🧠 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. 🚀💥
Python
379
29 commits
updated Feb 12, 2024
This project is no longer actively maintained.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. 🚀💥
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. 🕵️♀️
git clone https://github.com/mnns/LLMFuzzer.git
cd LLMFuzzer
pip install -r requirements.txt
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
python main.py
We are working on full documentation. It will cover detailed information about the architecture, different fuzzing strategies, examples, and how to extend the tool.
We welcome all contributors who are passionate about improving LLMFuzzer. See our contributing guidelines for ways to get started. 🤗
LLMFuzzer is licensed under the MIT License. See the LICENSE file for more details.
LLMFuzzer couldn't exist without the community. We appreciate all our contributors and supporters. Let's make AI safer together! 💖
29 commits
Python
100.0%
🧠 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. 🚀💥
Python
379
29 commits
updated Feb 12, 2024
This project is no longer actively maintained.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. 🚀💥
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. 🕵️♀️
git clone https://github.com/mnns/LLMFuzzer.git
cd LLMFuzzer
pip install -r requirements.txt
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
python main.py
We are working on full documentation. It will cover detailed information about the architecture, different fuzzing strategies, examples, and how to extend the tool.
We welcome all contributors who are passionate about improving LLMFuzzer. See our contributing guidelines for ways to get started. 🤗
LLMFuzzer is licensed under the MIT License. See the LICENSE file for more details.
LLMFuzzer couldn't exist without the community. We appreciate all our contributors and supporters. Let's make AI safer together! 💖
29 commits
Python
100.0%