toxy4ny/redteam-ai-benchmark
📦 Open Source Projecttoxy4ny
A specialized benchmark suite for evaluating the offensive security capabilities and safety boundaries of uncensored LLMs.
The Red Team AI Benchmark provides a comprehensive testing environment for security researchers and AI developers. As uncensored models become more prevalent, understanding their potential for misuse or their utility in offensive security operations is critical. This repository offers a suite of test cases and evaluation metrics specifically tailored to probe the boundaries of LLMs. Key features include automated prompt-tuning workflows, evaluation of RAG-based chatbot vulnerabilities, and specific modules for testing hacking-related capabilities. The tool is built in Python, making it highly extensible for researchers looking to integrate custom red-teaming datasets or specific attack vectors. By focusing on the intersection of MLSecOps and offensive security, it bridges the gap between traditional penetration testing and modern AI safety research, allowing for a more rigorous assessment of model robustness against adversarial inputs.
💡Highlights
- ├─Evaluates uncensored LLM security
- ├─Automated red-teaming workflows
- └─Focus on offensive security tasks
🎯For
- ├─Cybersecurity Researchers
- ├─AI Safety Engineers
- └─MLSecOps Practitioners