Episode 83 — Evaluate AI threat and vulnerability management programs for real coverage (Task 19)
This episode teaches you how to evaluate whether an AI threat and vulnerability management program has real coverage, because Task 19 scenarios often describe “we have a program” while leaving model and data risks unaddressed. You’ll learn how to assess scope first: whether the program includes training pipelines, data stores, model registries, inference endpoints, prompt interfaces where applicable, and third-party components that influence outcomes. We’ll cover what “coverage” looks like beyond scanning, including threat modeling for AI abuse cases, secure design reviews for model interfaces, integrity controls for datasets, and monitoring for suspicious inference patterns. You’ll also learn what evidence proves the program operates, such as tracked findings, prioritized remediation tied to decision impact, change records showing fixes deployed, and repeat testing that confirms risks were reduced. By the end, you should be able to answer exam questions by selecting the option that expands traditional vulnerability management into AI-relevant controls and auditable assurance, not just reusing existing IT processes unchanged. 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.
