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🧠 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. πŸš€πŸ’₯

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🧠 LLMFuzzer - Fuzzing Framework for Large Language Models 🧠

LLMFuzzer-shell

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Project Status: Unmaintained

This project is no longer actively maintained. You are welcome to fork and continue its development on your own. Thank you for your interest and support.


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

🎯 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. πŸ•΅οΈβ€β™€οΈ

Untitled

🌟 Features

  • Robust fuzzing for LLMs πŸ§ͺ
  • LLM API integration testing πŸ› οΈ
  • Wide range of fuzzing strategies πŸŒ€
  • Modular architecture for easy extendability πŸ“š

πŸ”₯ Roadmap

  • Adding more attacks
  • HTML Report as output
  • Multiple Connectors (JSON-POST, RAW-POST, QUERY-GET)
  • Multiple Comparers
  • Proxy Support
  • Dual-LLM (Side LLM observation)
  • Autonomous Attack Mode

πŸš€ Get Started

  1. Clone the repo
git clone https://github.com/mnns/LLMFuzzer.git
  1. Navigate to the project directory
cd LLMFuzzer
  1. Install dependencies
pip install -r requirements.txt
  1. 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
  1. Run LLMFuzzer
python main.py

πŸ“š 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. πŸ€—

πŸ’Ό 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! πŸ’–

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🧠 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. πŸš€πŸ’₯

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