README.md

🧠 LLMFuzzer - Fuzzing Framework for Large Language Models 🧠

LLMFuzzer is the first open-source fuzzing framework specifically designed for Large Language Models (LLMs), especially for their integrations in applications via LLM APIs. 🚀💥

🎯 Who is this for?

If you're a security enthusiast, a pentester, or a cybersec researcher who loves to find and exploit vulnerabilities in AI systems, LLMFuzzer is the perfect tool for you. It's built to make your testing process streamlined and efficient. 🕵️‍♀️

🌟 Features

• Robust fuzzing for LLMs 🧪
• LLM API integration testing 🛠️
• Wide range of fuzzing strategies 🌀
• Modular architecture for easy extendability 📚

🚀 Get Started

1. Clone the repo

git clone https://github.com/mnns/LLMFuzzer.git

2. Navigate to the project directory

cd LLMFuzzer

3. Install dependencies

pip install -r requirements.txt

4. Edit llmfuzzer.cfg with your LLM API endpoint (LLMFuzzer -> Your Application -> LLM)

Connection: 
  Type: HTTP-API
  Url: "http://localhost:3000/chat" # Your LLM API
  Content: JSON
  Query-Attribute: "query" # Your JSON query attribute
  Output-Attribute: "answer" # Your JSON response attribute
  Headers: {'enwiki_session': '17ab96bd8ffbe8ca58a78657a918558'} # Add HTTP Headers if needed 
  Cookie: {'enwiki_session': '17ab96bd8ffbe8ca58a78657a918558'} # Add Cookies if needed

5. Run LLMFuzzer

python main.py

📚 Documentation

We are working on full documentation. It will cover detailed information about the architecture, different fuzzing strategies, examples, and how to extend the tool.

🤝 Contributing

We welcome all contributors who are passionate about improving LLMFuzzer. See our contributing guidelines for ways to get started. 🤗

💼 License

LLMFuzzer is licensed under the MIT License. See the LICENSE file for more details.

🎩 Acknowledgments

LLMFuzzer couldn't exist without the community. We appreciate all our contributors and supporters. Let's make AI safer together! 💖