AI SECURITY
The Holistic AI Offensive Security Playbook
A comprehensive integration plan for embedding Large Language Models into the offensive security lifecycle.
The Unseen Threat
As organizations rush to adopt Generative AI, they are introducing a new class of vulnerabilities that traditional scanners cannot detect. Prompt injection, model inversion, and poisoning attacks require a fundamental shift in how we approach penetration testing.
Current methodologies treat AI systems as black boxes, ignoring the nuance of probabilistic failure modes.
The Solution
Our framework provides a structured approach to AI-inclusive pentesting. We move beyond simple "jailbreaking" to examine the entire AI supply chain, from data ingestion to inference.
This paper outlines specific test cases, tooling requirements, and risk scoring metrics tailored for stochastic systems.
Key Takeaways
- ➤ Taxonomy of LLM-specific vulnerabilities
- ➤ Tools and techniques for model red-teaming
- ➤ Risk scoring matrix for probabilistic systems