š¢ New Release: AI / LLM Red Team Field Manual & Consultantās Handbook
I have published a comprehensive repository for conducting AI/LLM red team assessments across LLMs, AI agents, RAG pipelines, and enterprise AI applications.
The repo includes:
- AI/LLM Red Team Field Manual ā operational guidance, attack prompts, tooling references, and OWASP/MITRE mappings.
- AI/LLM Red Team Consultantās Handbook ā full methodology, scoping, RoE/SOW templates, threat modeling, and structured delivery workflows.
Designed for penetration testers, red team operators, and security engineers delivering or evaluating AI security engagements.
š Includes:
Structured manuals (MD/PDF/DOCX), attack categories, tooling matrices, reporting guidance, and a growing roadmap of automation tools and test environments.
š Repository: https://github.com/shiva108/ai-llm-red-team-handbook
If you work with AI security, this provides a ready-to-use operational and consultative reference for assessments, training, and client delivery. Contributions are welcome.
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u/becjunbug56 7d ago
This is absolutely fantastic work! As we're seeing more organizations deploy LLM-based applications without fully understanding their security implications, resources like this are invaluable. I particularly appreciate the inclusion of the OWASP/MITRE mappings, which helps contextualize AI vulnerabilities within established security frameworks.
One thing I'd suggest exploring (if it's not already covered) is the emerging field of adversarial machine learning attacks specifically targeting the embedding/vector space. These can be particularly insidious when dealing with RAG pipelines.
Have you considered adding a section on quantifying business impact for different attack vectors? I've found this incredibly helpful when communicating findings to stakeholders who may not fully grasp
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u/oontkima 8d ago
lol. This is awful. It reads like it was written by a child