Episode 45 — Protect Against Adversarial Inputs: Evasion, Prompt Injection, and Abuse Patterns (Domain 3)
Adversarial attacks represent a unique class of security threats where small, often invisible changes to inputs can cause an AI model to misbehave. This episode focuses on the mechanics of evasion attacks, where an attacker bypasses a classifier, and prompt injection, where an attacker hijacks a large language model's instructions to perform unauthorized actions. For the AAIR exam, candidates must be able to identify these abuse patterns and recommend specific technical mitigations, such as input sanitization, adversarial training, and the use of robust architectural guardrails. We discuss the importance of "rate limiting" and "intent analysis" to detect when a user is attempting to probe the model for vulnerabilities. Scenarios include an attacker using a specially crafted image to trick an autonomous vehicle's vision system or a user manipulating a chatbot to leak internal company secrets. By defending the AI interface against these sophisticated attacks, organizations maintain the integrity of their services and protect their data from exploitation by malicious actors. 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.
