Foundations of AI & Cybersecurity - Lesson 36: Scenario on Identifying the Attack Indicators

This scenario lesson shows how AI attacks often reveal themselves through subtle behavioral indicators rather than obvious technical failures. It shows how signs like hallucinations, output manipulation, sensitive data disclosure, insecure execution, excessive autonomy, overreliance, and model drift can be turned into real monitoring and response controls. The key point is that secure AI depends on treating these behaviors as early warning signals, not waiting for a fullincident to confirm something is wrong.

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