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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 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.
Topic 3
  • 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.

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q55-Q60):

NEW QUESTION # 55
Which proactive control BEST mitigates the risk of memory poisoning in agentic AI systems?

Answer: D

Explanation:
Enforcing validation before persistence helps prevent malicious or manipulated information from being stored in the agent's memory. This proactive control ensures that only trusted and verified data is retained, directly mitigating the risk of memory poisoning attacks.


NEW QUESTION # 56
A vendor switched its chatbot's AI model without due diligence, causing unethical investment advice. What control BEST prevents this scenario?

Answer: C

Explanation:
AAISM stresses AI-specific change management as essential for vendor-driven or system-driven updates.
Proper change control includes:
* impact assessments
* ethical review
* risk evaluation
* approval checkpoints
* rollback plans
An MSA (A) supports contracts but does not manage operational change. Shared responsibility (C) describes roles, not change control. Data minimization (D) reduces exposure but doesn't control model updates.
References: AAISM Study Guide - AI Change Management; Vendor Model Update Controls.


NEW QUESTION # 57
An organization is commissioning a third-party AI system using sensitive data. Which metric is MOST important to consider?

Answer: A

Explanation:
AAISM specifies that when AI systems process sensitive or high-impact data (e.g., financial, identity, health), accuracy thresholds become critical risk indicators. Inaccurate predictions can cause harm, regulatory non-compliance, discrimination, or financial loss.


NEW QUESTION # 58
An organization is implementing AI agent development across multiple engineering teams. Which of the following is the MOST important focus of AI-specific security training for developers?

Answer: B

Explanation:
For developer-facing, near-term hardening of AI agents, AAISM prioritizes secure agent design and runtime controls against prompt injection, unsafe memory/tool use, and tool-execution compromise. These are primary exploitation paths for agents that read external content, persist memory, and call tools with elevated privileges. Training must center on: guarding tool invocation, constraining memory scope, sanitizing/validating inputs, and isolating high-risk actions.


NEW QUESTION # 59
The PRIMARY purpose of adopting and implementing AI architecture as part of an organizational AI program is to:

Answer: A

Explanation:
An AI architecture, within program governance, exists to align AI system components and lifecycle processes with business goals and policy constraints. Architecture provides the organizing structure linking strategy, capabilities, processes, data, models, controls, and assurance so that AI outcomes are traceable to business value, risk appetite, and compliance expectations. Efficiency, speed, and threat analysis are important architectural qualities, but they are not the primary purpose; the primary purpose is strategic and governance alignment so that technical choices and controls consistently realize organizational objectives.
References:* AI Security Management (AAISM) Body of Knowledge: AI Program Architecture - alignment of capabilities, processes, and controls to business objectives* AI Security Management Study Guide: Architecture-driven governance, traceability from business goals to technical and control design


NEW QUESTION # 60
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