In an era where large language models (LLMs) are integral to technological advancements, ensuring their security is paramount.
Agentic Security offers a pioneering open-source vulnerability scanner designed to robustly test and enhance the resilience of LLMs.
This tool not only integrates seamlessly but also provides customizable attack simulations to safeguard against emerging threats.
Features
- Customizable Rule Sets or Agent based attacks
- Comprehensive fuzzing for any LLMs
- LLM API integration and stress testing
- Wide range of fuzzing and attack techniques
Tool | Source | Integrated |
---|---|---|
Garak | leondz/garak | ✅ |
InspectAI | UKGovernmentBEIS/inspect_ai | ✅ |
llm-adaptive-attacks | tml-epfl/llm-adaptive-attacks | ✅ |
Custom Huggingface Datasets | markush1/LLM-Jailbreak-Classifier | ✅ |
Local CSV Datasets | – | ✅ |
Note: Please be aware that Agentic Security is designed as a safety scanner tool and not a foolproof solution. It cannot guarantee complete protection against all possible threats.
Installation
To get started with Agentic Security, simply install the package using pip:
pip install agentic_security
Quick Start
agentic_security
2024-04-13 13:21:31.157 | INFO | agentic_security.probe_data.data:load_local_csv:273 - Found 1 CSV files
2024-04-13 13:21:31.157 | INFO | agentic_security.probe_data.data:load_local_csv:274 - CSV files: ['prompts.csv']
INFO: Started server process [18524]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:8718 (Press CTRL+C to quit)
python -m agentic_security
# or
agentic_security --help
agentic_security --port=PORT --host=HOST
LLM kwargs
Agentic Security uses plain text HTTP spec like:
POST https://api.openai.com/v1/chat/completions
Authorization: Bearer sk-xxxxxxxxx
Content-Type: application/json
{
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": "<<PROMPT>>"}],
"temperature": 0.7
}
Where <<PROMPT>>
will be replaced with the actual attack vector during the scan, insert the Bearer XXXXX
header value with your app credentials.
Adding LLM Integration Templates
TBD
....
For more information click here.