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On the recordRead 7 Oct 202619 facts
Red Team LLM Lab
On the record
- Analysis modules
- Its modules include a prompt analyzer with risk scoring, a jailbreak simulator, a honeypot orchestrator, a backdoor tester, and a master dashboard.github.com · read 7 Oct 2026
- Attack testing
- It includes prompt injection testing, jailbreak simulation with 14+ techniques, honeypot agents, backdoor detection, prompt analysis, and RAG poisoning tests.github.com · read 7 Oct 2026
- Backdoor detection
- Its backdoor tester checks for hidden triggers, including Unicode triggers.github.com · read 7 Oct 2026
- Defense testing
- The framework tests input validation and sanitization, pattern-based injection detection, and output filtering for information leaks.github.com · read 7 Oct 2026
- Honeypots
- It provides intentionally vulnerable honeypot agents for studying attack patterns.github.com · read 7 Oct 2026
- Integrations
- Support for OpenAI and Anthropic API testing is listed on the project roadmap.github.com · read 7 Oct 2026
- Intended users
- The project names security researchers, secure AI application developers, educators, and organizations conducting internal security audits as intended users.github.com · read 7 Oct 2026
- Jailbreak simulation
- It tests guardrail effectiveness using 14 or more jailbreak techniques.github.com · read 7 Oct 2026
- License
- The project states that it is licensed under the MIT License.github.com · read 7 Oct 2026
- Model setup
- The installation instructions download a quantized Phi-3 Mini model, and the project is built with llama-cpp-python.github.com · read 7 Oct 2026
- Notable limits
- The roadmap also lists a web UI, Docker support, GPU acceleration, function-calling tests, and CI/CD examples as planned items.github.com · read 7 Oct 2026
- Prompt injection
- It tests for vulnerabilities to prompt manipulation and includes static prompt analysis with risk scoring.github.com · read 7 Oct 2026
- Purpose
- Red Team LLM Lab is an open-source framework for testing large language model robustness against security attacks.github.com · read 7 Oct 2026
- RAG security
- It can test retrieval-augmented generation poisoning attacks.github.com · read 7 Oct 2026
- Reporting
- It saves JSON logs with metadata and provides security posture scoring, category-based vulnerability analysis, and automated recommendations.github.com · read 7 Oct 2026
- Requirements
- The stated prerequisites are Python 3.8 or higher, 4GB RAM minimum (8GB recommended), and about 4GB disk space for models.github.com · read 7 Oct 2026
- Security guidance
- The project recommends isolated or offline test environments, authorization, careful handling of results, and responsible vulnerability disclosure.github.com · read 7 Oct 2026
- Support
- The repository directs users to GitHub Issues for bugs or feature requests and Discussions for conversation.github.com · read 7 Oct 2026
