Episode 51 — Identify the AI threat landscape using realistic abuse cases (Task 5)
This episode covers Task 5 by building a practical view of the AI threat landscape using realistic abuse cases, because AAISM expects you to recognize how AI systems can be attacked or misused without relying on vague “AI is risky” statements. You’ll define what a threat landscape means in exam terms: the set of credible threat actors, their objectives, and the tactics that can affect AI confidentiality, integrity, availability, safety, and compliance. We’ll walk through common abuse patterns such as prompt injection that manipulates tool use, data exfiltration through connectors and output channels, model misuse for prohibited content generation, and poisoning risks that degrade reliability over time. You’ll also learn how to describe threats in a structured way that maps to controls and evidence, so you can choose the best-answer response that reduces exposure and supports governance decisions. 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.
