Foundations of AI & Cybersecurity - Lesson 35: Identifying the Attack Indicators

This module explains how AI attacks and failures often appear as subtle behavioral signals rather than obvious breaches. It outlines seven key indicators, including hallucinations, output manipulation, data leakage, insecure execution, excessive autonomy, human overreliance, and model drift, that act as early warning signs of compromise or misuse. The core lesson is that securing AI depends on recognizing and monitoring these patterns before they escalate into real incidents.

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