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EC-CouncilCertified Offensive AI Security Professional

Domain 1Objective 4

AI Attack Taxonomies and Classification Models COASP Practice Questions (Page 1)

Part of the Offensive AI Foundations and Hacking Methodology domain, which makes up ~18% of our current practice bank.

39questions here
8free pages
5concepts

Questions 1–5

  1. 1foundation · easy

    In the AI kill chain, which stage corresponds to the attacker achieving their ultimate objective, such as causing financial loss or reputational damage?

    Select an answer first
  2. 2foundation · easy

    Which adversarial ML attack is characterized by the attacker's goal of recovering private training data or sensitive attributes from a model?

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  3. 3expert · hard

    A penetration tester is using an AI attack taxonomy to plan an assessment of a voice recognition system. The tester has physical access to a device that uses the system but no network access to the backend. The goal is to cause the system to execute a malicious command. Which attack taxonomy-based approach is most viable given the physical access constraint?

    Select an answer first
  4. 4application · medium

    An offensive AI team is scoping a test for a self-driving car's object-detection model. The team has limited time and must choose which attacks to test first. The model is deployed in a safety-critical environment, and the team has no access to the training data. Using a taxonomy, which prioritization is most defensible?

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  5. 5application · medium

    A cybersecurity instructor is explaining AI attack taxonomies to a class. The instructor wants to illustrate how different taxonomies organize attacks based on the attacker's goal. Which of the following correctly groups attacks by their primary goal?

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