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ISACA AAISM Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: AI Governance and Program Management	31%	- AI governance frameworks and alignment with business objectives - AI security policies, standards, and procedures - AI asset and data lifecycle management - AI security program development and management - Business continuity and incident response for AI systems
Topic 2: AI Risk Management	31%	- AI vendor and supply chain risk management - Regulatory compliance and ethical considerations in AI - AI risk assessment, thresholds, and treatment strategies - AI threat and vulnerability management
Topic 3: AI Technologies and Controls	38%	- Security monitoring, testing, and continuous assurance for AI systems - AI security architecture and secure design principles - Privacy, ethics, trust, and safety controls - AI lifecycle security: model selection, training, validation, and deployment - Data management and protection controls for AI

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q423-Q428):

NEW QUESTION # 423
Which of the following MOST effectively minimizes the attack surface when securing AI agent components during their development and deployment?

A. Implement compartmentalization with least privilege enforcement.
B. Consolidate event logs for correlation and centralized analysis.
C. Deploy pre-trained models directly into production.
D. Schedule periodic manual code reviews.

Answer: A

Explanation:
The most effective strategy to minimize attack surfaces in AI agent security is to apply compartmentalization and least privilege enforcement.
AAISM control frameworks emphasize:
* Isolation of components (e.g., training, inference, data pipelines) to limit lateral movement.
* Principle of least privilege to restrict access only to what is required for function.
* Hardening AI pipelines through segmentation rather than relying solely on manual reviews or monitoring.
* Pre-trained models and log centralization are useful but do not directly reduce the attack surface.
* Manual code reviews are important but insufficient against runtime exploitation.
Thus, compartmentalization with least privilege enforcement is the most effective technical safeguard.

NEW QUESTION # 424
As organizations increasingly rely on vendors to develop AI systems, which of the following is the MOST effective way to monitor vendors and ensure compliance with ethical and security standards?

A. Allowing vendors to self-attest ethical AI compliance and implement benchmark monitoring
B. Mandating that vendors share source code and AI documentation with the contracting party
C. Conducting regular audits of vendor processes and adherence to AI development guidelines
D. Requiring vendors to monitor their adherence to ethics and security standards

Answer: C

Explanation:
AAISM vendor governance guidance identifies regular audits of vendor processes as the most effective method of ensuring compliance with ethical and security standards. Independent audits provide verifiable assurance that vendors are meeting agreed-upon requirements. Self- attestation, internal monitoring, or documentation sharing provide some transparency but do not guarantee compliance. The best practice, particularly for high-risk AI deployments, is independent and recurring audits of vendor processes.

NEW QUESTION # 425
When designing self-driving vehicles, conformity assessment is PRIMARILY needed to:

A. protect against unfair decisions.
B. verify that the AI system operates reliably.
C. test for security flaws before the AI system goes live.
D. assess compliance against AI regulations and frameworks.

Answer: D

Explanation:
Conformity assessment is primarily conducted to evaluate whether an AI system complies with applicable regulations, standards, and governance frameworks. For self-driving vehicles, this is critical because they are high-risk AI systems subject to strict regulatory and safety requirements.

NEW QUESTION # 426
A hospital adopts an AI solution from an external vendor to help diagnose rare diseases. Which of the following BEST demonstrates the verification of security requirements for this technology?

A. Preview contractual clauses of mandatory security AI software update.
B. Integrate requirements for sensitive data aligned with healthcare regulations.
C. Require contractual clauses stipulating periodic information security reviews.
D. Perform regular in-depth vulnerability scans on the AI system.

Answer: B

Explanation:
Verification of security requirements for an AI used in diagnosis must focus on how sensitive health data (PHI) is protected in line with regulations such as HIPAA and similar healthcare laws.
Integrating explicit requirements for handling, storing, transmitting, and accessing sensitive data in accordance with healthcare regulations is a direct verification that the technology's security controls meet the hospital's legal and security obligations.

NEW QUESTION # 427
Employees are regularly using open-source generative AI without guidance. What should be the CISO's GREATEST concern?

A. Model hallucinations
B. Policy violations
C. Lack of monitoring
D. Data leakage

Answer: D

Explanation:
AAISM emphasizes that the primary and most severe risk of uncontrolled generative AI usage is data leakage, including:
- confidential data
- regulated personal data
- intellectual property
While hallucinations (A) are harmful, they do not cause direct data loss. Lack of monitoring (C) is a secondary risk. Policy violations (D) occur because of lack of controls but do not outweigh the impact of leaked sensitive data.

NEW QUESTION # 428
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