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.


  • 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
Custom Huggingface Datasetsmarkush1/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.


To get started with Agentic Security, simply install the package using pip:

pip install agentic_security

Quick Start


2024-04-13 13:21:31.157 | INFO     | - Found 1 CSV files
2024-04-13 13:21:31.157 | INFO     | - CSV files: ['prompts.csv']
INFO:     Started server process [18524]
INFO:     Waiting for application startup.
INFO:     Application startup complete.
INFO:     Uvicorn running on (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:

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



For more information click here.

Published by Tamil S

Tamil has a great interest in the fields of Cyber Security, OSINT, and CTF projects. Currently, he is deeply involved in researching and publishing various security tools with Kali Linux Tutorials, which is quite fascinating.

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