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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • AI Risk Management: This section of the exam measures the skills of AI Risk Managers and covers assessing enterprise threats, vulnerabilities, and supply chain risk associated with AI adoption, including risk treatment plans and vendor oversight.
Topic 2
  • AI Governance and Program Management: This section of the exam measures the abilities of AI Security Governance Professionals and focuses on advising stakeholders in implementing AI security through governance frameworks, policy creation, data lifecycle management, program development, and incident response protocols.
Topic 3
  • AI Technologies and Controls: This section of the exam measures the expertise of AI Security Architects and assesses knowledge in designing secure AI architecture and controls. It addresses privacy, ethical, and trust concerns, data management controls, monitoring mechanisms, and security control implementation tailored to AI systems.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q339-Q344):

NEW QUESTION # 339
When evaluating a new AI tool for intrusion prevention, which is MOST important to ensure fit within the existing program architecture?

Answer: D

Explanation:
AAISM stresses that AI tools must align with the organization's existing control objectives and governance requirements, ensuring consistency with risk management, detection philosophy, and operational processes.
Integration with SIEM (D) is important but secondary. Anomaly detection (B) is a feature, not an architectural requirement. Automated orchestration (A) is optional.
References: AAISM Study Guide - AI Security Architecture & Control Alignment.


NEW QUESTION # 340
Which of the following mitigation control strategies would BEST reduce the risk of introducing hidden backdoors during model fine-tuning via third-party components?

Answer: D

Explanation:
AAISM highlights threat modeling and supply chain integrity checks as key controls for managing AI-specific risks, including hidden backdoors in third-party models, libraries, or fine-tuning artifacts. The official guidance states that organizations should "identify adversarial insertion points, verify component integrity, and continuously test for malicious behaviors introduced via external components." This is precisely what option B describes.


NEW QUESTION # 341
Which of the following BEST supports the evaluation of AI system outputs?

Answer: B

Explanation:
Manual review allows direct assessment of AI outputs for accuracy, relevance, and potential issues in real-world contexts, making it the most effective method for evaluating the quality and reliability of outputs.


NEW QUESTION # 342
An organization uses an AI tool to scan social media for product reviews. Fraudulent social media accounts begin posting negative reviews attacking the organization's product. Which type of AI attack is MOST likely to have occurred?

Answer: C

Explanation:
The AAISM materials classify availability attacks as attempts to disrupt or degrade the functioning of an AI system so that its outputs become unreliable or unusable. In this scenario, the fraudulent social media accounts are deliberately overwhelming the AI tool with misleading negative reviews, undermining its ability to deliver accurate sentiment analysis. This aligns directly with the concept of an availability attack. Model inversion relates to reconstructing training data from outputs, deepfakes involve synthetic content generation, and data poisoning corrupts the training set rather than manipulating inputs at runtime. Therefore, the fraudulent review campaign is most accurately identified as an availability attack.


NEW QUESTION # 343
Which BEST addresses hallucination risk in AI systems?

Answer: B

Explanation:
AAISM states that human oversight is the strongest control for hallucination risks, especially in high-impact decisions. Humans validate outputs, correct errors, and override unsafe model responses.
Automated validation (C) helps but cannot fully detect hallucinations. Chunking (B) improves information handling but not hallucination mitigation. Content enrichment (D) does not reduce hallucinations.
References: AAISM Study Guide - Human-in-the-Loop (HITL) Controls; Hallucination Mitigation.


NEW QUESTION # 344
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