mnns/LLMFuzzer

🧠 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. 🚀💥

46
/ 100
Emerging

This tool helps security enthusiasts and pentesters find vulnerabilities in applications that use Large Language Models (LLMs). It takes your LLM API endpoint and fuzzer configurations as input, then generates various malicious inputs to test the LLM's robustness and reveal security flaws in how your application interacts with the LLM. It's designed for cybersecurity researchers looking to stress-test AI systems.

347 stars. No commits in the last 6 months.

Use this if you are a security professional looking to systematically discover and exploit vulnerabilities in applications built around Large Language Models.

Not ideal if you are an end-user of an LLM application simply trying to evaluate its performance or generate content, as this tool is specifically for security testing.

AI security penetration testing vulnerability research LLM security application security
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

347

Forks

57

Language

Python

License

MIT

Last pushed

Feb 12, 2024

Commits (30d)

0

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