
provide O
direct O
profit O
to O
the O
app O
author O
from O
the O
advertisers O
. O
We O
have O
seen O
two O
types O
of O
apps O
that O
use O
this O
custom-made O
SDK O
. O
The O
first O
are O
games O
of O
very O
low O
quality O
that O
mimic O
the O
experience O
of O
popular O
mobile O
games O
. O
While O
the O
counterfeit O
games O
claim O
to O
provide O
similar O
functionality O
to O
the O
popular O
apps O
, O
they O
are O
simply O
used O
to O
display O
ads O
through O
a O
custom O
advertisement O
SDK O
. O
The O
second O
type O
of O
apps O
reveals O
an O
evolution O
in O
the O
author O
's O
tactics O
. O
Instead O
of O
implementing O
very O
basic O
gameplay O
, O
the O
authors O
pirated O
and O
repackaged O
the O
original O
game O
in O
their O
app O
and O
bundled O
with O
it O
their O
advertisement O
SDK O
. O
The O
only O
noticeable O
difference O
is O
the O
game O
has O
more O
ads O
, O
including O
ads O
on O
the O
very O
first O
screen O
. O
In O
all O
cases O
, O
the O
ads O
are O
used O
to O
convince O
users O
to O
install O
other O
apps O
from O
different O
developer O
accounts O
, O
but O
written O
by O
the O
same O
group O
. O
Those O
apps O
use O
the O
same O
techniques O
to O
monetize O
their O
actions O
. O
Click O
fraud O
apps O
The O
authors O
' O
tactics O
evolved O
from O
advertisement O
spam O
to O
real O
PHA O
( O
Click O
Fraud O
) O
. O
Click O
fraud O
PHAs O
simulate O
user O
clicks O
on O
ads O
instead O
of O
simply O
displaying O
ads O
and O
waiting O
for O
users O
to O
click O
them O
. O
This O
allows O
the O
PHA O
authors O
to O
monetize O
their O
apps O
more O
effectively O
than O
through O
regular O
advertising O
. O
This O
behavior O
negatively O
impacts O
advertisement O
networks O
and O
their O
clients O
because O
advertising O
budget O
is O
spent O
without O
acquiring O
real O
customers O
, O
and O
impacts O
user O
experience O
by O
consuming O
their O
data O
plan O
resources O
. O
The O
click O
fraud O
PHA O
requests O
a O
URL O
to O
the O
advertising O
network O
directly O
instead O
of O
proxying O
it O
through O
an O
additional O
SDK O
. O
The O
command O
& O
control O
server O
( O
C O
& O
C O
server O
) O
returns O
the O
URL O
to O
click O
along O
with O
a O
very O
long O
list O
of O
additional O
parameters O
in O
JSON O
format O
. O
After O
rendering O
the O
ad O
on O
the O
screen O
, O
the O
app O
tries O
to O
identify O
the O
part O
of O
the O
advertisement O
website O
to O
click O
. O
If O
that O
part O
is O
found O
, O
the O
app O
loads O
Javascript O
snippets O
from O
the O
JSON O
parameters O
to O
click O
a O
button O
or O
other O
HTML O
element O
, O
simulating O
a O
real O
user O
click O
. O
Because O
a O
user O
interacting O
with O
an O
ad O
often O
leads O
to O
a O
higher O
chance O
of O
the O
user O
purchasing O
something O
, O
ad O
networks O
often O
" O
pay O
per O
click O
'' O
to O
developers O
who O
host O
their O
ads O
. O
Therefore O
, O
by O
simulating O
fraudulent O
clicks O
, O
these O
developers O
are O
making O
money O
without O
requiring O
a O
user O
to O
click O
on O
an O
advertisement O
. O
This O
example O
code O
shows O
a O
JSON O
reply O
returned O
by O
the O
C O
& O
C O
server O
. O
It O
has O
been O
shortened O
for O
brevity O
. O
Based O
on O
this O
JSON O
reply O
, O
the O
app O
looks O
for O
an O
HTML O
snippet O
that O
corresponds O
to O
the O
active O
element O
( O
show_hide O
btnnext O
) O
and O
, O
if O
found O
, O
the O
Javascript O
snippet O
tries O
to O
perform O
a O
click O
( O
) O
method O
on O
it O
. O
Rooting O
trojans O
The O
Zen B-Malware
authors O
have O
also O
created O
a O
rooting O
trojan O
. O
Using O
a O
publicly O
available O
rooting O
framework O
, O
the O
PHA O
attempts O
to O
root O
devices O
and O
gain O
persistence O
on O
them O
by O
reinstalling O
itself O
on O
the O
system O
partition O
of O
rooted O
device O
. O
Installing O
apps O
on O
the O
system O
partition O
makes O
it O
harder O
for O
the O
user O
to O
remove O
the O
app O
. O
This O
technique O
only O
works O
for O
unpatched O
devices O
running O
Android B-System
4.3 I-System
or O
lower O
. O
Devices O
running O
Android B-System
4.4 I-System
and O
higher O
are O
protected O
by O
Verified O
Boot O
. O
Zen B-Malware
's O
rooting O
trojan O
apps O
target O
a O
specific O
device O
model O
with O
a O
very O
specific O
system O
image O
. O
After O
achieving O
root O
access O
the O
app O
tries O
to O
replace O
the O
framework.jar B-Indicator
file O
on O
the O
system O
partition O
. O
Replicating O
framework.jar B-Indicator
allows O
the O
app O
to O
intercept O
and O
modify O
the O
behavior O
of O
the O
Android B-System
standard O
API O
. O
In O
particular O
, O
these O
apps O
try O
to O
add O
an O
additional O
method O
called O
statistics O
( O
) O
into O
the O
Activity O
class O
. O
When O
inserted O
, O
this O
method O
runs O
every O
time O
any O
Activity O
object O
in O
any O
Android O
app O
is O
created O
. O
This O
happens O
all O
the O
time O
in O
regular O
Android B-System
apps O
, O
as O
Activity O
is O
one O
of O
the O
fundamental O
Android B-System
UI O
elements O
. O
The O
only O
purpose O
of O
this O
method O
is O
to O
connect O
to O
the O
C O
& O
C O
server O
. O
The O
Zen B-Malware
trojan O
After O
achieving O
persistence O
, O
the O
trojan O
downloads O
additional O
payloads O
, O
including O
another O
trojan O
called O
Zen B-Malware
. O
Zen B-Malware
requires O
root O
to O
work O
correctly O
on O
the O
Android B-System
operating O
system O
. O
The O
Zen B-Malware
trojan O
uses O
its O
root O
privileges O
to O
turn O
on O
accessibility O
service O
( O
a O
service O
used O
to O
allow O
Android B-System
users O
with O
disabilities O
to O
use O
their O
devices O
) O
for O
itself O
by O
writing O
to O
a O
system-wide O
setting O
value O
enabled_accessibility_services O
. O
Zen B-Malware
does O
n't O
even O
check O
for O
the O
root O
privilege O
: O
it O
just O
assumes O
it O
has O
it O
. O
This O
leads O
us O
to O
believe O
that O
Zen B-Malware
is O
just O
part O
of O
a O
larger O
infection O
chain O
. O
The O
trojan O
implements O
three O
accessibility O
services O
directed O
at O
different O
Android B-System
API I-System
levels O
and O
uses O
these O
accessibility O
services O
, O
chosen O
by O
checking O
the O
operating O
system O
version O
, O
to O
create O
new O
Google B-Organization
accounts O
. O
This O
is O
done O
by O
opening O
the O
Google B-Organization
account O
creation O
process O
and O
parsing O
the O
current O
view O
. O
The O
app O
then O
clicks O
the O
appropriate O
buttons O
, O
scrollbars O
, O
and O
other O
UI O
elements O
to O
go O
through O
account O
sign-up O
without O
user O
intervention O
. O
During O
the O
account O
sign-up O
process O
, O
Google B-Organization
may O
flag O
the O
account O
creation O
attempt O
as O
suspicious O
and O
prompt O
the O
app O
to O
solve O
a O
CAPTCHA O
. O
To O
get O
around O
this O
, O
the O
app O
then O
uses O
its O
root O
privilege O
to O
inject O
code O
into O
the O
Setup O
Wizard O
, O
extract O
the O
CAPTCHA O
image O
, O
and O
sends O
it O
to O
a O
remote O
server O
to O
try O
to O
solve O
the O
CAPTCHA O
. O
It O
is O
unclear O
if O
the O
remote O
server O
is O
capable O
of O
solving O
the O
CAPTCHA O
image O
automatically O
or O
if O
this O
is O
done O
manually O
by O
a O
human O
in O
the O
background O
. O
After O
the O
server O
returns O
the O
solution O
, O
the O
app O
enters O
it O
into O
the O
appropriate O
text O
field O
to O
complete O
the O
CAPTCHA O
challenge O
. O
The O
Zen B-Malware
trojan O
does O
not O
implement O
any O
kind O
of O
obfuscation O
except O
for O
one O
string O
that O
is O
encoded O
using O
Base64 O
encoding O
. O
It O
's O
one O
of O
the O
strings O
- O
" O
How O
you O
'll O
sign O
in O
'' O
- O
that O
it O
looks O
for O
during O
the O
account O
creation O
process O
. O
The O
code O
snippet O
below O
shows O
part O
of O
the O
screen O
parsing O
process O
. O
Apart O
from O
injecting O
code O
to O
read O
the O
CAPTCHA O
, O
the O
app O
also O
injects O
its O
own O
code O
into O
the O
system_server O
process O
, O
which O
requires O
root O
privileges O
. O
This O
indicates O
that O
the O
app O
tries O
to O
hide O
itself O
from O
any O
anti-PHA O
systems O
that O
look O
for O
a O
specific O
app O
process O
name O
or O
does O
not O
have O
the O
ability O
to O
scan O
the O
memory O
of O
the O
system_server O
process O
. O
The O
app O
also O
creates O
hooks O
to O
prevent O
the O
phone O
from O
rebooting O
, O
going O
to O
sleep O
or O
allowing O
the O
user O
from O
pressing O
hardware O
buttons O
during O
the O
account O
creation O
process O
. O
These O
hooks O
are O
created O
using O
the O
root O
access O
and O
a O
custom O
native O
code O
called O
Lmt_INJECT O
, O
although O
the O
algorithm O
for O
this O
is O
well O
known O
. O
First O
, O
the O
app O
has O
to O
turn O
off O
SELinux B-System
protection O
. O
Then O
the O
app O
finds O
a O
process O
id O
value O
for O
the O
process O
it O
wants O
to O
inject O
with O
code O
. O
This O
is O
done O
using O
a O
series O
of O
syscalls O
as O
outlined O
below O
. O
The O
" O
source O
process O
'' O
refers O
to O
the O
Zen B-Malware
trojan O
running O
as O
root O
, O
while O
the O
" O
target O
process O
'' O
refers O
to O
the O
process O
to O
which O
the O
code O
is O
injected O
and O
[ O
pid O
] O
refers O
to O
the O
target O
process O
pid O
value O
. O
The O
source O
process O
checks O
the O
mapping O
between O
a O
process O
id O
and O
a O
process O
name O
. O
This O
is O
done O
by O
reading O
the O
/proc/ B-Indicator
[ I-Indicator
pid I-Indicator
] I-Indicator
/cmdline I-Indicator
file O
. O
This O
very O
first O
step O
fails O
in O
Android B-System
7.0 I-System
and O
higher O
, O
even O
with O
a O
root O
permission O
. O
The O
/proc B-Indicator
filesystem O
is O
now O
mounted O
with O
a O
hidepid=2 O
parameter O
, O
which O
means O
that O
the O
process O
can O
not O
access O
other O
process O
/proc/ B-Indicator
[ I-Indicator
pid I-Indicator
] I-Indicator
directory O
. O
A O
ptrace_attach O
syscall O
is O
called O
. O
This O
allows O
the O
source O
process O
to O
trace O
the O
target O
. O
The O
source O
process O
looks O
at O
its O
own O
memory O
to O
calculate O
the O
offset O
between O
the O
beginning O
of O
the O
libc O
library O
and O
the O
mmap O
address O
. O
The O
source O
process O
reads O
/proc/ B-Indicator
[ I-Indicator
pid I-Indicator
] I-Indicator
/maps I-Indicator
to O
find O
where O
libc O
is O
located O
in O
the O
target O
process O
memory O
. O
By O
adding O
the O
previously O
calculated O
offset O
, O
it O
can O
get O
the O
address O
of O
the O
mmap O
function O
in O
the O
target O
process O
memory O
. O
The O
source O
process O
tries O
to O
determine O
the O
location O
of O
dlopen O
, O
dlsym O
, O
and O
dlclose O
functions O
in O
the O
target O
process O
. O
It O
uses O
the O
same O
technique O
as O
it O
used O
to O
determine O
the O
offset O
to O
the O
mmap O
function O
. O
The O
source O
process O
writes O
the O
native O
shellcode O
into O
the O
memory O
region O
allocated O
by O
mmap O
. O
Additionally O
, O
it O
also O
writes O
addresses O
of O
dlopen O
, O
dlsym O
, O
and O
dlclose O
into O
the O
same O
region O
, O
so O
that O
they O
can O
be O
used O
by O
the O
shellcode O
. O
Shellcode O
simply O
uses O
dlopen O
to O
open O
a O
.so O
file O
within O
the O
target O
process O
and O
then O
dlsym O
to O
find O
a O
symbol B-Organization
in O
that O
file O
and O
run O
it O
. O
The O
source O
process O
changes O
the O
registers O
in O
the O
target O
process O
so O
that O
PC O
register O
points O
directly O
to O
the O
shellcode O
. O
This O
is O
done O
using O
the O
ptrace O
syscall O
. O
This O
diagram O
illustrates O
the O
whole O
process O
. O
Summary O
PHA O
authors O
go O
to O
great O
lengths O
to O
come O
up O
with O
increasingly O
clever O
ways O
to O
monetize O
their O
apps O
. O
Zen B-Malware
family O
PHA O
authors O
exhibit O
a O
wide O
range O
of O
techniques O
, O
from O
simply O
inserting O
an O
advertising O
SDK O
to O
a O
sophisticated O
trojan O
. O
The O
app O
that O
resulted O
in O
the O
largest O
number O
of O
affected O
users O
was O
the O
click O
fraud O
version O
, O
which O
was O
installed O
over O
170,000 O
times O
at O
its O
peak O
in O
February O
2018 O
. O
The O
most O
affected O
countries O
were O
India O
, O
Brazil O
, O
and O
Indonesia O
. O
In O
most O
cases O
, O
these O
click O
fraud O
apps O
were O
uninstalled O
by O
the O
users O
, O
probably O
due O
to O
the O
low O
quality O
of O
the O
apps O
. O
If O
Google B-System
Play I-System
Protect I-System
detects O
one O
of O
these O
apps O
, O
Google B-System
Play I-System
Protect I-System
will O
show O
a O
warning O
to O
users O
. O
We O
are O
constantly O
on O
the O
lookout O
for O
new O
threats O
and O
we O
are O
expanding O
our O
protections O
. O
Every O
device O
with O
Google B-System
Play I-System
includes O
Google B-System
Play I-System
Protect I-System
and O
all O
apps O
on O
Google B-System
Play I-System
are O
automatically O
and O
periodically O
scanned O
by O
our O
solutions O
. O
You O
can O
check O
the O
status O
of O
Google B-System
Play I-System
Protect I-System
on O
your O
device O
: O
Open O
your O
Android O
device O
's O
Google B-System
Play I-System
Store I-System
app O
. O
Tap O
Menu O
> O
Play O
Protect O
. O
Look O
for O
information O
about O
the O
status O
of O
your O
device O
. O
Hashes O
of O
samples O
Type O
Package O
name O
SHA256 O
digest O
Custom O
ads O
com.targetshoot.zombieapocalypse.sniper.zombieshootinggame B-Indicator
5d98d8a7a012a858f0fa4cf8d2ed3d5a82937b1a98ea2703d440307c63c6c928 B-Indicator
Click O
fraud O
com.counterterrorist.cs.elite.combat.shootinggame B-Indicator
84672fb2f228ec749d3c3c1cb168a1c31f544970fd29136bea2a5b2cefac6d04 B-Indicator
Rooting O
trojan O
com.android.world.news O
bd233c1f5c477b0cc15d7f84392dab3a7a598243efa3154304327ff4580ae213 B-Indicator
Zen B-Malware
trojan O
com.lmt.register B-Indicator
eb12cd65589cbc6f9d3563576c304273cb6a78072b0c20a155a0951370476d8d B-Indicator
Mobile O
Campaign O
‘ O
Bouncing B-Malware
Golf I-Malware
’ O
Affects O
Middle O
East O
We O
uncovered O
a O
cyberespionage O
campaign O
targeting O
Middle O
Eastern O
countries O
. O
We O
named O
this O
campaign O
“ O
Bouncing B-Malware
Golf I-Malware
” O
based O
on O
the O
malware O
’ O
s O
code O
in O
the O
package O
named O
“ O
golf. O
” O
June O
18 O
, O
2019 O
We O
uncovered O
a O
cyberespionage O
campaign O
targeting O
Middle O
Eastern O
countries O
. O
We O
named O
this O
campaign O
“ O
Bouncing B-Malware
Golf I-Malware
” O
based O
on O
the O
malware O
’ O
s O
code O
in O
the O
package O
named O
“ O
golf. O
” O
The O
malware O
involved O
, O
which O
Trend B-Organization
Micro I-Organization
detects O
as O
AndroidOS_GolfSpy.HRX B-Malware
, O
is O
notable O
for O
its O
wide O
range O
of O
cyberespionage O
capabilities O
. O
Malicious O
codes O
are O
embedded O
in O
apps O
that O
the O
operators O
repackaged O
from O
legitimate O
applications O
. O
Monitoring O
the O
command O
and O
control O
( O
C O
& O
C O
) O
servers O
used O
by O
Bouncing B-Malware
Golf I-Malware
, O
we O
’ O
ve O
so O
far O
observed O
more O
than O
660 O
Android B-System
devices O
infected O
with O
GolfSpy B-Malware
. O
Much O
of O
the O
information O
being O
stolen O
appear O
to O
be O
military-related O
. O
The O
campaign O
’ O
s O
attack O
vector O
is O
also O
interesting O
. O
These O
repackaged O
, O
malware-laden O
apps O
are O
neither O
on O
Google B-System
Play I-System
nor O
popular O
third-party O
app O
marketplaces O
, O
and O
we O
only O
saw O
the O
website O
hosting O
the O
malicious O
apps O
being O
promoted O
on O
social O
media O
when O
we O
followed O
GolfSpy B-Malware
’ O
s O
trail O
. O
We O
were O
also O
able O
to O
analyze O
some O
GolfSpy B-Malware
samples O
sourced O
from O
the O
Trend B-Organization
Micro I-Organization
mobile O
app O
reputation O
service O
. O
Also O
of O
note O
is O
Bouncing B-Malware
Golf I-Malware
’ O
s O
possible O
connection O
to O
a O
previously O
reported O
mobile O
cyberespionage O
campaign O
that O
researchers O
named O
Domestic B-Malware
Kitten I-Malware
. O
The O
strings O
of O
code O
, O
for O
one O
, O
are O
similarly O
structured O
. O
The O
data O
targeted O
for O
theft O
also O
have O
similar O
formats O
. O
Figure O
1 O
. O
GolfSpy B-Malware
’ O
s O
infection O
chain O
GolfSpy B-Malware
's O
Potential O
Impact O
Given O
GolfSpy B-Malware
’ O
s O
information-stealing O
capabilities O
, O
this O
malware O
can O
effectively O
hijack O
an O
infected O
Android B-System
device O
. O
Here O
is O
a O
list O
of O
information O
that O
GolfSpy B-Malware
steals O
: O
Device O
accounts O
List O
of O
applications O
installed O
in O
the O
device O
Device O
’ O
s O
current O
running O
processes O
Battery O
status O
Bookmarks/Histories O
of O
the O
device O
’ O
s O
default O
browser O
Call O
logs O
and O
records O
Clipboard O
contents O
Contacts O
, O
including O
those O
in O
VCard O
format O
Mobile O
operator O
information O
Files O
stored O
on O
SDcard O
Device O
location O
List O
of O
image O
, O
audio O
, O
and O
video O
files O
stored O
on O
the O
device O
Storage O
and O
memory O
information O
Connection O
information O
Sensor O
information O
SMS O
messages O
Pictures O
GolfSpy B-Malware
also O
has O
a O
function O
that O
lets O
it O
connect O
to O
a O
remote O
server O
to O
fetch O
and O
perform O
commands O
, O
including O
: O
searching O
for O
, O
listing O
, O
deleting O
, O
and O
renaming O
files O
as O
well O
as O
downloading O
a O
file O
into O
and O
retrieving O
a O
file O
from O
the O
device O
; O
taking O
screenshots O
; O
installing O
other O
application O
packages O
( O
APK O
) O
; O
recording O
audio O
and O
video O
; O
and O
updating O
the O
malware O
. O
Technical O
Analysis O
The O
repackaged O
applications O
are O
embedded O
with O
malicious O
code O
, O
which O
can O
be O
found O
in O
the O
com.golf B-Indicator
package O
. O
These O
repackaged O
apps O
pose O
as O
communication O
, O
news O
, O
lifestyle O
, O
book O
, O
and O
reference O
apps O
popularly O
used O
in O
the O
Middle O
East O
. O
The O
GolfSpy B-Malware
malware O
embedded O
in O
the O
apps O
is O
hardcoded O
with O
an O
internal O
name O
used O
by O
the O
attacker O
. O
Figure O
2 O
. O
Icons O
of O
the O
apps O
that O
Bouncing B-Malware
Golf I-Malware
’ O
s O
operators O
repackaged O
( O
top O
) O
and O
a O
comparison O
of O
packages O
between O
the O
original O
legitimate O
app O
( O
bottom O
left O
) O
and O
GolfSpy B-Malware
( O
bottom O
right O
) O
Figure O
3 O
. O
GolfSpy B-Malware
’ O
s O
configurations O
encoded O
by O
a O
custom O
algorithm O
( O
right O
) O
and O
its O
decoded O
version O
( O
left O
) O
As O
shown O
in O
Figure O
3 O
, O
GolfSpy B-Malware
’ O
s O
configurations O
( O
e.g. O
, O
C O
& O
C O
server O
, O
secret O
keys O
) O
are O
encoded O
by O
a O
customized O
algorithm O
. O
After O
it O
is O
launched O
, O
GolfSpy B-Malware
will O
generate O
a O
unique O
ID O
for O
the O
affected O
device O
and O
then O
collect O
its O
data O
such O
as O
SMS O
, O
contact O
list O
, O
location O
, O
and O
accounts O
in O
this O
format O
: O
“ O
% O
, O
[ O
] O
, O
time O
” O
( O
shown O
in O
Figure O
4 O
) O
. O
The O
information O
is O
written O
into O
a O
file O
on O
the O
device O
. O
The O
attacker O
can O
choose O
the O
data O
types O
to O
collect O
, O
which O
are O
written O
in O
a O
certain O
format O
. O
Figure O
4 O
. O
Code O
snippet O
showing O
GolfSpy B-Malware
generating O
UUID O
The O
value O
of O
% O
is O
in O
the O
range O
of O
1-9 O
or O
a-j O
. O
Each O
value O
represents O
a O
different O
type O
of O
data O
to O
steal O
from O
the O
device O
: O
Value O
Data O
Type O
1 O
Accounts O
2 O
Installed O
APP O
list O
3 O
Running O
processes O
list O
4 O
Battery O
status O
5 O
Browser O
bookmarks O
and O
histories O
6 O
Call O
logs O
7 O
Clipboard O
8 O
Contacts O
9 O
Mobile O
operator O
information O
a O
File O
list O
on O
SD O
card O
b O
Location O
c O
Image O
list O
d O
Audio O
list O
e O
Video O
list O
f O
Storage O
and O
memory O
information O
g O
Connection O
information O
h O
Sensors O
information O
i O
SMS O
messages O
j O
VCard O
format O
contacts O
Table O
1 O
. O
The O
type O
of O
data O
corresponding O
to O
the O
value O
coded O
in O
GolfSpy B-Malware
Figure O
5 O
shows O
the O
code O
snippets O
that O
are O
involved O
in O
monitoring O
and O
recording O
the O
device O
’ O
s O
phone O
call O
. O
It O
will O
also O
take O
a O
photo O
using O
the O
device O
’ O
s O
front O
camera O
when O
the O
user O
wakes O
the O
device O
. O
Apart O
from O
collecting O
the O
above O
data O
, O
the O
spyware O
monitors O
users O
’ O
phone O
calls O
, O
records O
them O
, O
and O
saves O
the O
recorded O
file O
on O
the O
device O
. O
GolfSpy B-Malware
encrypts O
all O
the O
stolen O
data O
using O
a O
simple O
XOR O
operation O
with O
a O
pre-configured O
key O
before O
sending O
it O
to O
the O
C O
& O
C O
server O
using O
the O
HTTP O
POST O
method O
. O
Figure O
5 O
. O
Code O
snippets O
showing O
how O
GolfSpy B-Malware
monitors O
phone O
calls O
via O
register O
receiver O
( O
top O
left O
) O
, O
its O
actions O
when O
the O
device O
is O
woken O
up O
( O
top O
right O
) O
, O
and O
how O
it O
encrypts O
the O
stolen O
data O
( O
bottom O
) O
The O
malware O
retrieves O
commands O
from O
the O
C O
& O
C O
server O
via O
HTTP O
, O
and O
attackers O
can O
steal O
specific O
files O
on O
the O
infected O
device O
. O
The O
command O
is O
a O
constructed O
string O
split O
into O
three O
parts O
using O
" O
" O
as O
a O
separator O
. O
The O
first O
part O
is O
the O
target O
directory O
, O
the O
second O
is O
a O
regular O
expression O
used O
to O
match O
specific O
files O
, O
while O
the O
last O
part O
is O
an O
ID O
. O
Figure O
6 O
. O
Example O
of O
a O
command O
that O
steals O
specific O
files O
from O
an O
infected O
device O
’ O
s O
application O
( O
top O
) O
, O
and O
GolfSpy B-Malware
’ O
s O
parse-and-perform O
command O
( O
bottom O
) O
Apart O
from O
the O
HTTP O
POST O
method O
, O
GolfSpy B-Malware
also O
creates O
a O
socket O
connection O
to O
the O
remote O
C O
& O
C O
server O
in O
order O
to O
receive O
and O
perform O
additional O
commands O
. O
Stolen O
data O
will O
also O
be O
encrypted O
and O
sent O
to O
the O
C O
& O
C O
server O
via O
the O
socket O
connection O
. O
The O
encryption O
key O
is O
different O
from O
the O
one O
used O
for O
sending O
stolen O
data O
via O
HTTP O
. O
Figure O
7 O
. O
The O
additional O
commands O
that O
attackers O
can O
carry O
out O
via O
a O
socket O
connection O
( O
top O
) O
and O
the O
key O
used O
to O
encrypt O
the O
stolen O
data O
( O
bottom O
) O
Correlating O
Bouncing B-Malware
Golf I-Malware
's O
Activities O
We O
monitored O
Bouncing B-Malware
Golf I-Malware
’ O
s O
C O
& O
C-related O
activities O
and O
saw O
that O
the O
campaign O
has O
affected O
more O
than O
660 O
devices O
as O
of O
this O
writing O
. O
The O
small O
or O
limited O
number O
is O
understandable O
given O
the O
nature O
of O
this O
campaign O
, O
but O
we O
also O
expect O
it O
to O
increase O
or O
even O
diversify O
in O
terms O
of O
distribution O
. O
Most O
of O
the O
affected O
devices O
were O
located O
in O
the O
Middle O
East O
, O
and O
many O
of O
the O
stolen O
data O
we O
saw O
is O
military-related O
( O
e.g. O
, O
images O
, O
documents O
) O
. O
Bouncing B-Malware
Golf I-Malware
’ O
s O
operators O
also O
try O
to O
cover O
their O
tracks O
. O
The O
registrant O
contact O
details O
of O
the O
C O
& O
C O
domains O
used O
in O
the O
campaign O
, O
for O
instance O
, O
were O
masked O
. O
The O
C O
& O
C O
server O
IP O
addresses O
used O
also O
appear O
to O
be O
disparate O
, O
as O
they O
were O
located O
in O
many O
European O
countries O
like O
Russia O
, O
France O
, O
Holland O
, O
and O
Germany O
. O
It O
’ O
s O
not O
a O
definite O
correlation O
, O
but O
Bouncing B-Malware
Golf I-Malware
also O
seems O
to O
have O
a O
connection O
with O
Domestic B-Malware
Kitten I-Malware
due O
to O
similarities O
we O
found O
in O
their O
code O
. O
For O
example O
, O
the O
Android B-System
malware O
that O
both O
deploy O
share O
the O
same O
strings O
of O
code O
for O
their O
decoding O
algorithm O
. O
The O
data O
that O
Domestic B-Malware
Kitten I-Malware
steals O
follows O
a O
similar O
format O
with O
Bouncing B-Malware
Golf I-Malware
’ O
s O
, O
with O
each O
type O
of O
data O
having O
a O
unique O
identifying O
character O
. O
It O
’ O
s O
also O
worth O
noting O
that O
both O
campaigns O
repackage O
apps O
that O
are O
commonly O
used O
in O
their O
target O
’ O
s O
countries O
, O
such O
as O
Telegram B-System
, O
Kik B-System
, O
and O
Plus B-System
messaging O
apps O
. O
Figure O
8 O
. O
Code O
snippets O
showing O
: O
the O
decoding O
algorithm O
shared O
by O
both O
Bouncing B-Malware
Golf I-Malware
and O
Domestic B-Malware
Kitten I-Malware
( O
top O
) O
, O
the O
format O
of O
data O
that O
Domestic B-Malware
Kitten I-Malware
’ O
s O
malware O
targets O
to O
steal O
( O
center O
) O
, O
and O
how O
both O
Bouncing B-Malware
Golf I-Malware
( O
bottom O
left O
) O
and O
Domestic B-Malware
Kitten I-Malware
( O
bottom O
right O
) O
use O
" O
" O
as O
a O
separator O
in O
their O
command O
strings O
. O
As O
we O
’ O
ve O
seen O
in O
last O
year O
’ O
s O
mobile O
threat O
landscape O
, O
we O
expect O
more O
cyberespionage O
campaigns O
targeting O
the O
mobile O
platform O
given O
its O
ubiquity O
, O
employing O
tried-and-tested O
techniques O
to O
lure O
unwitting O
users O
. O
The O
extent O
of O
information O
that O
these O
kinds O
of O
threats O
can O
steal O
is O
also O
significant O
, O
as O
it O
lets O
attackers O
virtually O
take O
over O
a O
compromised O
device O
. O
Users O
should O
adopt O
best O
practices O
, O
while O
organizations O
should O
ensure O
that O
they O
balance O
the O
need O
for O
mobility O
and O
the O
importance O
of O
security O
. O
End O
users O
and O
enterprises O
can O
also O
benefit O
from O
multilayered O
mobile O
security O
solutions O
such O
as O
Trend B-Organization
Micro™ I-Organization
Mobile O
Security™ O
. O
Trend B-Organization
Micro™ I-Organization
Mobile B-System
Security I-System
for I-System
Enterprise I-System
provides O
device O
, O
compliance O
and O
application O
management O
, O
data O
protection O
, O
and O
configuration O
provisioning O
, O
as O
well O
as O
protects O
devices O
from O
attacks O
that O
exploit O
vulnerabilities O
, O
preventing O
unauthorized O
access O
to O
apps O
, O
and O
detecting O
and O
blocking O
malware O
and O
fraudulent O
websites O
. O
Trend B-Organization
Micro I-Organization
’ O
s O
Mobile B-System
App I-System
Reputation I-System
Service I-System
( O
MARS O
) O
covers O
Android B-System
and O
iOS B-System
threats O
using O
leading O
sandbox O
and O
machine O
learning O
technologies O
, O
protecting O
devices O
against O
malware O
, O
zero-day O
and O
known O
exploits O
, O
privacy O
leaks O
, O
and O
application O
vulnerabilities O
. O
Several O
weeks O
ago O
, O
Check B-Organization
Point I-Organization
Mobile O
Threat O
Prevention O
detected O
and O
quarantined O
the O
Android B-System
device O
of O
an O
unsuspecting O
customer O
employee O
who O
downloaded O
and O
installed O
a O
0day O
mobile O
ransomware O
from O
Google B-System
Play I-System
dubbed O
“ O
Charger. B-Malware
” O
This O
incident O
demonstrates O
how O
malware O
can O
be O
a O
dangerous O
threat O
to O
your O
business O
, O
and O
how O
advanced O
behavioral O
detection O
fills O
mobile O
security O
gaps O
attackers O
use O
to O
penetrate O
entire O
networks O
. O
Charger B-Malware
was O
found O
embedded O
in O
an O
app O
called O
EnergyRescue B-Malware
. O
The O
infected O
app O
steals O
contacts O
and O
SMS O
messages O
from O
the O
user O
’ O
s O
device O
and O
asks O
for O
admin O
permissions O
. O
If O
granted O
, O
the O
ransomware O
locks O
the O
device O
and O
displays O
a O
message O
demanding O
payment O
: O
You O
need O
to O
pay O
for O
us O
, O
otherwise O
we O
will O
sell O
portion O
of O
your O
personal O
information O
on O
black O
market O
every O
30 O
minutes O
. O
WE O
GIVE O
100 O
% O
GUARANTEE O
THAT O
ALL O
FILES O
WILL O
RESTORE O
AFTER O
WE O
RECEIVE O
PAYMENT O
. O
WE O
WILL O
UNLOCK O
THE O
MOBILE O
DEVICE O
AND O
DELETE O
ALL O
YOUR O
DATA O
FROM O
OUR O
SERVER O
! O
TURNING O
OFF O
YOUR O
PHONE O
IS O
MEANINGLESS O
, O
ALL O
YOUR O
DATA O
IS O
ALREADY O
STORED O
ON O
OUR O
SERVERS O
! O
WE O
STILL O
CAN O
SELLING O
IT O
FOR O
SPAM O
, O
FAKE O
, O
BANK O
CRIME O
etc… O
We O
collect O
and O
download O
all O
of O
your O
personal O
data O
. O
All O
information O
about O
your O
social O
networks O
, O
Bank O
accounts O
, O
Credit O
Cards O
. O
We O
collect O
all O
data O
about O
your O
friends O
and O
family O
. O
The O
ransom O
demand O
for O
0.2 O
Bitcoins O
( O
roughly O
$ O
180 O
) O
is O
a O
much O
higher O
ransom O
demand O
than O
has O
been O
seen O
in O
mobile O
ransomware O
so O
far O
. O
By O
comparison O
, O
the O
DataLust B-Malware
ransomware O
demanded O
merely O
$ O
15 O
. O
Payments O
are O
made O
to O
a O
specific O
Bitcoin B-System
account O
, O
but O
we O
haven O
’ O
t O
identified O
any O
payments O
so O
far O
. O
Adware O
commonly O
found O
on O
Play O
collects O
profits O
from O
ad O
networks O
, O
but O
mobile O
ransomware O
inflicts O
direct O
harm O
to O
users O
. O
Like O
FakeDefender B-Malware
and O
DataLust B-Malware
, O
Charger B-Malware
could O
be O
an O
indicator O
of O
a O
wider O
effort O
by O
mobile O
malware O
developers O
to O
catch O
up O
with O
their O
PC O
ransomware O
cousins O
. O
Similar O
to O
other O
malware O
seen O
in O
the O
past O
, O
Charger B-Malware
checks O
the O
local O
settings O
of O
the O
device O
and O
does O
not O
run O
its O
malicious O
logic O
if O
the O
device O
is O
located O
in O
Ukraine O
, O
Russia O
, O
or O
Belarus O
. O
This O
is O
likely O
done O
to O
keep O
the O
developers O
from O
being O
prosecuted O
in O
their O
own O
countries O
or O
being O
extradited O
between O
countries O
. O
Most O
malware O
found O
on O
Google B-System
Play I-System
contains O
only O
a O
dropper O
that O
later O
downloads O
the O
real O
malicious O
components O
to O
the O
device O
. O
Charger B-Malware
, O
however O
, O
uses O
a O
heavy O
packing O
approach O
which O
it O
harder O
for O
the O
malware O
to O
stay O
hidden O
, O
so O
it O
must O
compensate O
with O
other O
means O
. O
The O
developers O
of O
Charger B-Malware
gave O
it O
everything O
they O
had O
to O
boost O
its O
evasion O
capabilities O
and O
so O
it O
could O
stay O
hidden O
on O
Google B-System
Play I-System
for O
as O
long O
as O
possible O
. O
The O
malware O
uses O
several O
advanced O
techniques O
to O
hide O
its O
real O
intentions O
and O
makes O
it O
harder O
to O
detect O
. O
It O
encodes O
strings O
into O
binary O
arrays O
, O
making O
it O
hard O
to O
inspect O
them O
. O
It O
loads O
code O
from O
encrypted O
resources O
dynamically O
, O
which O
most O
detection O
engines O
can O
not O
penetrate O
and O
inspect O
. O
The O
dynamically-loaded O
code O
is O
also O
flooded O
with O
meaningless O
commands O
that O
mask O
the O
actual O
commands O
passing O
through O
. O
It O
checks O
whether O
it O
is O
being O
run O
in O
an O
emulator O
before O
it O
starts O
its O
malicious O
activity O
. O
PC O
malware O
first O
introduced O
this O
technique O
which O
is O
becoming O
a O
trend O
in O
mobile O
malware O
having O
been O
adopted O
by O
several O
malware O
families O
including O
Dendroid B-Malware
. O
Emulator O
and O
location O
conditions O
for O
the O
malware O
’ O
s O
activity O
Check B-Organization
Point I-Organization
Mobile O
Threat O
Prevention O
customers O
are O
protected O
from O
Charger B-Malware
and O
similar O
malware O
. O
Check B-Organization
Point I-Organization
’ O
s O
Analysis O
and O
Response O
Team O
( O
ART O
) O
disclosed O
the O
finding O
to O
Android B-System
’ O
s O
Security O
team O
who O
took O
the O
appropriate O
security O
steps O
to O
remove O
the O
infected O
app O
and O
added O
the O
malware O
to O
Android B-System
’ O
s O
built-in O
protection O
mechanisms O
. O
Charger O
SHA256 O
hash O
: O
58eb6c368e129b17559bdeacb3aed4d9a5d3596f774cf5ed3fdcf51775232ba0 B-Indicator
Infostealer O
, O
Keylogger O
, O
and O
Ransomware O
in O
One O
: O
Anubis B-Malware
Targets O
More O
than O
250 O
Android B-System
Applications O
October O
29 O
, O
2021 O
The O
Cofense B-Organization
Phishing I-Organization
Defense I-Organization
Center I-Organization
uncovered O
a O
phishing O
campaign O
that O
specifically O
targets O
users O
of O
Android B-System
devices O
that O
could O
result O
in O
compromise O
if O
unsigned O
Android B-System
applications O
are O
permitted O
on O
the O
device O
. O
The O
campaign O
seeks O
to O
deliver O
Anubis B-Malware
, O
a O
particularly O
nasty O
piece O
of O
malware O
that O
was O
originally O
used O
for O
cyber O
espionage O
and O
retooled O
as O
a O
banking O
trojan O
. O
Anubis B-Malware
can O
completely O
hijack O
an O
Android B-System
mobile O
device O
, O
steal O
data O
, O
record O
phone O
calls O
, O
and O
even O
hold O
the O
device O
to O
ransom O
by O
encrypting O
the O
victim O
’ O
s O
personal O
files O
. O
With O
mobile O
devices O
increasingly O
used O
in O
the O
corporate O
environment O
, O
thanks O
to O
the O
popularity O
of O
BYOD O
policies O
, O
this O
malware O
has O
the O
potential O
to O
cause O
serious O
harm O
, O
mostly O
to O
consumers O
, O
and O
businesses O
that O
allow O
the O
installation O
of O
unsigned O
applications O
. O
Here O
’ O
s O
how O
it O
works O
: O
At O
first O
glance O
, O
the O
email O
shown O
in O
Figure O
1 O
looks O
like O
any O
other O
phishing O
email O
that O
asks O
the O
user O
to O
download O
an O
invoice O
. O
However O
, O
this O
particular O
email O
downloads O
an O
Android B-System
Package I-System
Kit I-System
( O
APK O
) O
, O
which O
is O
the O
common O
format O
used O
by O
Android B-System
to O
distribute O
and O
install O
applications O
. O
Let O
’ O
s O
take O
a O
closer O
look O
at O
the O
suspicious O
file O
. O
Figure O
1 O
– O
Phishing O
Email O
When O
the O
email O
link O
is O
opened O
from O
an O
Android B-System
device O
, O
an O
APK O
file O
( O
Fattura002873.apk B-Indicator
) O
, O
is O
downloaded O
. O
Upon O
opening O
the O
file O
, O
the O
user O
is O
asked O
to O
enable O
“ O
Google B-System
Play I-System
Protect O
” O
as O
shown O
in O
Figure O
2 O
. O
However O
, O
this O
is O
not O
a O
genuine O
“ O
Google B-System
Play I-System
Protect O
” O
screen O
; O
instead O
it O
gives O
the O
app O
all O
the O
permissions O
it O
needs O
while O
simultaneously O
disabling O
the O
actual O
Google B-System
Play I-System
Protect I-System
. O
Figure O
2 O
– O
Granting O
Permissions O
The O
following O
permissions O
are O
granted O
to O
the O
app O
: O
Figure O
3 O
– O
Permissions O
Granted O
to O
App O
A O
closer O
look O
at O
the O
code O
reveals O
the O
application O
gathers O
a O
list O
of O
installed O
applications O
to O
compare O
the O
results O
against O
a O
list O
of O
targeted O
applications O
( O
Figure O
4 O
) O
. O
The O
malware O
mainly O
targets O
banking O
and O
financial O
applications O
, O
but O
also O
looks O
for O
popular O
shopping O
apps O
such O
as O
eBay B-Organization
or O
Amazon B-Organization
. O
A O
full O
list O
of O
targeted O
applications O
is O
included O
in O
the O
IOC O
section O
at O
the O
end O
of O
this O
post O
. O
Once O
an O
application O
has O
been O
identified O
, O
Anubis B-Malware
overlays O
the O
original O
application O
with O
a O
fake O
login O
page O
to O
capture O
the O
user O
’ O
s O
credentials O
. O
Figure O
4 O
– O
Checking O
for O
installed O
apps O
Based O
on O
a O
thorough O
analysis O
of O
the O
code O
, O
the O
most O
interesting O
technical O
capabilities O
include O
: O
Capturing O
screenshots O
Enabling O
or O
changing O
administration O
settings O
Opening O
and O
visiting O
any O
URL O
Disabling O
Play O
Protect O
Recording O
audio O
Making O
phone O
calls O
Stealing O
the O
contact O
list O
Controlling O
the O
device O
via O
VNC O
Sending O
, O
receiving O
and O
deleting O
SMS O
Locking O
the O
device O
Encrypting O
files O
on O
the O
device O
and O
external O
drives O
Searching O
for O
files O
Retrieving O
the O
GPS O
location O
Capturing O
remote O
control O
commands O
from O
Twitter B-System
and O
Telegram B-System
Pushing O
overlays O
Reading O
the O
device O
ID O
The O
malware O
includes O
a O
keylogger O
that O
works O
in O
every O
app O
installed O
on O
the O
Android B-System
device O
. O
However O
, O
the O
keylogger O
needs O
to O
be O
specifically O
enabled O
by O
a O
command O
sent O
from O
the O
C2 O
server O
. O
The O
keylogger O
can O
track O
three O
different O
events O
( O
Figure O
5 O
) O
: O
TYPE_VIEW_CLICKED O
Represents O
the O
event O
of O
clicking O
on O
a O
View-like O
Button O
, O
CompoundButton O
, O
etc O
. O
TYPE_VIEW_FOCUSED O
Represents O
the O
event O
of O
setting O
input O
focus O
of O
a O
View O
. O
TYPE_VIEW_TEXT_CHANGED O
Represents O
the O
event O
of O
changing O
the O
text O
of O
an O
EditText O
. O
Figure O
5 O
– O
Keylogger O
component O
Figure O
6 O
shows O
one O
of O
the O
most O
noteworthy O
functions O
of O
Anubis B-Malware
: O
its O
ransomware O
module O
. O
The O
malware O
searches O
both O
internal O
and O
external O
storage O
and O
encrypts O
them O
using O
RC4 O
. O
It O
adds O
the O
file O
extension O
.AnubisCrypt B-Indicator
to O
each O
encrypted O
file O
and O
sends O
it O
to O
the O
C2 O
. O
Figure O
6 O
– O
Ransomware O
component O
Anubis B-Malware
has O
been O
known O
to O
utilize O
Twitter B-Organization
or O
Telegram B-Organization
to O
retrieve O
the O
C2 O
address O
and O
this O
sample O
is O
no O
exception O
( O
Figure O
7 O
) O
. O
Figure O
7 O
– O
C2 O
As O
seen O
in O
Figure O
8 O
, O
this O
version O
of O
Anubis B-Malware
is O
built O
to O
run O
on O
several O
iterations O
of O
the O
Android B-System
operating O
system O
, O
dating O
back O
to O
version O
4.0.3 O
, O
which O
was O
released O
in O
2012 O
. O
Figure O
8 O
– O
Android B-System
requirements O
Android B-System
malware O
has O
been O
around O
for O
many O
years O
and O
will O
be O
with O
us O
for O
the O
foreseeable O
future O
. O
Users O
who O
have O
configured O
their O
Android B-System
mobile O
device O
to O
receive O
work-related O
emails O
and O
allow O
installation O
of O
unsigned O
applications O
face O
the O
most O
risk O
of O
compromise O
. O
APK O
files O
will O
not O
natively O
open O
in O
an O
environment O
other O
than O
an O
Android B-System
device O
. O
With O
the O
increased O
use O
of O
Android B-System
phones O
in O
business O
environments O
, O
it O
is O
important O
to O
defend O
against O
these O
threats O
by O
ensuring O
devices O
are O
kept O
current O
with O
the O
latest O
updates O
. O
Limiting O
app O
installations O
on O
corporate O
devices O
, O
as O
well O
as O
ensuring O
that O
applications O
are O
created O
by O
trusted O
developers O
on O
official O
marketplaces O
, O
can O
help O
in O
reducing O
the O
risk O
of O
infection O
as O
well O
. O
ViceLeaker B-Malware
Operation O
: O
mobile O
espionage O
targeting O
Middle O
East O
26 O
JUN O
2019 O
In O
May O
2018 O
, O
we O
discovered O
a O
campaign O
targeting O
dozens O
of O
mobile O
Android B-System
devices O
belonging O
to O
Israeli O
citizens O
. O
Kaspersky B-Organization
spyware O
sensors O
caught O
the O
signal O
of O
an O
attack O
from O
the O
device O
of O
one O
of O
the O
victims O
; O
and O
a O
hash O
of O
the O
APK O
involved O
( O
Android B-System
application O
) O
was O
tagged O
in O
our O
sample O
feed O
for O
inspection O
. O
Once O
we O
looked O
into O
the O
file O
, O
we O
quickly O
found O
out O
that O
the O
inner-workings O
of O
the O
APK O
included O
a O
malicious O
payload O
, O
embedded O
in O
the O
original O
code O
of O
the O
application O
. O
This O
was O
an O
original O
spyware O
program O
, O
designed O
to O
exfiltrate O
almost O
all O
accessible O
information O
. O
During O
the O
course O
of O
our O
research O
, O
we O
noticed O
that O
we O
were O
not O
the O
only O
ones O
to O
have O
found O
the O
operation O
. O
Researchers O
from O
Bitdefender B-System
also O
released O
an O
analysis O
of O
one O
of O
the O
samples O
in O
a O
blogpost O
. O
Although O
something O
had O
already O
been O
published O
, O
we O
decided O
to O
do O
something O
different O
with O
the O
data O
we O
acquired O
. O
The O
following O
month O
, O
we O
released O
a O
private O
report O
on O
our O
Threat O
Intelligence O
Portal O
to O
alert O
our O
clients O
about O
this O
newly O
discovered O
operation O
and O
began O
writing O
YARA O
rules O
in O
order O
to O
catch O
more O
samples O
. O
We O
decided O
to O
call O
the O
operation O
“ O
ViceLeaker B-Malware
” O
, O
because O
of O
strings O
and O
variables O
in O
its O
code O
. O
Mobile O
ViceLeaker B-Malware
The O
following O
table O
shows O
meta O
information O
on O
the O
observed O
samples O
, O
including O
compiler O
timestamps O
: O
MD5 O
Package O
Compiler O
C2 O
51df2597faa3fce38a4c5ae024f97b1c B-Indicator
com.xapps.SexGameForAdults B-Indicator
dexlib O
2.x O
188.165.28 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
251 I-Indicator
2d108ff3a735dea1d1fdfa430f37fab2 B-Indicator
com.psiphon3 B-Indicator
dexlib O
2.x O
188.165.49 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
7ed754a802f0b6a1740a99683173db73 B-Indicator
com.psiphon3 B-Indicator
dexlib O
2.x O
188.165.49 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
205 I-Indicator
3b89e5cd49c05ce6dc681589e6c368d9 B-Indicator
ir.abed.dastan B-Indicator
dexlib O
2.x O
185.141.60 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
213 I-Indicator
To O
backdoor O
legitimate O
applications O
, O
attackers O
used O
a O
Smali O
injection O
technique O
– O
a O
type O
of O
injection O
that O
allows O
attackers O
to O
disassemble O
the O
code O
of O
original O
app O
with O
the O
Baksmali O
tool O
, O
add O
their O
malicious O
code O
, O
and O
assemble O
it O
with O
Smali O
. O
As O
a O
result O
, O
due O
to O
such O
an O
unusual O
compilation O
process O
, O
there O
were O
signs O
in O
the O
dex O
file O
that O
point O
to O
dexlib O
, O
a O
library O
used O
by O
the O
Smali O
tool O
to O
assemble O
dex O
files O
. O
Original O
code O
of O
the O
APK O
on O
the O
left O
, O
versus O
injected O
APK O
on O
the O
right O
The O
analysis O
of O
the O
APK O
was O
rather O
interesting O
, O
because O
some O
of O
the O
actions O
were O
very O
common O
spyware O
features O
, O
such O
as O
the O
exfiltration O
of O
SMS O
messages O
, O
call O
logs O
and O
other O
data O
. O
However O
, O
in O
addition O
to O
the O
traditional O
functionality O
, O
there O
were O
also O
backdoor O
capabilities O
such O
as O
upload O
, O
download O
, O
delete O
files O
, O
camera O
takeover O
and O
record O
surrounding O
audio O
. O
The O
malware O
uses O
HTTP O
for O
communication O
with O
the O
C2 O
server O
for O
command O
handling O
and O
data O
exfiltration O
. O
Here O
is O
a O
command O
and O
control O
protocol O
fragment O
: O
Commands O
from O
C2 O
server O
parsing O
In O
total O
, O
the O
malicious O
APK O
handles O
16 O
different O
commands O
: O
Command O
Endpoint O
Description O
1 O
reqsmscal.php B-Indicator
Send O
specified O
SMS O
message O
2 O
reqsmscal.php B-Indicator
Call O
specified O
number O
3 O
reqsmscal.php B-Indicator
Exfiltrate O
device O
info O
, O
such O
as O
phone O
model O
and O
OS O
version O
4 O
reqsmscal.php B-Indicator
Exfiltrate O
a O
list O
of O
all O
installed O
applications O
5 O
reqsmscal.php B-Indicator
Exfiltrate O
default O
browser O
history O
( O
limited O
to O
a O
given O
date O
) O
6 O
reqsmscal.php B-Indicator
Exfiltrate O
Chrome O
browser O
history O
( O
limited O
to O
a O
given O
date O
) O
7 O
reqsmscal.php B-Indicator
Exfiltrate O
memory O
card O
file O
structure O
8 O
reqsmscal.php B-Indicator
Record O
surrounding O
sound O
for O
80 O
seconds O
1 O
reqcalllog.php B-Indicator
Exfiltrate O
all O
call O
logs O
2 O
reqcalllog.php B-Indicator
Exfiltrate O
all O
SMS O
messages O
3 O
reqcalllog.php B-Indicator
Upload O
specified O
file O
from O
the O
device O
to O
the O
C2 O
4 O
reqcalllog.php B-Indicator
Download O
file O
from O
specified O
URL O
and O
save O
on O
device O
5 O
reqcalllog.php B-Indicator
Delete O
specified O
file O
6,7,8 O
reqcalllog.php B-Indicator
Commands O
not O
yet O
implemented O
9 O
reqcalllog.php B-Indicator
Take O
photo O
( O
muted O
audio O
) O
with O
rear O
camera O
, O
send O
to O
C2 O
10 O
reqcalllog.php B-Indicator
Take O
photo O
( O
muted O
audio O
) O
with O
front O
camera O
, O
send O
to O
C2 O
All O
observed O
samples O
with O
Smali O
injections O
were O
signed O
by O
the O
same O
debug O
certificate O
( O
0x936eacbe07f201df O
) O
. O
As O
we O
know O
from O
our O
investigation O
, O
traces O
of O
the O
first O
development O
activities O
were O
found O
at O
the O
end O
of O
2016 O
, O
but O
the O
main O
distribution O
campaign O
began O
in O
2018 O
( O
end O
of O
2017 O
) O
. O
Based O
on O
our O
detection O
statistics O
, O
the O
main O
infection O
vector O
is O
the O
spread O
of O
Trojanized O
applications O
directly O
to O
victims O
via O
Telegram O
and O
WhatsApp O
messengers O
. O
There O
are O
the O
following O
relevant O
detection O
paths O
( O
the O
last O
one O
is O
an O
alternative O
Telegram O
client O
– O
“ O
Telegram O
X O
“ O
) O
: O
Name O
Detection O
path O
Sex O
Game O
For O
Adults O
18.apk B-Indicator
/storage/emulated/0/WhatsApp/Media/WhatsApp B-Indicator
Documents/ I-Indicator
4_6032967490689041387.apk I-Indicator
/storage/emulated/0/Telegram/Telegram I-Indicator
Documents/ I-Indicator
Psiphon-v91.apk B-Indicator
/storage/emulated/0/Android/data/org.thunderdog.challegram/files/documents/ B-Indicator
Backdoored O
Open O
Source O
During O
the O
course O
of O
our O
analysis O
, O
we O
also O
found O
samples O
sharing O
code O
with O
the O
ViceLeaker B-Malware
malware O
, O
in O
particular O
they O
shared O
a O
delimiter O
that O
was O
used O
in O
both O
cases O
to O
parse O
commands O
from O
the O
C2 O
server O
. O
This O
would O
be O
a O
very O
unusual O
coincidence O
. O
Even O
when O
a O
false O
flag O
might O
also O
be O
a O
possibility O
, O
we O
consider O
this O
to O
be O
unlikely O
. O
The O
samples O
sharing O
this O
overlap O
are O
modified O
versions O
of O
an O
open O
source O
Jabber/XMPP B-System
client O
called O
“ O
Conversations O
” O
with O
some O
code O
additions O
. O
The O
legitimate O
version O
of O
this O
app O
is O
also O
available O
on O
Google B-System
Play I-System
. O
The O
Conversations O
modified O
samples O
differ O
from O
the O
original O
one O
in O
the O
getKnownHosts O
method O
that O
was O
modified O
to O
replace O
the O
main O
XMPP B-System
host O
with O
the O
attackers O
’ O
C2 O
server O
: O
It O
appears O
that O
the O
attackers O
were O
using O
a O
specific O
C2 O
for O
the O
use O
of O
that O
app O
. O
Another O
important O
modification O
is O
in O
the O
message O
transfer O
process O
: O
With O
this O
modification O
, O
an O
application O
sends O
device O
location O
coordinates O
with O
every O
message O
. O
There O
are O
also O
many O
other O
modifications O
, O
fully O
described O
in O
our O
private O
report O
. O
In O
addition O
, O
we O
did O
not O
see O
traces O
of O
the O
Smali O
injection O
. O
In O
this O
case O
we O
found O
traces O
of O
dx/dexmerge O
compilers O
, O
which O
means O
that O
, O
this O
time O
, O
the O
attackers O
just O
imported O
the O
original O
source O
code O
into O
an O
Android B-System
IDE O
( O
such O
as O
Android B-System
Studio I-System
, O
for O
instance O
) O
and O
compiled O
it O
with O
their O
own O
modifications O
. O
In O
addition O
to O
adding O
the O
code O
, O
the O
attackers O
also O
changed O
the O
icon O
and O
package O
name O
. O
We O
do O
not O
know O
why O
, O
but O
we O
suspect O
that O
it O
was O
an O
attempt O
to O
hide O
the O
origin O
of O
the O
application O
. O
Conversations-based O
app O
mimics O
Telegram B-System
messenger I-System
Even O
when O
we O
originally O
thought O
this O
was O
a O
backdoored O
version O
of O
the O
Conversations O
app O
, O
used O
to O
infect O
victims O
, O
we O
didn´t O
discovered O
anything O
malicious O
in O
it O
. O
This O
brought O
to O
us O
the O
hypothesis O
that O
this O
might O
be O
a O
version O
used O
by O
the O
group O
behind O
ViceLeaker B-Malware
for O
internal O
communication O
or O
for O
other O
, O
unclear O
purposes O
. O
All O
the O
detections O
of O
this O
backdoored O
app O
were O
geolocated O
in O
Iran O
. O
Backdoored O
Conversations O
C2 O
server O
analysis O
During O
the O
analysis O
of O
the O
Smali O
injected O
apps O
and O
their O
C2 O
server O
infrastructure O
we O
hadn O
’ O
t O
found O
any O
interesting O
clues O
, O
but O
things O
changed O
when O
we O
looked O
at O
the O
C2 O
server O
of O
the O
linked O
Conversations O
messenger O
. O
It O
uses O
“ O
185.51.201 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
133 I-Indicator
” O
as O
a O
main O
C2 O
address O
, O
and O
there O
is O
only O
one O
domain O
that O
is O
hosted O
on O
this O
dedicated O
server O
– O
iliageram B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
ir I-Indicator
. O
Note O
that O
we O
later O
found O
versions O
that O
used O
the O
domain O
as O
a O
C2 O
directly O
instead O
of O
the O
IP O
address O
. O
The O
record O
contains O
a O
personal O
email O
address O
: O
WHOIS O
records O
of O
C2 O
server O
exposing O
the O
attacker O
’ O
s O
email O
address O
We O
were O
aware O
of O
the O
possibility O
that O
the O
attackers O
might O
be O
using O
a O
compromised O
email O
account O
, O
so O
we O
dug O
deeper O
to O
find O
more O
information O
related O
to O
this O
email O
address O
. O
A O
quick O
search O
produced O
results O
about O
a O
personal O
page O
and O
, O
what O
is O
more O
interesting O
, O
a O
GitHub B-Organization
account O
that O
contains O
a O
forked O
Conversation O
repository O
. O
Related O
Github B-Organization
account O
contains O
forked O
Conversations O
repository O
Summarizing O
all O
the O
found O
clues O
, O
we O
have O
the O
following O
attribution O
flow O
: O
Conclusion O
The O
operation O
of O
ViceLeaker B-Malware
is O
still O
ongoing O
, O
as O
is O
our O
research O
. O
The O
attackers O
have O
taken O
down O
their O
communication O
channels O
and O
are O
probably O
looking O
for O
ways O
to O
assemble O
their O
tools O
in O
a O
different O
manner O
. O
Kaspersky B-Organization
detects O
and O
blocks O
samples O
of O
the O
ViceLeaker B-Malware
operation O
using O
the O
following O
verdict O
: O
Trojan-Spy.AndroidOS.ViceLeaker B-Indicator
. I-Indicator
* I-Indicator
Actually O
, O
we O
are O
currently O
investigating O
whether O
this O
group O
might O
also O
be O
behind O
a O
large-scale O
web-oriented O
attack O
at O
the O
end O
of O
2018 O
using O
code O
injection O
and O
exploiting O
SQL B-Vulnerability
vulnerabilities I-Vulnerability
. O
Even O
when O
this O
would O
not O
be O
directly O
related O
to O
the O
Android B-System
malware O
described O
in O
this O
blogpost O
, O
it O
would O
be O
an O
indicator O
of O
wider O
capabilities O
and O
objectives O
of O
this O
actor O
. O
XLoader B-Malware
Android B-System
Spyware O
and O
Banking O
Trojan O
Distributed O
via O
DNS O
Spoofing O
We O
have O
been O
detecting O
a O
new O
wave O
of O
network O
attacks O
since O
early O
March O
, O
which O
, O
for O
now O
, O
are O
targeting O
Japan O
, O
Korea O
, O
China O
, O
Taiwan O
, O
and O
Hong O
Kong O
. O
Trend B-Organization
Micro I-Organization
detects O
these O
as O
ANDROIDOS_XLOADER.HRX B-Indicator
. O
By O
: O
Trend B-Organization
Micro I-Organization
April O
20 O
, O
2018 O
We O
have O
been O
detecting O
a O
new O
wave O
of O
network O
attacks O
since O
early O
March O
, O
which O
, O
for O
now O
, O
are O
targeting O
Japan O
, O
Korea O
, O
China O
, O
Taiwan O
, O
and O
Hong O
Kong O
. O
The O
attacks O
use O
Domain O
Name O
System O
( O
DNS O
) O
cache O
poisoning/DNS O
spoofing O
, O
possibly O
through O
infringement O
techniques O
such O
as O
brute-force O
or O
dictionary O
attacks O
, O
to O
distribute O
and O
install O
malicious O
Android B-System
apps O
. O
Trend B-Organization
Micro I-Organization
detects O
these O
as O
ANDROIDOS_XLOADER.HRX B-Indicator
. O
These O
malware O
pose O
as O
legitimate O
Facebook B-System
or O
Chrome B-System
applications O
. O
They O
are O
distributed O
from O
polluted O
DNS O
domains O
that O
send O
a O
notification O
to O
an O
unknowing O
victim O
’ O
s O
device O
. O
The O
malicious O
apps O
can O
steal O
personally O
identifiable O
and O
financial O
data O
and O
install O
additional O
apps O
. O
XLoader B-Malware
can O
also O
hijack O
the O
infected O
device O
( O
i.e. O
, O
send O
SMSs O
) O
and O
sports O
self-protection/persistence O
mechanisms O
through O
device O
administrator O
privileges O
. O
Infection O
Chain O
As O
with O
our O
earlier O
reports O
in O
late O
March O
, O
the O
attack O
chain O
involves O
diverting O
internet O
traffic O
to O
attacker-specified O
domains O
by O
compromising O
and O
overwriting O
the O
router O
’ O
s O
DNS O
settings O
. O
A O
fake O
alert O
will O
notify O
and O
urge O
the O
user O
to O
access O
the O
malicious O
domain O
and O
download O
XLoader B-Malware
. O
Technical O
Analysis O
XLoader B-Malware
first O
loads O
the O
encrypted O
payload O
from O
Assets/db B-Indicator
as O
test.dex B-Indicator
to O
drop O
the O
necessary O
modules O
then O
requests O
for O
device O
administrator O
privileges O
. O
Once O
granted O
permission O
, O
it O
hides O
its O
icon O
from O
the O
launcher O
application O
list O
then O
starts O
a O
service O
that O
it O
keeps O
running O
in O
the O
background O
. O
The O
background O
service O
uses O
the O
reflection O
technique O
( O
a O
feature O
that O
allows O
the O
inspection O
and O
modification O
of O
Java-based O
programs O
’ O
internal O
properties O
) O
to O
invoke O
the O
method O
com.Loader.start B-Indicator
in O
the O
payload O
. O
Monitoring O
Broadcast O
Events O
XLoader B-Malware
registers O
many O
broadcast O
receivers O
in O
the O
payload O
dynamically O
( O
to O
monitor O
broadcast O
events O
sent O
between O
system O
and O
applications O
) O
. O
Registering O
broadcast O
receivers O
enable O
XLoader B-Malware
to O
trigger O
its O
malicious O
routines O
. O
Here O
is O
a O
list O
of O
broadcast O
actions O
: O
android.provider.Telephony.SMS_RECEIVED B-Indicator
android.net.conn.CONNECTIVITY_CHANGE B-Indicator
android.intent.action.BATTERY_CHANGED B-Indicator
android.intent.action.USER_PRESENT B-Indicator
android.intent.action.PHONE_STATE B-Indicator
android.net.wifi.SCAN_RESULTS B-Indicator
android.intent.action.PACKAGE_ADDED B-Indicator
android.intent.action.PACKAGE_REMOVED B-Indicator
android.intent.action.SCREEN_OFF B-Indicator
android.intent.action.SCREEN_ON B-Indicator
android.media.RINGER_MODE_CHANGED B-Indicator
android.sms.msg.action.SMS_SEND B-Indicator
android.sms.msg.action.SMS_DELIVERED B-Indicator
Creating O
a O
Web O
Server O
to O
Phish O
XLoader B-Malware
creates O
a O
provisional O
web O
server O
to O
receive O
the O
broadcast O
events O
. O
It O
can O
also O
create O
a O
simple O
HTTP O
server O
on O
the O
infected O
device O
to O
deceive O
victims O
. O
It O
shows O
a O
web O
phishing O
page O
whenever O
the O
affected O
device O
receives O
a O
broadcast O
event O
( O
i.e. O
, O
if O
a O
new O
package O
is O
installed O
or O
if O
the O
device O
’ O
s O
screen O
is O
on O
) O
to O
steal O
personal O
data O
, O
such O
as O
those O
keyed O
in O
for O
banking O
apps O
. O
The O
phishing O
page O
is O
translated O
in O
Korean O
, O
Japanese O
, O
Chinese O
, O
and O
English O
, O
which O
are O
hardcoded O
in O
the O
payload O
. O
It O
will O
appear O
differently O
to O
users O
depending O
on O
the O
language O
set O
on O
the O
device O
. O
XLoader B-Malware
as O
Spyware O
and O
Banking O
Trojan O
XLoader B-Indicator
can O
also O
collect O
information O
related O
to O
usage O
of O
apps O
installed O
in O
the O
device O
. O
Its O
data-stealing O
capabilities O
include O
collecting O
SMSs O
after O
receiving O
an O
SMS-related O
broadcast O
event O
and O
covertly O
recording O
phone O
calls O
. O
XLoader B-Malware
can O
also O
hijack O
accounts O
linked O
to O
financial O
or O
game-related O
apps O
installed O
on O
the O
affected O
device O
. O
XLoader B-Malware
can O
also O
start O
other O
attacker-specified O
packages O
. O
A O
possible O
attack O
scenario O
involves O
replacing O
legitimate O
apps O
with O
repackaged O
or O
malicious O
versions O
. O
By O
monitoring O
the O
package O
installation O
broadcast O
event O
, O
XLoader B-Malware
can O
start O
their O
packages O
. O
This O
enables O
it O
to O
launch O
malicious O
apps O
without O
the O
user O
’ O
s O
awareness O
and O
explicit O
consent O
. O
We O
reverse O
engineered O
XLoader B-Malware
and O
found O
that O
it O
appears O
to O
target O
South O
Korea-based O
banks O
and O
game O
development O
companies O
. O
XLoader B-Malware
also O
prevents O
victims O
from O
accessing O
the O
device O
’ O
s O
settings O
or O
using O
a O
known O
antivirus O
( O
AV O
) O
app O
in O
the O
country O
. O
XLoader B-Malware
can O
also O
load O
multiple O
malicious O
modules O
to O
receive O
and O
execute O
commands O
from O
its O
remote O
command-and-control O
( O
C O
& O
C O
) O
server O
, O
as O
shown O
below O
: O
Here O
’ O
s O
a O
list O
of O
the O
modules O
and O
their O
functions O
: O
sendSms O
— O
send O
SMS/MMS O
to O
a O
specified O
address O
setWifi O
— O
enable O
or O
disable O
Wi-Fi O
connection O
gcont O
— O
collect O
all O
the O
device O
’ O
s O
contacts O
lock O
— O
currently O
just O
an O
input O
lock O
status O
in O
the O
settings O
( O
pref O
) O
file O
, O
but O
may O
be O
used O
as O
a O
screenlocking O
ransomware O
bc O
— O
collect O
all O
contacts O
from O
the O
Android B-System
device O
and O
SIM O
card O
setForward O
— O
currently O
not O
implemented O
, O
but O
can O
be O
used O
to O
hijack O
the O
infected O
device O
getForward O
— O
currently O
not O
implemented O
, O
but O
can O
be O
used O
to O
hijack O
the O
infected O
device O
hasPkg O
— O
check O
the O
device O
whether O
a O
specified O
app O
is O
installed O
or O
not O
setRingerMode O
— O
set O
the O
device O
’ O
s O
ringer O
mode O
setRecEnable O
— O
set O
the O
device O
’ O
s O
ringer O
mode O
as O
silent O
reqState O
— O
get O
a O
detailed O
phone O
connection O
status O
, O
which O
includes O
activated O
network O
and O
Wi-Fi O
( O
with O
or O
without O
password O
) O
showHome O
— O
force O
the O
device O
’ O
s O
back O
to O
the O
home O
screen O
getnpki O
: O
get O
files/content O
from O
the O
folder O
named O
NPKI O
( O
contains O
certificates O
related O
to O
financial O
transactions O
) O
http O
— O
access O
a O
specified O
network O
using O
HttpURLConnection O
onRecordAction O
— O
simulate O
a O
number-dialed O
tone O
call O
— O
call O
a O
specified O
number O
get_apps O
— O
get O
all O
the O
apps O
installed O
on O
the O
device O
show_fs_float_window O
— O
show O
a O
full-screen O
window O
for O
phishing O
Of O
note O
is O
XLoader B-Malware
’ O
s O
abuse O
of O
the O
WebSocket O
protocol O
( O
supported O
in O
many O
browsers O
and O
web O
applications O
) O
via O
ws O
( O
WebSockets O
) O
or O
wss O
( O
WebSockets O
over O
SSL/TLS O
) O
to O
communicate O
with O
its O
C O
& O
C O
servers O
. O
The O
URLs O
— O
abused O
as O
part O
of O
XLoader B-Malware
’ O
s O
C O
& O
C O
— O
are O
hidden O
in O
three O
webpages O
, O
and O
the O
C O
& O
C O
server O
that O
XLoader B-Malware
connects O
to O
differ O
per O
region O
. O
The O
abuse O
of O
the O
WebSocket O
protocol O
provides O
XLoader B-Malware
with O
a O
persistent O
connection O
between O
clients O
and O
servers O
where O
data O
can O
be O
transported O
any O
time O
. O
XLoader B-Malware
abuses O
the O
MessagePack O
( O
a O
data O
interchange O
format O
) O
to O
package O
the O
stolen O
data O
and O
exfiltrate O
it O
via O
the O
WebSocket O
protocol O
for O
faster O
and O
more O
efficient O
transmission O
. O
Mitigations O
XLoader B-Malware
will O
not O
download O
malicious O
apps O
if O
the O
Android O
device O
uses O
a O
mobile O
data O
connection O
. O
Nevertheless O
, O
users O
should O
practice O
proper O
security O
hygiene O
to O
mitigate O
threats O
that O
may O
take O
advantage O
of O
a O
home O
or O
business O
router O
’ O
s O
security O
gaps O
. O
Employ O
stronger O
credentials O
, O
for O
instance O
, O
to O
make O
them O
less O
susceptible O
to O
unauthorized O
access O
. O
Regularly O
update O
and O
patch O
the O
router O
’ O
s O
software O
and O
firmware O
to O
prevent O
exploits O
, O
and O
enable O
its O
built-in O
firewall O
. O
For O
system O
administrators O
and O
information O
security O
professionals O
, O
configuring O
the O
router O
to O
be O
more O
resistant O
to O
attacks O
like O
DNS O
cache O
poisoning O
can O
help O
mitigate O
similar O
threats O
. O
Everyday O
users O
can O
do O
the O
same O
by O
checking O
the O
router O
’ O
s O
DNS O
settings O
if O
they O
’ O
ve O
been O
modified O
. O
Even O
threats O
like O
DNS O
cache O
poisoning O
employ O
social O
engineering O
, O
so O
users O
should O
also O
be O
more O
prudent O
against O
suspicious O
or O
unknown O
messages O
that O
have O
telltale O
signs O
of O
malware O
. O
We O
have O
worked O
with O
Google B-Organization
and O
they O
ensure O
that O
Google B-System
Play I-System
Protect I-System
proactively O
catches O
apps O
of O
this O
nature O
. O
No O
instances O
of O
these O
apps O
were O
found O
in O
Google B-System
Play I-System
. O
September O
08 O
, O
2020 O
TikTok B-System
Spyware O
A O
detailed O
analysis O
of O
spyware O
masquerading O
as O
TikTok B-System
A O
recent O
threat O
to O
ban O
TikTok B-System
in O
the O
United O
States O
has O
taken O
the O
internet O
by O
storm O
and O
received O
mixed O
reactions O
from O
social O
media O
and O
internet O
users O
. O
U.S. O
President O
Donald O
Trump O
has O
ordered O
ByteDance B-Organization
, O
the O
parent O
company O
of O
TikTok B-System
, O
to O
sell O
its O
U.S. O
TikTok B-System
assets O
and O
also O
issued O
executive O
orders O
that O
would O
ban O
the O
social O
media O
apps O
TikTok B-System
and O
WeChat B-System
from O
operating O
in O
the O
U.S. O
if O
the O
sale O
doesn O
’ O
t O
happen O
in O
the O
next O
few O
weeks O
. O
On O
the O
other O
side O
, O
ByteDance B-Organization
has O
filed O
a O
lawsuit O
suing O
the O
Trump O
administration O
. O
When O
popular O
applications O
come O
under O
fire O
and O
are O
featured O
prominently O
in O
the O
news O
, O
hackers O
get O
excited O
as O
these O
newsworthy O
apps O
can O
become O
their O
latest O
target O
. O
And O
TikTok B-System
is O
no O
exception O
. O
Generally O
, O
after O
an O
application O
gets O
banned O
from O
an O
official O
app O
store O
, O
such O
as O
Google B-System
Play I-System
, O
users O
try O
to O
find O
alternative O
ways O
to O
download O
the O
app O
. O
In O
doing O
so O
, O
users O
can O
become O
victims O
to O
malicious O
apps O
portraying O
themselves O
as O
the O
original O
app O
. O
Recently O
there O
was O
a O
huge O
wave O
of O
SMS O
messages O
, O
as O
well O
as O
Whatsapp B-System
messages O
, O
making O
the O
rounds O
asking O
users O
to O
download O
the O
latest O
version O
of O
TikTok B-System
at O
hxxp B-Indicator
: I-Indicator
//tiny I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cc/TiktokPro I-Indicator
. O
In O
reality O
, O
this O
downloaded O
app O
is O
a O
fake O
app O
that O
asks O
for O
credentials O
and O
Android B-System
permissions O
( O
including O
camera O
and O
phone O
permissions O
) O
, O
resulting O
in O
the O
user O
being O
bombarded O
with O
advertisements O
. O
Recently O
, O
we O
have O
come O
across O
another O
variant O
of O
this O
app O
portraying O
itself O
as O
TikTok B-System
Pro I-System
, O
but O
this O
is O
a O
full-fledged O
spyware O
with O
premium O
features O
to O
spy O
on O
victim O
with O
ease O
. O
( O
Please O
note O
this O
is O
a O
different O
app O
and O
not O
the O
same O
as O
the O
one O
being O
spread O
by O
hxxp B-Indicator
: I-Indicator
//tiny I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
cc/TiktokPro I-Indicator
. I-Indicator
) I-Indicator
Technical O
Analysis O
App O
Name O
: O
TikTok B-System
Pro I-System
Hash O
: O
9fed52ee7312e217bd10d6a156c8b988 B-Indicator
Package O
Name O
: O
com.example.dat.a8andoserverx B-Indicator
Upon O
installation O
, O
the O
spyware O
portrays O
itself O
as O
TikTok B-System
using O
the O
name O
TikTok B-System
Pro I-System
. O
As O
soon O
as O
a O
user O
tries O
to O
open O
the O
app O
, O
it O
launches O
a O
fake O
notification O
and O
soon O
the O
notification O
as O
well O
as O
the O
app O
icon O
disappears O
. O
This O
fake O
notification O
tactic O
is O
used O
to O
redirect O
the O
user O
's O
attention O
, O
meanwhile O
the O
app O
hides O
itself O
, O
making O
the O
user O
believe O
the O
app O
to O
be O
faulty O
. O
This O
functionality O
can O
be O
seen O
in O
Figure O
1 O
. O
App O
Icon O
Figure O
1 O
: O
App O
icon O
and O
fake O
notification O
. O
Behind O
the O
scenes O
, O
there O
are O
number O
of O
process O
occurring O
simultaneously O
. O
First O
, O
an O
activity O
named O
MainActivity O
fires O
up O
, O
taking O
care O
of O
hiding O
the O
icon O
and O
showing O
the O
fake O
notification O
. O
It O
also O
starts O
an O
Android B-System
service O
named O
MainService O
. O
The O
spyware O
also O
appears O
to O
have O
an O
additional O
payload O
stored O
under O
the O
/res/raw/ O
directory O
. O
This O
is O
a O
common O
technique O
used O
by O
malware O
developers O
to O
bundle O
the O
main O
payload O
inside O
the O
Android B-System
package O
to O
avoid O
easy O
detection O
. O
As O
seen O
in O
Figure O
2 O
, O
the O
app O
tries O
to O
open O
the O
payload O
from O
the O
/res/raw/ O
directory O
and O
generate O
an O
additional O
Android B-System
Package I-System
Kit I-System
( O
APK O
) O
named O
.app.apk B-Indicator
: O
Decoy O
Code O
Figure O
2 O
: O
The O
decoy O
code O
for O
the O
fake O
TikTok B-System
. O
Upon O
analysis O
, O
we O
discovered O
that O
this O
is O
a O
decoy O
functionality O
and O
no O
new O
payload O
is O
generated O
. O
The O
conditions O
to O
build O
an O
additional O
payload O
are O
never O
met O
. O
Going O
one O
step O
further O
, O
we O
rebuilt O
the O
malware O
to O
execute O
the O
apparent O
functionality O
of O
generating O
a O
payload O
, O
but O
discovered O
that O
the O
APK O
stored O
in O
the O
/res/raw/ O
directory O
is O
empty O
. O
The O
placement O
of O
the O
decoy O
functionality O
is O
likely O
designed O
to O
confuse O
the O
malware O
researchers O
. O
It O
is O
also O
possible O
that O
this O
functionality O
is O
under O
development O
, O
making O
this O
placeholder O
code O
incomplete O
. O
Coming O
back O
to O
the O
execution O
flow O
, O
once O
the O
spyware O
hides O
itself O
, O
it O
starts O
an O
Android B-System
service O
named O
MainService O
. O
Android B-System
services O
are O
components O
that O
can O
be O
made O
to O
execute O
independently O
in O
the O
background O
without O
the O
victim O
's O
knowledge O
. O
MainService O
is O
the O
brain O
of O
this O
spyware O
and O
controls O
almost O
everything—from O
stealing O
the O
victim O
's O
data O
to O
deleting O
it O
. O
All O
of O
its O
capabilities O
are O
discussed O
later O
in O
this O
blog O
. O
Hide O
Icon O
Figure O
3 O
: O
Code O
showing O
the O
hiding O
icon O
and O
starting O
service O
. O
As O
MainService O
is O
the O
main O
controller O
, O
the O
developer O
has O
taken O
the O
appropriate O
actions O
to O
keep O
it O
functional O
and O
running O
at O
all O
times O
. O
The O
malware O
developer O
uses O
various O
tactics O
to O
do O
so O
, O
and O
one O
of O
them O
is O
using O
Android B-System
's O
broadcast O
receivers O
. O
Broadcast O
receivers O
are O
components O
that O
allow O
you O
to O
register O
for O
various O
Android B-System
events O
. O
In O
this O
case O
, O
it O
registers O
three O
broadcast O
receivers O
: O
MyReceiver O
- O
Triggers O
when O
the O
device O
is O
booted O
. O
Intercept O
Call O
- O
Triggers O
on O
incoming O
and O
outgoing O
calls O
. O
AlarmReceiver O
- O
Triggers O
every O
three O
minutes O
. O
MyReceiver O
and O
AlarmReceiver O
start O
the O
MainService O
whenever O
appropriate O
events O
occur O
. O
This O
tactic O
is O
very O
common O
among O
malware O
developers O
to O
ensure O
the O
malware O
is O
not O
killed O
by O
the O
Android B-System
OS O
or O
by O
any O
other O
means O
. O
Figure O
4 O
shows O
MyReceiver O
in O
action O
where O
it O
eventually O
calls O
the O
MainService O
service O
. O
Broadcast O
Receiver O
Figure O
4 O
: O
MyReceiver O
broadcast O
receiver O
. O
The O
InterceptCall O
receiver O
is O
triggered O
whenever O
there O
is O
an O
incoming O
or O
outgoing O
call O
. O
It O
sets O
particular O
parameters O
in O
relation O
to O
call O
details O
and O
a O
further O
service O
named O
calls O
takes O
the O
control O
as O
seen O
in O
Figure O
5 O
. O
Call O
Service O
Figure O
5 O
: O
Code O
for O
the O
calls O
service O
As O
seen O
above O
, O
the O
calls O
service O
stores O
incoming O
call O
details O
in O
.mp3 O
format O
in O
the O
/sdcard/DCIM/.dat/ O
directory O
with O
file O
name O
appended O
with O
" O
In_ O
'' O
for O
incoming O
calls O
and O
" O
Out_ O
'' O
for O
outgoing O
calls O
. O
How O
these O
recorded O
calls O
are O
sent O
to O
the O
command O
and O
control O
server O
( O
CnC O
) O
is O
taken O
care O
of O
by O
MainService O
, O
which O
is O
discussed O
next O
. O
MainService O
is O
the O
central O
controller O
of O
this O
spyware O
. O
It O
controls O
each O
and O
every O
functionality O
based O
on O
the O
commands O
sent O
by O
the O
command O
and O
control O
( O
C O
& O
C O
) O
server O
. O
As O
soon O
as O
this O
service O
is O
started O
, O
it O
creates O
two O
processes O
that O
take O
care O
of O
connection O
and O
disconnection O
to O
the O
C O
& O
C O
server O
. O
This O
functionality O
can O
be O
seen O
in O
Figure O
6 O
. O
TimerTask O
Figure O
6 O
: O
The O
timer O
task O
. O
MainService O
has O
the O
following O
capabilities O
: O
Steal O
SMS O
messages O
Send O
SMS O
messages O
Steal O
the O
victim O
's O
location O
Capture O
photos O
Execute O
commands O
Capture O
screenshots O
Call O
phone O
numbers O
Initiate O
other O
apps O
Steal O
Facebook B-System
credentials O
, O
etc O
All O
of O
the O
above O
functionalities O
take O
place O
on O
the O
basis O
of O
commands O
sent O
by O
the O
attacker O
. O
Stolen O
data O
is O
stored O
in O
external O
storage O
under O
the O
/DCIM/ O
directory O
with O
a O
hidden O
sub-directory O
named O
" O
.dat O
'' O
. O
Below O
is O
the O
list O
of O
all O
the O
commands O
catered O
by O
the O
C O
& O
C O
server O
. O
Command O
Action O
Unistxcr O
Restart O
the O
app O
dowsizetr O
Send O
the O
file O
stored O
in O
the O
/sdcard/DCIM/.dat/ O
directory O
to O
the O
C O
& O
C O
server O
Caspylistx O
Get O
a O
list O
of O
all O
hidden O
files O
in O
the O
/DCIM/.dat/ O
directory O
spxcheck O
Check O
whether O
call O
details O
are O
collected O
by O
the O
spyware O
S8p8y0 O
Delete O
call O
details O
stored O
by O
the O
spyware O
screXmex O
Take O
screenshots O
of O
the O
device O
screen O
Batrxiops O
Check O
battery O
status O
L4oclOCMAWS O
Fetch O
the O
victim O
's O
location O
GUIFXB O
Launch O
the O
fake O
Facebook B-System
login O
page O
IODBSSUEEZ O
Send O
a O
file O
containing O
stolen O
Facebook B-System
credentials O
to O
the O
C O
& O
C O
server O
FdelSRRT O
Delete O
files O
containing O
stolen O
Facebook B-System
credentials O
chkstzeaw O
Launch O
Facebook B-System
LUNAPXER O
Launch O
apps O
according O
to O
the O
package O
name O
sent O
by O
the O
C O
& O
C O
server O
Gapxplister O
Get O
a O
list O
of O
all O
installed O
applications O
DOTRall8xxe O
Zip O
all O
the O
stolen O
files O
and O
store O
in O
the O
/DCIM/.dat/ O
directory O
Acouxacour O
Get O
a O
list O
of O
accounts O
on O
the O
victim O
's O
device O
Fimxmiisx O
Open O
the O
camera O
Scxreexcv4 O
Capture O
an O
image O
micmokmi8x O
Capture O
audio O
Yufsssp O
Get O
latitude O
and O
longitude O
GExCaalsss7 O
Get O
call O
logs O
PHOCAs7 O
Call O
phone O
numbers O
sent O
by O
the O
C O
& O
C O
server O
Gxextsxms O
Get O
a O
list O
of O
inbox O
SMS O
messages O
Msppossag O
Send O
SMS O
with O
message O
body O
sent O
by O
the O
C O
& O
C O
server O
Getconstactx O
Get O
a O
list O
of O
all O
contacts O
Rinxgosa O
Play O
a O
ringtone O
bithsssp64 O
Execute O
commands O
sent O
by O
the O
C O
& O
C O
server O
DOWdeletx O
Deletes O
the O
file O
specified O
by O
the O
C O
& O
C O
server O
Deldatall8 O
Delete O
all O
files O
stored O
in O
the O
/sdcard/DCIM/.dat/ O
directory O
We O
do O
n't O
have O
the O
space O
to O
cover O
all O
of O
the O
commands O
, O
but O
let O
's O
take O
a O
look O
at O
some O
of O
the O
major O
ones O
. O
Facebook B-System
phishing O
One O
of O
the O
interesting O
features O
of O
this O
spyware O
is O
the O
ability O
to O
steal O
Facebook B-System
credentials O
using O
a O
fake O
login O
page O
, O
similar O
to O
phishing O
. O
Upon O
receiving O
the O
command O
GUIFXB O
, O
the O
spyware O
launches O
a O
fake O
Facebook B-System
login O
page O
. O
As O
soon O
as O
the O
victim O
tries O
to O
log O
in O
, O
it O
stores O
the O
victim O
's O
credentials O
in O
/storage/0/DCIM/.fdat O
Facebook B-System
Login O
Figure O
7 O
: O
Fake O
Facebook B-System
login O
The O
second O
command O
is O
IODBSSUEEZ O
, O
which O
further O
sends O
stolen O
credentials O
to O
the O
C O
& O
C O
server O
, O
as O
seen O
in O
Figure O
8 O
. O
Stolen O
Data O
Figure O
8 O
: O
Sending O
data O
to O
the O
attacker O
. O
This O
functionality O
can O
be O
easily O
further O
extended O
to O
steal O
other O
information O
, O
such O
as O
bank O
credentials O
, O
although O
we O
did O
not O
see O
any O
banks O
being O
targeted O
in O
this O
attack O
. O
Calling O
functionality O
Command O
PHOCAs7 O
initiates O
calling O
functionality O
. O
The O
number O
to O
call O
is O
received O
along O
with O
the O
command O
, O
as O
seen O
in O
Figure O
9 O
. O
Call O
Command O
Figure O
9 O
: O
The O
calling O
functionality O
. O
The O
phone O
number O
is O
fetched O
from O
a O
response O
from O
the O
C O
& O
C O
server O
and O
is O
stored O
in O
str3 O
variable O
, O
which O
further O
is O
utilized O
using O
the O
tel O
: O
function O
. O
Stealing O
SMS O
The O
Gxextsxms O
command O
is O
responsible O
for O
fetching O
all O
the O
SMS O
messages O
from O
the O
victim O
's O
device O
and O
sending O
it O
over O
to O
the O
C O
& O
C O
server O
. O
Stealing O
SMS O
Figure O
10 O
: O
Stealing O
SMS O
messages O
. O
Similarly O
, O
there O
are O
many O
crucial O
commands O
that O
further O
allow O
this O
spyware O
to O
perform O
additional O
functionality O
, O
such O
as O
executing O
commands O
sent O
by O
the O
C O
& O
C O
, O
clicking O
photos O
, O
capturing O
screenshots O
, O
stealing O
location O
information O
, O
and O
more O
. O
Further O
analysis O
Upon O
further O
research O
, O
we O
found O
this O
spyware O
to O
be O
developed O
by O
a O
framework O
similar O
to O
Spynote B-Malware
and O
Spymax B-Malware
, O
meaning O
this O
could O
be O
an O
updated O
version O
of O
these O
Trojan O
builders O
, O
which O
allow O
anyone O
, O
even O
with O
limited O
knowledge O
, O
to O
develop O
full-fledged O
spyware O
. O
Many O
of O
the O
functionalities O
seen O
in O
this O
spyware O
are O
similar O
to O
Spynote B-Malware
and O
Spymax B-Malware
based O
on O
the O
samples O
we O
analyzed O
with O
some O
modifications O
. O
This O
spyware O
sample O
communicates O
over O
dynamic O
DNS O
. O
By O
doing O
so O
, O
attackers O
can O
easily O
set O
up O
the O
Trojan O
to O
communicate O
back O
to O
them O
without O
any O
need O
for O
high-end O
servers O
. O
Other O
common O
functionalities O
include O
executing O
commands O
received O
from O
the O
attacker O
, O
taking O
screenshots O
of O
the O
victim O
's O
device O
, O
fetching O
locations O
, O
stealing O
SMS O
messages O
and O
most O
common O
features O
that O
every O
spyware O
may O
poses O
. O
Stealing O
Facebook B-Organization
credentials O
using O
fake O
Facebook B-Organization
activity O
is O
something O
we O
did O
n't O
observe O
in O
Spynote/Spymax B-Malware
versions O
but O
was O
seen O
in O
this O
spyware O
. O
This O
framework O
allows O
anyone O
to O
develop O
a O
malicious O
app O
with O
the O
desired O
icon O
and O
communication O
address O
. O
Some O
of O
the O
icons O
used O
can O
be O
seen O
below O
. O
We O
found O
280 O
such O
apps O
in O
the O
past O
three O
months O
. O
A O
complete O
list O
of O
hashes O
can O
be O
found O
here O
. O
icons O
Figure O
11 O
: O
Icons O
used O
to O
pose O
as O
famous O
apps O
. O
All O
of O
these O
apps O
are O
developed O
by O
the O
same O
framework O
and O
hence O
have O
the O
same O
package O
name O
and O
certificate O
information O
as O
seen O
in O
Figure O
12. O
certificate O
Figure O
12 O
: O
Package O
name O
and O
certificate O
information O
. O
Conclusion O
Due O
to O
the O
ubiquitous O
nature O
of O
mobile O
devices O
and O
the O
widespread O
use O
of O
Android B-System
, O
it O
is O
very O
easy O
for O
attackers O
to O
victimize O
Android B-System
users O
. O
In O
such O
situations O
, O
mobile O
users O
should O
always O
take O
the O
utmost O
precautions O
while O
downloading O
any O
applications O
from O
the O
internet O
. O
It O
is O
very O
easy O
to O
trick O
victims O
to O
fall O
for O
such O
attacks O
. O
Users O
looking O
forward O
to O
using O
the O
TikTok B-System
app O
amidst O
the O
ban O
might O
look O
for O
alternative O
methods O
to O
download O
the O
app O
. O
In O
doing O
so O
, O
users O
can O
mistakenly O
install O
malicious O
apps O
, O
such O
as O
the O
spyware O
mentioned O
in O
this O
blog O
. O
The O
precautions O
you O
take O
online O
have O
been O
covered O
extensively O
in O
almost O
all O
of O
our O
blogs O
; O
even O
so O
, O
we O
believe O
this O
information O
bears O
repeating O
. O
Please O
follow O
these O
basic O
precautions O
during O
the O
current O
crisis—and O
at O
all O
times O
: O
Install O
apps O
only O
from O
official O
stores O
, O
such O
as O
Google B-System
Play I-System
. O
Never O
click O
on O
unknown O
links O
received O
through O
ads O
, O
SMS O
messages O
, O
emails O
, O
or O
the O
like O
. O
Always O
keep O
the O
" O
Unknown O
Sources O
'' O
option O
disabled O
in O
the O
Android B-System
device O
. O
This O
disallows O
apps O
to O
be O
installed O
on O
your O
device O
from O
unknown O
sources O
. O
We O
would O
also O
like O
to O
mention O
that O
if O
you O
come O
across O
an O
app O
hiding O
it O
's O
icon O
, O
always O
try O
to O
search O
for O
the O
app O
in O
your O
device O
settings O
( O
by O
going O
to O
Settings O
- O
> O
Apps O
- O
> O
Search O
for O
icon O
that O
was O
hidden O
) O
. O
In O
the O
case O
of O
this O
spyware O
, O
search O
for O
app O
named O
TikTok B-System
Pro I-System
. O
MITRE B-Organization
TAGS O
Action O
Tag O
ID O
App O
auto-start O
at O
device O
boot O
T1402 O
Input O
prompt O
T1411 O
Capture O
SMS O
messages O
T1412 O
Application O
discovery O
T1418 O
Capture O
audio O
T1429 O
Location O
tracking O
T1430 O
Access O
contact O
list O
T1432 O
Access O
call O
log O
T1433 O
Commonly O
used O
port O
T1436 O
Standard O
application O
layer O
protocol O
T1437 O
Masquerage O
as O
legitimate O
application O
T1444 O
Suppress O
application O
icon O
T1508 O
Capture O
camera O
T1512 O
Screen O
capture O
T1513 O
Foreground O
persistence O
T1541 O
DualToy B-Malware
: O
New O
Windows B-System
Trojan O
Sideloads O
Risky O
Apps O
to O
Android B-System
and O
iOS B-System
Devices O
By O
Claud O
Xiao O
September O
13 O
, O
2016 O
at O
5:00 O
AM O
Over O
the O
past O
two O
years O
, O
we O
’ O
ve O
observed O
many O
cases O
of O
Microsoft B-System
Windows I-System
and O
Apple B-System
iOS I-System
malware O
designed O
to O
attack O
mobile O
devices O
. O
This O
attack O
vector O
is O
increasingly O
popular O
with O
malicious O
actors O
as O
almost O
everyone O
on O
the O
planet O
carries O
at O
least O
one O
mobile O
device O
they O
interact O
with O
throughout O
any O
given O
day O
. O
Thanks O
to O
a O
relative O
lack O
of O
security O
controls O
applied O
to O
mobile O
devices O
, O
these O
devices O
have O
become O
very O
attractive O
targets O
for O
a O
broad O
range O
of O
malicious O
actors O
. O
For O
example O
: O
WireLurker B-Malware
installed O
malicious O
apps O
on O
non-jailbroken O
iPhones O
Six O
different O
Trojan O
, O
Adware O
and O
HackTool B-Malware
families I-Malware
launched O
“ O
BackStab O
” O
attacks O
to O
steal O
backup O
archives O
of O
iOS B-System
and O
BlackBerry B-System
devices O
The O
HackingTeam B-Malware
’ O
s O
RCS B-Malware
delivered O
its O
Spyware O
from O
infected O
PCs O
and O
Macs O
to O
jailbroken O
iOS B-System
devices O
and O
BlackBerry B-System
phones O
Recently O
, O
we O
discovered O
another O
Windows B-System
Trojan O
we O
named O
“ O
DualToy B-Malware
” O
which O
side O
loads O
malicious O
or O
risky O
apps O
to O
both O
Android B-System
and O
iOS B-System
devices O
via O
a O
USB B-System
connection O
. O
When O
DualToy B-Malware
began O
to O
spread O
in O
January O
2015 O
, O
it O
was O
only O
capable O
of O
infecting O
Android B-System
devices O
. O
However O
, O
within O
six O
months O
the O
malicious O
actors O
added O
the O
capability O
to O
infect O
iOS B-System
devices O
. O
DualToy B-Malware
is O
still O
active O
and O
we O
have O
detected O
over O
8,000 O
unique O
samples O
belonging O
to O
this O
Trojan O
family O
to O
date O
. O
It O
mainly O
targets O
Chinese O
users O
, O
but O
has O
also O
successfully O
affected O
people O
and O
organizations O
in O
the O
United O
States O
, O
United O
Kingdom O
, O
Thailand O
, O
Spain O
, O
and O
Ireland O
. O
Credential O
phishing O
and O
an O
Android B-System
banking O
Trojan O
combine O
in O
Austrian O
mobile O
attacks O
NOVEMBER O
03 O
, O
2017 O
Overview O
Credential O
phishing O
, O
banking O
Trojans O
, O
and O
credit O
card O
phishing O
schemes O
are O
common O
threats O
that O
we O
regularly O
observe O
both O
at O
scale O
and O
in O
more O
targeted O
attacks O
. O
However O
, O
Proofpoint B-Organization
researchers O
have O
recently O
observed O
phishing O
attacks O
that O
incorporate O
all O
of O
these O
elements O
in O
a O
single O
, O
multistep O
scheme O
involving O
the O
Marcher B-Malware
Android O
banking O
Trojan O
targeting O
customers O
of O
large O
Austrian O
banks O
. O
Attacks O
involving O
Marcher B-Malware
have O
become O
increasingly O
sophisticated O
, O
with O
documented O
cases O
involving O
multiple O
attack O
vectors O
and O
a O
variety O
of O
targeted O
financial O
services O
and O
communication O
platforms O
[ O
1 O
] O
[ O
2 O
] O
. O
In O
this O
case O
, O
a O
threat O
actor O
has O
been O
targeting O
customers O
of O
Bank O
Austria O
, O
Raiffeisen O
Meine O
Bank O
, O
and O
Sparkasse O
since O
at O
least O
January O
2017 O
. O
The O
attacks O
described O
here O
begin O
with O
a O
banking O
credential O
phishing O
scheme O
, O
followed O
by O
an O
attempt O
to O
trick O
the O
victim O
into O
installing O
Marcher B-Malware
, O
and O
finally O
with O
attempts O
to O
steal O
credit O
card O
information O
by O
the O
banking O
Trojan O
itself O
. O
Analysis O
Marcher B-Malware
is O
frequently O
distributed O
via O
SMS O
, O
but O
in O
this O
case O
, O
victims O
are O
presented O
with O
a O
link O
in O
an O
email O
. O
Oftentimes O
, O
the O
emailed O
link O
is O
a O
bit.ly O
shortened O
link O
, O
used O
to O
potentially O
evade O
detection O
. O
The O
link O
leads O
to O
a O
phishing O
page O
that O
asks O
for O
banking O
login O
credentials O
or O
an O
account O
number O
and O
PIN O
. O
Figure O
1 O
shows O
one O
such O
landing O
page O
using O
stolen O
branding O
from O
Bank O
Austria O
. O
Figure O
1 O
: O
Landing O
page O
for O
phishing O
scheme O
asking O
for O
the O
victim O
’ O
s O
signatory O
number O
and O
PIN O
using O
stolen O
branding O
from O
Bank B-System
Austria I-System
Because O
the O
actor O
delivered O
phishing O
links O
using O
the O
bit.ly B-Indicator
URL O
shortener O
, O
we O
can O
access O
delivery O
statistics O
for O
this O
particular O
campaign O
. O
The O
link O
resolves O
to O
a O
URL O
designed O
to O
appear O
legitimate O
, O
with O
a O
canonical O
domain O
of O
sicher97140 B-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
info I-Indicator
including O
the O
“ O
bankaustria O
” O
brand O
. O
Figure O
2 O
: O
Bit.ly B-Indicator
statistics O
for O
a O
phishing O
landing O
page O
targeting O
Bank B-System
Austria I-System
customers O
The O
actor O
appears O
to O
have O
recently O
begun O
using O
“ O
.top O
” O
top-level O
domains O
( O
TLDs O
) O
for O
their O
phishing O
landing O
pages O
and O
have O
implemented O
a O
consistent O
naming O
structure O
as O
shown O
below O
. O
Earlier O
this O
year O
, O
the O
actor O
used O
“ O
.pw O
” O
TLDs O
while O
the O
Bank B-System
Austria I-System
scheme O
highlighted O
above O
used O
“ O
.info O
” O
. O
Some O
recent O
campaigns O
against O
other O
bank O
customers O
also O
used O
“ O
.gdn O
” O
TLDs O
. O
Other O
attacks O
on O
Bank B-System
Austria I-System
customers O
that O
we O
observed O
resolved O
to O
the O
following O
.top O
domains O
: O
Oct O
23 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id8817062 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
23 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id8817461 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
23 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
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[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
23 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id8817466 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
23 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id8817469 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id58712 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id58717 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id58729 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id58729 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id87721 I-Indicator
[ I-Indicator
. I-Indicator
] I-Indicator
top/ I-Indicator
Oct O
17 O
, O
2017 O
hxxp B-Indicator
: I-Indicator
//online.bankaustria.at.id87726 I-Indicator
[ I-Indicator
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] I-Indicator
top/ I-Indicator
These O
permutations O
of O
TLDs O
and O
canonical O
domains O
incorporating O
the O
legitimate O
domain O
expected O
by O
the O
targeted O
banking O
customers O
exemplifies O
recent O
trends O
in O
social O
engineering O
by O
threat O
actors O
. O
Just O
as O
threat O
actors O
may O
use O
stolen O
branding O
in O
their O
email O
lures O
to O
trick O
potential O
victims O
, O
they O
reproduce O
a O
legitimate O
domain O
name O
in O
a O
fraudulent O
domain O
that O
is O
not O
controlled O
by O
the O
bank O
. O
Once O
the O
victim O
enters O
their O
account O
information O
on O
the O
landing O
page O
, O
the O
phishing O
attack O
then O
requests O
that O
the O
user O
log O
in O
with O
their O
email O
address O
and O
phone O
number O
. O
Figure O
3 O
: O
Step O
two O
of O
the O
credential O
phish O
asking O
for O
the O
victim O
’ O
s O
email O
address O
and O
phone O
number O
Having O
stolen O
the O
victim O
’ O
s O
account O
and O
personal O
information O
, O
the O
scammer O
introduces O
a O
social O
engineering O
scheme O
, O
informing O
users O
that O
they O
currently O
do O
not O
have O
the O
“ O
Bank B-System
Austria I-System
Security I-System
App I-System
” O
installed O
on O
their O
smartphone O
and O
must O
download O
it O
to O
proceed O
. O
Figure O
4 O
shows O
the O
download O
prompt O
for O
this O
fake O
app O
; O
an O
English O
translation O
follows O
. O
Figure O
4 O
: O
Alert O
prompting O
the O
victim O
to O
download O
an O
Android B-System
banking I-System
app I-System
( O
English O
translation O
below O
) O
, O
with O
stolen O
branding O
and O
fraudulent O
copy O
* O
* O
* O
Translation O
* O
* O
* O
Dear O
Customer O
, O
The O
system O
has O
detected O
that O
the O
Bank B-System
Austria I-System
Security I-System
App I-System
is O
not O
installed O
on O
your O
smartphone O
. O
Due O
to O
new O
EU B-Organization
money O
laundering O
guidelines O
, O
the O
new O
Bank B-System
Austria I-System
security I-System
app I-System
is O
mandatory O
for O
all O
customers O
who O
have O
a O
mobile O
phone O
number O
in O
our O
system O
. O
Please O
install O
the O
app O
immediately O
to O
avoid O
blocking O
your O
account O
. O
Follow O
the O
instructions O
at O
the O
bottom O
of O
this O
page O
. O
Why O
you O
need O
the O
Bank B-System
Austria I-System
Security I-System
App I-System
: O
Due O
to O
outdated O
technology O
of O
the O
mobile O
network O
important O
data O
such O
as O
mTan O
SMS O
and O
online O
banking O
connections O
are O
transmitted O
unencrypted O
. O
Our O
security O
app O
allows O
us O
to O
transmit O
this O
sensitive O
data O
encrypted O
to O
you O
, O
thus O
increasing O
the O
security O
that O
you O
will O
not O
suffer O
any O
financial O
loss O
. O
Step O
1 O
: O
Download O
Bank B-System
Austria I-System
Security I-System
App I-System
Download O
the O
Bank O
Austria O
security O
app O
to O
your O
Android O
device O
. O
To O
do O
this O
, O
open O
the O
displayed O
link O
on O
your O
mobile O
phone O
by O
typing O
in O
the O
URL O
field O
of O
your O
browser O
or O
scan O
the O
displayed O
QR O
code O
. O
* O
* O
* O
End O
translation O
* O
* O
* O
The O
phishing O
template O
then O
presents O
additional O
instructions O
for O
installing O
the O
fake O
security O
application O
( O
Figure O
5 O
) O
: O
Figure O
5 O
: O
Additional O
instructions O
telling O
the O
victim O
to O
give O
the O
app O
the O
requested O
permissions O
( O
English O
translation O
below O
) O
, O
with O
stolen O
branding O
and O
fraudulent O
copy O
* O
* O
* O
Translation O
* O
* O
* O
Step O
2 O
: O
Allow O
installation O
Open O
your O
device O
's O
settings O
, O
select O
Security O
or O
Applications O
( O
depending O
on O
the O
device O
) O
, O
and O
check O
Unknown O
sources O
. O
Step O
3 O
: O
Run O
installation O
Start O
the O
Bank B-System
Austria I-System
security I-System
app I-System
from O
the O
notifications O
or O
your O
download O
folder O
, O
tap O
Install O
. O
After O
successful O
installation O
, O
tap O
Open O
and O
enable O
the O
device O
administrator O
. O
Finished O
! O
* O
* O
* O
End O
translation O
* O
* O
* O
Referring O
again O
to O
bit.ly B-Indicator
, O
we O
can O
see O
click O
statistics O
for O
this O
campaign O
( O
Figure O
6 O
) O
. O
Figure O
6 O
: O
bit.ly B-Indicator
statistics O
for O
the O
fake O
Bank B-System
Austria I-System
Android I-System
app I-System
download O
link O
From O
this O
small O
sample O
, O
we O
see O
that O
7 O
% O
of O
visitors O
clicked O
through O
to O
download O
the O
application O
, O
which O
is O
actually O
a O
version O
of O
the O
Marcher B-Malware
banking I-Malware
Trojan I-Malware
named O
“ O
BankAustria.apk B-Indicator
” O
, O
continuing O
the O
fraudulent O
use O
of O
the O
bank O
’ O
s O
branding O
to O
fool O
potential O
victims O
. O
This O
sample O
is O
similar O
to O
those O
presented O
in O
other O
recent O
Marcher B-Malware
analyses O
[ O
1 O
] O
[ O
2 O
] O
. O
This O
particular O
application O
is O
signed O
with O
a O
fake O
certificate O
: O
Owner O
: O
CN=Unknown O
, O
OU=Unknown O
, O
O=Unknown O
, O
L=Unknown O
, O
ST=Unknown O
, O
C=Unknown O
Issuer O
CN=Unknown O
, O
OU=Unknown O
, O
O=Unknown O
, O
L=Unknown O
, O
ST=Unknown O
, O
C=Unknown O
Serial O
: O
1c9157d7 O
Validity O
: O
11/02/2017 O
00:16:46 O
03/20/2045 O
00:16:46 O
MD5 O
Hash O
: O
A8:55:46:32:15 B-Indicator
: I-Indicator
A9 I-Indicator
: I-Indicator
D5:95 I-Indicator
: I-Indicator
A9:91 I-Indicator
: I-Indicator
C2:91:77:5D:30 I-Indicator
: I-Indicator
F6 I-Indicator
SHA1 O
Hash O
: O
32:17 B-Indicator
: I-Indicator
E9:7E:06 I-Indicator
: I-Indicator
FE:5D:84 I-Indicator
: I-Indicator
BE:7C:14:0C I-Indicator
: I-Indicator
C6:2B:12:85 I-Indicator
: I-Indicator
E7:03:9A:5F I-Indicator
The O
app O
requests O
extensive O
permissions O
during O
installation O
that O
enable O
a O
range O
of O
activities O
supported O
by O
the O
malware O
. O
Those O
permission O
shown O
in O
bold O
below O
are O
the O
most O
problematic O
: O
Allows O
an O
application O
to O
write O
to O
external O
storage O
. O
Allows O
an O
application O
to O
read O
from O
external O
storage O
. O
Allows O
an O
application O
to O
use O
SIP O
service O
. O
Allows O
an O
application O
to O
collect O
battery O
statistics O
Allows O
an O
app O
to O
access O
precise O
location O
. O
Allows O
an O
application O
to O
receive O
SMS O
messages O
. O
Allows O
an O
application O
to O
send O
SMS O
messages O
. O
Allows O
an O
application O
to O
read O
SMS O
messages O
. O
Allows O
an O
application O
to O
write O
SMS O
messages O
. O
Allows O
an O
application O
to O
initiate O
a O
phone O
call O
without O
going O
through O
the O
Dialer O
user O
interface O
for O
the O
user O
to O
confirm O
the O
call O
. O
Allows O
applications O
to O
access O
information O
about O
networks O
. O
Allows O
applications O
to O
open O
network O
sockets O
. O
Allows O
an O
application O
to O
read O
the O
user O
's O
contacts O
data O
. O
Allows O
an O
application O
to O
read O
or O
write O
the O
system O
settings O
. O
Allows O
an O
application O
to O
force O
the O
device O
to O
lock O
Allows O
applications O
to O
access O
information O
about O
Wi-Fi O
networks O
. O
Allows O
applications O
to O
change O
Wi-Fi O
connectivity O
state O
. O
Allows O
applications O
to O
change O
network O
connectivity O
state O
. O
Analysis O
of O
the O
malware O
shows O
that O
it O
uses O
the O
common O
string O
obfuscation O
of O
character O
replacement O
( O
Figure O
7 O
) O
: O
Figure O
7 O
: O
Encoded O
Marcher B-Malware
Strings O
Figure O
8 O
: O
Decoded O
Marcher B-Malware
Strings O
As O
noted O
, O
the O
application O
requests O
extensive O
permissions O
during O
installation O
; O
Figure O
9 O
shows O
the O
request O
to O
act O
as O
device O
administrator O
, O
a O
particular O
permission O
that O
should O
very O
rarely O
be O
granted O
to O
an O
app O
. O
Figure O
9 O
: O
Prompt O
for O
application O
permissions O
upon O
installation O
Figures O
10 O
and O
11 O
show O
the O
other O
permission O
screens O
for O
the O
app O
: O
Figure O
10 O
Figure O
10 O
: O
Part O
1 O
of O
the O
permission O
screen O
for O
the O
app O
Figure O
11 O
: O
Part O
2 O
of O
the O
permission O
screen O
for O
the O
app O
Once O
installed O
the O
app O
will O
place O
a O
legitimate O
looking O
icon O
on O
the O
phone O
’ O
s O
home O
screen O
, O
again O
using O
branding O
stolen O
from O
the O
bank O
. O
Figure O
12 O
: O
Fake B-System
Bank I-System
Austria I-System
Security I-System
application I-System
icon O
In O
addition O
to O
operating O
as O
a O
banking O
Trojan O
, O
overlaying O
a O
legitimate O
banking O
app O
with O
an O
indistinguishable O
credential O
theft O
page O
, O
the O
malware O
also O
asks O
for O
credit O
card O
information O
from O
the O
user O
when O
they O
open O
applications O
such O
as O
the O
Google B-System
Play I-System
store O
. O
Figure O
13 O
: O
Popup O
asking O
for O
a O
credit O
card O
number O
The O
application O
also O
supports O
stealing O
credit O
card O
verification O
information O
( O
Figures O
14 O
and O
15 O
) O
. O
Figure O
14 O
: O
Information O
theft O
via O
fake O
credit O
card O
verification O
using O
stolen O
branding O
Figure O
15 O
: O
Information O
theft O
via O
fake O
credit O
card O
verification O
using O
stolen O
branding O
Some O
of O
the O
campaigns O
appear O
to O
have O
a O
wider O
reach O
based O
on O
bit.ly B-Indicator
statistics O
like O
this O
one O
from O
October O
13 O
, O
2017 O
: O
Figure O
16 O
: O
bit.ly B-Indicator
statistics O
for O
an O
October O
13 O
, O
2017 O
campaign O
Over O
several O
days O
during O
the O
last O
three O
months O
, O
Proofpoint B-Organization
researchers O
observed O
campaigns O
using O
similar O
techniques O
targeting O
the O
banking O
customers O
of O
Raffeisen O
and O
Sparkasse O
. O
A O
review O
of O
the O
bit.ly B-Indicator
statistics O
for O
these O
campaigns O
shows O
that O
they O
were O
at O
least O
as O
effective O
in O
driving O
end-user O
clicks O
as O
the O
Bank B-System
Austria I-System
campaign O
analyzed O
above O
. O
Conclusion O
As O
our O
computing O
increasingly O
crosses O
multiple O
screens O
, O
we O
should O
expect O
to O
see O
threats O
extending O
across O
mobile O
and O
desktop O
environments O
. O
Moreover O
, O
as O
we O
use O
mobile O
devices O
to O
access O
the O
web O
and O
phishing O
templates O
extend O
to O
mobile O
environments O
, O
we O
should O
expect O
to O
see O
a O
greater O
variety O
of O
integrated O
threats O
like O
the O
scheme O
we O
detail O
here O
. O
As O
on O
the O
desktop O
, O
mobile O
users O
need O
to O
be O
wary O
of O
installing O
applications O
from O
outside O
of O
legitimate O
app O
stores O
and O
sources O
and O
be O
on O
the O
lookout O
for O
bogus O
banking O
sites O
that O
ask O
for O
more O
information O
than O
users O
would O
normally O
provide O
on O
legitimate O
sites O
. O
Unusual O
domains O
, O
the O
use O
of O
URL O
shorteners O
, O
and O
solicitations O
that O
do O
not O
come O
from O
verifiable O
sources O
are O
also O
red O
flags O
for O
potential O
phishing O
and O
malware O
. O
Ginp B-Malware
- O
A O
malware O
patchwork O
borrowing O
from O
Anubis B-Malware
November O
2019 O
Intro O
ThreatFabric B-System
analysts O
have O
recently O
investigated O
an O
interesting O
new O
strain O
of O
banking O
malware O
. O
The O
malware O
was O
first O
spotted O
by O
Tatyana O
Shishkova O
from O
Kaspersky B-Organization
by O
end O
October O
2019 O
, O
but O
actually O
dates O
back O
to O
June O
2019 O
. O
It O
is O
still O
under O
active O
development O
, O
with O
at O
least O
5 O
different O
versions O
of O
the O
Trojan O
released O
within O
the O
last O
5 O
months O
( O
June O
- O
November O
2019 O
) O
. O
What O
makes O
Ginp B-Malware
stand O
out O
is O
that O
it O
was O
built O
from O
scratch O
being O
expanded O
through O
regular O
updates O
, O
the O
last O
of O
which O
including O
code O
copied O
from O
the O
infamous O
Anubis B-Malware
banking O
Trojan O
, O
indicating O
that O
its O
author O
is O
cherry-picking O
the O
most O
relevant O
functionality O
for O
its O
malware O
. O
In O
addition O
, O
its O
original O
target O
list O
is O
extremely O
narrow O
and O
seems O
to O
be O
focused O
on O
Spanish O
banks O
. O
Last O
but O
not O
least O
, O
all O
the O
overlay O
screens O
( O
injects O
) O
for O
the O
banks O
include O
two O
steps O
; O
first O
stealing O
the O
victim O
’ O
s O
login O
credentials O
, O
then O
their O
credit O
card O
details O
. O
Although O
multi-step O
overlays O
are O
not O
something O
new O
, O
their O
usage O
is O
generally O
limited O
to O
avoid O
raising O
suspicion O
. O
Evolution O
The O
initial O
version O
of O
the O
malware O
dates O
back O
to O
early O
June O
2019 O
, O
masquerading O
as O
a O
“ O
Google B-System
Play I-System
Verificator I-System
” O
app O
. O
At O
that O
time O
, O
Ginp B-Malware
was O
a O
simple O
SMS O
stealer O
whose O
purpose O
was O
only O
to O
send O
a O
copy O
of O
incoming O
and O
outgoing O
SMS O
messages O
to O
the O
C2 O
server O
. O
A O
couple O
of O
months O
later O
, O
in O
August O
2019 O
, O
a O
new O
version O
was O
released O
with O
additional O
banking-specific O
features O
. O
This O
and O
following O
versions O
were O
masquerading O
as O
fake O
“ O
Adobe B-System
Flash I-System
Player I-System
” O
apps O
. O
The O
malware O
was O
able O
to O
perform O
overlay O
attacks O
and O
become O
the O
default O
SMS O
app O
through O
the O
abuse O
of O
the O
Accessibility O
Service O
. O
The O
overlay O
consisted O
of O
a O
generic O
credit O
card O
grabber O
targeting O
social O
and O
utility O
apps O
, O
such O
as O
Google B-System
Play I-System
, O
Facebook B-System
, O
WhatsApp B-System
, O
Chrome B-System
, O
Skype B-System
, O
Instagram B-System
and O
Twitter B-System
. O
Although O
early O
versions O
had O
some O
basic O
code O
and O
string O
obfuscation O
, O
protection O
of O
the O
third O
version O
of O
the O
malware O
was O
enhanced O
with O
the O
use O
of O
payload O
obfuscation O
. O
The O
capabilities O
remained O
unchanged O
, O
but O
a O
new O
endpoint O
was O
added O
to O
the O
Trojan O
C2 O
allowing O
it O
to O
handle O
the O
generic O
card O
grabber O
overlay O
and O
specific O
target O
overlays O
( O
banking O
apps O
) O
separately O
. O
In O
addition O
, O
the O
credit O
card O
grabber O
target O
list O
was O
expanded O
with O
Snapchat B-System
and O
Viber B-System
. O
In O
the O
third O
version O
spotted O
in O
the O
wild O
, O
the O
author O
introduced O
parts O
of O
the O
source O
code O
of O
the O
infamous O
Anubis B-Malware
Trojan O
( O
which O
was O
leaked O
earlier O
in O
2019 O
) O
. O
This O
change O
came O
hand O
in O
hand O
with O
a O
new O
overlay O
target O
list O
, O
no O
longer O
targeting O
social O
apps O
, O
but O
focusing O
on O
banking O
instead O
. O
A O
remarkable O
fact O
is O
that O
all O
the O
targeted O
apps O
relate O
to O
Spanish O
banks O
, O
including O
targets O
never O
seen O
before O
in O
any O
other O
Android B-System
banking O
Trojan O
. O
The O
24 O
target O
apps O
belong O
to O
7 O
different O
Spanish O
banks O
: O
Caixa B-System
bank I-System
, O
Bankinter B-System
, O
Bankia B-System
, O
BBVA B-System
, O
EVO B-System
Banco I-System
, O
Kutxabank B-System
and O
Santander B-System
. O
The O
specific O
apps O
can O
be O
found O
in O
the O
target O
list O
in O
the O
appendix O
. O
The O
most O
recent O
version O
of O
Ginp B-Malware
( O
at O
the O
time O
of O
writing O
) O
was O
detected O
at O
the O
end O
of O
November O
2019 O
. O
This O
version O
has O
some O
small O
modifications O
which O
seems O
to O
be O
unused O
, O
as O
the O
malware O
behaviour O
is O
the O
same O
as O
the O
previous O
version O
. O
The O
author O
has O
introduced O
the O
capability O
to O
grant O
the O
app O
the O
device O
admin O
permission O
. O
Additionally O
new O
endpoint O
was O
added O
that O
seems O
related O
to O
downloading O
a O
module O
for O
the O
malware O
, O
probably O
with O
new O
features O
or O
configuration O
. O
How O
it O
works O
When O
the O
malware O
is O
first O
started O
on O
the O
device O
it O
will O
begin O
by O
removing O
its O
icon O
from O
the O
app O
drawer O
, O
hiding O
from O
the O
end O
user O
. O
In O
the O
second O
step O
it O
asks O
the O
victim O
for O
the O
Accessibility O
Service O
privilege O
as O
visible O
in O
following O
screenshot O
: O
Ginp B-Malware
Accessibility O
request O
Once O
the O
user O
grants O
the O
requested O
Accessibility O
Service O
privilege O
, O
Ginp B-Malware
starts O
by O
granting O
itself O
additional O
permissions O
, O
such O
as O
( O
dynamic O
) O
permissions O
required O
in O
order O
to O
be O
able O
to O
send O
messages O
and O
make O
calls O
, O
without O
requiring O
any O
further O
action O
from O
the O
victim O
. O
When O
done O
, O
the O
bot O
is O
functional O
and O
ready O
to O
receive O
commands O
and O
perform O
overlay O
attacks O
. O
The O
commands O
supported O
by O
the O
most O
recent O
version O
of O
the O
bot O
are O
listed O
below O
. O
As O
can O
be O
observed O
, O
the O
possibilities O
offered O
by O
the O
bot O
are O
pretty O
common O
. O
Command O
Description O
SEND_SMS O
Send O
an O
SMS O
from O
the O
bot O
to O
a O
specific O
number O
NEW_URL O
Update O
the O
C2 O
URL O
KILL O
Disable O
the O
bot O
PING_DELAY O
Update O
interval O
between O
each O
ping O
request O
CLEAN_IGNORE_PKG O
Empty O
list O
of O
overlayed O
apps O
WRITE_INJECTS O
Update O
target O
list O
READ_INJECTS O
Get O
current O
target O
list O
START_ADMIN O
Request O
Device O
Admin O
privileges O
ALL_SMS O
Get O
all O
SMS O
messages O
DISABLE_ACCESSIBILITY O
Stop O
preventing O
user O
from O
disabling O
the O
accessibility O
service O
ENABLE_ACCESSIBILITY O
Prevent O
user O
from O
disabling O
the O
accessibility O
service O
ENABLE_HIDDEN_SMS O
Set O
malware O
as O
default O
SMS O
app O
DISABLE_HIDDEN_SMS O
Remove O
malware O
as O
default O
SMS O
app O
ENABLE_EXTENDED_INJECT O
Enable O
overlay O
attacks O
DISABLE_EXTENDED_INJECT O
Disable O
overlay O
attacks O
ENABLE_CC_GRABBER O
Enable O
the O
Google B-System
Play I-System
overlay O
DISABLE_CC_GRABBER O
Disable O
the O
Google B-System
Play I-System
overlay O
START_DEBUG O
Enable O
debugging O
GET_LOGCAT O
Get O
logs O
from O
the O
device O
STOP_DEBUG O
Disable O
debugging O
GET_APPS O
Get O
installed O
applications O
GET_CONTACTS O
Get O
contacts O
SEND_BULK_SMS O
Send O
SMS O
to O
multiple O
numbers O
UPDATE_APK O
Not O
implemented O
INJECT_PACKAGE O
Add O
new O
overlay O
target O
CALL_FORWARD O
Enable/disable O
call O
forwarding O
START_PERMISSIONS O
Starts O
request O
for O
additional O
permissions O
( O
Accessibility O
privileges O
, O
battery O
optimizations O
bypass O
, O
dynamic O
permissions O
) O
Features O
The O
most O
recent O
version O
of O
Ginp O
has O
the O
same O
capabilities O
as O
most O
other O
Android B-System
banking O
Trojans O
, O
such O
as O
the O
use O
of O
overlay O
attacks O
, O
SMS O
control O
and O
contact O
list O
harvesting O
. O
Overall O
, O
it O
has O
a O
fairly O
common O
feature O
list O
, O
but O
it O
is O
expected O
to O
expand O
in O
future O
updates O
. O
Since O
Ginp O
is O
already O
using O
some O
code O
from O
the O
Anubis B-Malware
Trojan O
, O
it O
is O
quite O
likely O
that O
other O
, O
more O
advanced O
features O
from O
Anubis B-System
or O
other O
malware O
, O
such O
as O
a O
back-connect O
proxy O
, O
screen-streaming O
and O
RAT O
will O
also O
be O
added O
in O
the O
future O
. O
Ginp B-Malware
embeds O
the O
following O
set O
of O
features O
, O
allowing O
it O
to O
remain O
under O
the O
radar O
and O
successfully O
perform O
attacks O
: O
Overlaying O
: O
Dynamic O
( O
local O
overlays O
obtained O
from O
the O
C2 O
) O
SMS O
harvesting O
: O
SMS O
listing O
SMS O
harvesting O
: O
SMS O
forwarding O
Contact O
list O
collection O
Application O
listing O
Overlaying O
: O
Targets O
list O
update O
SMS O
: O
Sending O
Calls O
: O
Call O
forwarding O
C2 O
Resilience O
: O
Auxiliary O
C2 O
list O
Self-protection O
: O
Hiding O
the O
App O
icon O
Self-protection O
: O
Preventing O
removal O
Self-protection O
: O
Emulation-detection O
Update O
10/03/2020 O
At O
the O
end O
of O
February O
the O
actors O
behind O
Ginp B-Malware
added O
screen O
capture O
capabilities O
to O
their O
Trojan O
. O
Like O
previously O
added O
functionality O
, O
the O
code O
is O
borrowed O
from O
the O
leaked O
Anubis B-Malware
Trojan O
source O
code O
. O
It O
enables O
the O
bot O
to O
stream O
screenshots O
and O
send O
them O
to O
the O
C2 O
so O
that O
actors O
can O
see O
what O
is O
happening O
on O
the O
screen O
of O
the O
infected O
device O
. O
Overlay O
attack O
Ginp O
uses O
the O
Accessibility O
Service O
to O
check O
which O
application O
runs O
is O
the O
foreground O
. O
If O
the O
package O
name O
of O
the O
foreground O
app O
is O
included O
in O
the O
target O
list O
, O
an O
overlay O
is O
shown O
. O
The O
WebView-based O
overlay O
is O
loading O
an O
HTML O
page O
provided O
by O
the O
C2 O
in O
response O
to O
the O
package O
name O
provided O
by O
the O
bot O
. O
Something O
that O
makes O
Ginp B-Malware
special O
is O
that O
all O
of O
its O
overlay O
screens O
for O
banking O
apps O
are O
consist O
of O
multiple O
steps O
, O
first O
stealing O
the O
victim O
’ O
s O
login O
credentials O
, O
then O
stealing O
the O
credit O
card O
details O
( O
to O
“ O
validate O
” O
the O
user O
identity O
) O
, O
as O
shown O
in O
the O
screenshots O
hereafter O
: O
The O
following O
code O
snippet O
shows O
that O
after O
the O
second O
overlay O
is O
filled-in O
and O
validated O
, O
it O
disappears O
and O
the O
targeted O
application O
is O
added O
to O
the O
list O
of O
packages O
names O
to O
be O
ignored O
for O
future O
overlays O
attacks O
. O
Targets O
The O
initial O
version O
of O
Ginp B-Malware
had O
a O
generic O
credit O
card O
grabber O
overlay O
screen O
used O
for O
all O
targeted O
applications O
. O
Still O
included O
in O
the O
last O
versions O
, O
this O
screen O
is O
only O
used O
to O
overlay O
the O
official O
Google B-System
Play I-System
Store I-System
app O
. O
More O
apps O
could O
be O
added O
to O
the O
grabber O
target O
list O
in O
the O
future O
, O
such O
as O
the O
ones O
that O
were O
targeted O
in O
older O
versions O
: O
Facebook B-System
WhatsApp B-System
Skype B-System
Twitter B-System
Chrome B-System
Instagram B-System
Snapchat B-System
Viber B-System
The O
following O
screenshot O
shows O
the O
generic O
card O
grabber O
overlay O
screen O
: O
Ginp B-Malware
generic O
grabber O
The O
current O
active O
target O
list O
is O
available O
in O
the O
appendix O
, O
containing O
a O
total O
of O
24 O
unique O
targets O
. O
The O
following O
screenshots O
show O
what O
type O
of O
information O
is O
collected O
in O
both O
steps O
of O
the O
overlay O
attack O
: O
Ginp B-Malware
overlaysGinp O
overlaysGinp O
overlaysGinp O
overlays O
Based O
on O
Anubis B-Malware
Once O
the O
Anubis B-Malware
bot O
code O
got O
leaked O
, O
it O
was O
just O
a O
matter O
of O
time O
before O
new O
banking O
Trojans O
based O
on O
Anubis B-Malware
would O
surface O
. O
When O
analyzing O
the O
Ginp B-Malware
’ O
s O
recent O
samples O
, O
ThreatFabric B-System
analysts O
found O
some O
similarities O
with O
the O
famous O
Android O
banking O
Trojan O
. O
Based O
on O
the O
evolution O
of O
Ginp B-Malware
it O
is O
clear O
that O
it O
isn O
’ O
t O
based O
on O
Anubis B-Malware
, O
but O
rather O
reuses O
some O
of O
its O
code O
. O
Below O
are O
some O
of O
the O
elements O
showing O
the O
relation O
. O
The O
names O
used O
for O
Android B-System
components O
are O
similar O
: O
Similarities O
with O
AnubisSimilarities O
with O
Anubis B-Malware
When O
analyzing O
these O
components O
, O
similarities O
were O
found O
in O
the O
code O
of O
both O
malware O
families O
: O
Similarities O
with O
Anubis B-System
Another O
major O
change O
that O
indicated O
that O
the O
actor O
copied O
code O
from O
the O
Anubis B-Malware
Trojan O
is O
the O
way O
of O
handling O
configuration O
values O
. O
Previous O
versions O
were O
storing O
config O
values O
within O
the O
variables O
of O
a O
class O
, O
while O
the O
latest O
version O
is O
using O
SharedPreferences O
with O
some O
of O
the O
keys O
being O
identical O
to O
those O
used O
by O
Anubis B-System
: O
isAccessibility O
time_work O
time_start_permission O
url_inj O
Conclusion O
Ginp B-Malware
is O
a O
simple O
but O
rather O
efficient O
banking O
Trojan O
providing O
the O
basic O
functionality O
to O
be O
able O
to O
trick O
victims O
into O
delivering O
personal O
information O
. O
In O
a O
5-month O
timespan O
, O
actor O
managed O
to O
create O
a O
Trojan O
from O
scratch O
which O
will O
presumably O
continue O
evolving O
offering O
new O
features O
such O
as O
keylogging O
, O
back-connect O
proxy O
or O
RAT O
capabilities O
. O
Ginp B-Malware
’ O
s O
unusual O
target O
selection O
is O
not O
just O
about O
its O
focus O
on O
Spanish O
banks O
but O
also O
the O
wide O
selection O
of O
targeted O
apps O
per O
bank O
. O
The O
fact O
that O
the O
overlay O
screens O
are O
almost O
identical O
to O
the O
legitimate O
banking O
apps O
suggests O
that O
the O
actors O
might O
be O
very O
familiar O
with O
the O
Spanish O
banking O
applications O
and O
might O
even O
be O
accustomed O
to O
the O
language O
. O
Although O
the O
current O
target O
list O
is O
limited O
to O
Spanish O
apps O
, O
it O
seems O
that O
the O
actor O
is O
taking O
into O
account O
that O
the O
bot O
should O
also O
be O
able O
to O
target O
other O
countries O
, O
seeing O
that O
the O
path O
used O
in O
the O
inject O
requests O
contains O
the O
country O
code O
of O
the O
targeted O
institution O
. O
This O
could O
indicate O
that O
actor O
already O
has O
plans O
in O
expanding O
the O
targets O
to O
applications O
from O
different O
countries O
and O
regions O
. O
Appendix O
Samples O
Some O
of O
the O
latest O
Ginp B-Malware
samples O
found O
in O
the O
wild O
: O
App O
name O
Package O
name O
SHA-256 O
hash O
Google B-System
Play I-System
Verificator I-System
sing.guide.false B-Indicator
0ee075219a2dfde018f17561467272633821d19420c08cba14322cc3b93bb5d5 B-Indicator
Google B-System
Play I-System
Verificator I-System
park.rather.dance B-System
087a3beea46f3d45649b7506073ef51c784036629ca78601a4593759b253d1b7 B-Indicator
Adobe B-System
Flash I-System
Player I-System
ethics.unknown.during B-Indicator
5ac6901b232c629bc246227b783867a0122f62f9e087ceb86d83d991e92dba2f B-Indicator
Adobe B-System
Flash I-System
Player I-System
solution.rail.forward B-Indicator
7eb239cc86e80e6e1866e2b3a132b5af94a13d0d24f92068a6d2e66cfe5c2cea B-Indicator
Adobe B-System
Flash I-System
Player I-System
com.pubhny.hekzhgjty B-Indicator
14a1b1dce69b742f7e258805594f07e0c5148b6963c12a8429d6e15ace3a503c B-Indicator
Adobe B-System
Flash I-System
Player I-System
sentence.fancy.humble B-Indicator
78557094dbabecdc17fb0edb4e3a94bae184e97b1b92801e4f8eb0f0626d6212 B-Indicator
Target O
list O
The O
current O
list O
of O
apps O
observed O
to O
be O
targeted O
by O
Ginp B-Malware
contains O
a O
total O
of O
24 O
unique O
applications O
as O
seen O
below O
. O
This O
list O
is O
expected O
to O
grow O
in O
the O
future O
. O