Auditer la sécurité des LLM

This article presents a practical, offensive-security approach to auditing and pentesting LLM-powered systems, detailing how to map attack surfaces and test prompts, integrations, and MLOps pipelines against threats like prompt injection, data exfiltration, model extraction, poisoning, and adversarial attacks; it aligns with OWASP LLM Top 10, NIST AI RMF, and ANSSI guidance and recommends continuous governance, CI/CD and MLOps controls, and SOC integration to operationalize AI security.