Episode 37 — Investigate AI security incidents by collecting the right evidence fast (Task 15)
This episode explains how to investigate AI security incidents by quickly collecting evidence that preserves accuracy under pressure, which AAISM scenarios test through triage and investigation choices. You will learn what “right evidence” means in AI contexts, including prompt and response logs, model version and configuration details, pipeline and data lineage records, access logs for service accounts and endpoints, and any change approvals tied to recent releases. We walk through a scenario where abnormal outputs appear in production, showing how to separate performance issues from abuse, data integrity problems, or unauthorized access. Troubleshooting focuses on evidence pitfalls such as missing retention, incomplete logging, and unclear ownership, all of which slow containment and make root cause conclusions fragile. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
