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--- |
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license: gpl-3.0 |
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library_name: transformers |
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language: en |
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tags: |
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- language-model |
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- text-generation |
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- security |
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- shell |
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--- |
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# SandboxLM |
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**SandboxLM** is a language model fine-tuned on a carefully curated synthetic dataset using the GPT-2 architecture. This model was specifically created to act as a special advisory to AI agents using shell commands, helping them operate securely by identifying potentially harmful shell commands. SandboxLM aims to assist in improving the safety and security of AI-driven shell operations. |
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## Model Description |
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SandboxLM is built on the GPT-2 architecture, a Transformer-based language model. The model has been fine-tuned on a dataset designed to help identify and classify shell commands as either safe or potentially dangerous. This makes it suitable for security advisory tasks, particularly in environments where AI agents are used to execute shell commands. |
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### Usage |
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To use this model, install the `transformers` library and load the model and tokenizer as follows: |
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```python |
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from transformers import GPT2Tokenizer, GPT2LMHeadModel |
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tokenizer = GPT2Tokenizer.from_pretrained("your-username/sandboxlm") |
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model = GPT2LMHeadModel.from_pretrained("your-username/sandboxlm") |
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input_text = "rm -rf /" |
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inputs = tokenizer(input_text, return_tensors="pt") |
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outputs = model.generate(**inputs) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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### Limitations and Biases |
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While SandboxLM performs well in detecting potentially harmful shell commands, it may not catch all edge cases or obscure security risks. It should not be solely relied upon for mission-critical systems. It is recommended to combine it with other security measures to ensure the safety of shell operations. Additionally, since it was trained on specific datasets, it may reflect any biases present in those datasets. |
