Episode 37 — Investigate AI security incidents by collecting the right evidence fast (Task 15)
This episode introduces Task 15 by teaching how to investigate AI security incidents through fast, disciplined evidence collection, because AAISM expects you to prioritize what preserves truth and supports defensible decisions before focusing on attribution or deeper analysis. You’ll define the evidence categories that matter for AI incidents, including access and authentication logs, prompt and output records where permitted, model and configuration versions, data source and plugin activity, change management history, and monitoring alerts that show timeline and impact. We’ll walk through a scenario where sensitive data appears in an AI-generated response, and you’ll practice building an investigation timeline, identifying likely exposure paths such as prompt leakage or overly broad data connectors, and determining what to secure immediately to prevent evidence loss. Best practices include chain-of-custody discipline, documenting assumptions, and using structured triage questions so you can rapidly separate misuse, misconfiguration, and system faults under time pressure. 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.
