Episode 83 — AI-Related Attacks (High-Level)
This episode explains AI-related risks in scenario-friendly terms by treating them as input manipulation, access control, and data exposure problems rather than as mysterious model magic. You’ll learn prompt injection as crafted input that changes system behavior, data leakage as unintended disclosure of sensitive context or training-related information, and model manipulation as steering outputs toward unsafe or misleading outcomes. We’ll cover supply chain concerns such as untrusted models or components, access boundaries for who can query systems and what they can retrieve, and why logging and retention require special care because prompts and outputs may contain sensitive data. You’ll practice reasoning through scenarios where an assistant reveals private instructions or sensitive information, deciding what the most likely weakness is, how to validate behavior responsibly, and what mitigations fit, such as input controls, output filtering, tighter access controls, and reduced sensitive context exposure. By the end, you’ll be able to describe AI risks clearly, avoid treating them as purely quality issues, and choose answers that emphasize governance, boundaries, and practical controls. 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.
