Episode 81 — Evaluate AI threats and vulnerabilities that do not exist in normal IT (Domain 2F)
This episode explains AI-specific threats and vulnerabilities that go beyond normal IT risk, which matters for Domain 2F because AAIA expects you to recognize failure modes unique to models, data pipelines, and inference behavior. You’ll learn how threats shift from “break the server” to “break the decision,” including manipulation of inputs, abuse of model behavior, leakage of sensitive outputs, and attacks that degrade performance without obvious outages. We’ll cover how AI risk is introduced through training data, feature engineering, model interfaces, and monitoring gaps, and how traditional vulnerability scans may miss these weaknesses entirely. You’ll also learn what evidence auditors should look for, such as threat models that include AI abuse cases, controls that protect model artifacts and data integrity, and monitoring that detects suspicious inference patterns. By the end, you should be able to choose exam answers that treat AI security as outcome-protection with testable controls, not just a rebrand of standard IT hardening. 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.
