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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
AI Technologies and Controls38%- Privacy, ethics, trust, and safety controls
- AI lifecycle security: model selection, training, validation, and deployment
- Data management and protection controls for AI
- Security monitoring, testing, and continuous assurance for AI systems
- AI security architecture and secure design principles
AI Governance and Program Management31%- AI security program development and management
- AI governance frameworks and alignment with business objectives
- AI security policies, standards, and procedures
- Business continuity and incident response for AI systems
- AI asset and data lifecycle management
AI Risk Management31%- AI threat and vulnerability management
- Regulatory compliance and ethical considerations in AI
- AI vendor and supply chain risk management
- AI risk assessment, thresholds, and treatment strategies

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q389-Q394):

NEW QUESTION # 389
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?

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 # 390
An organization has discovered that employees have started regularly utilizing open-source generative AI without formal guidance. Which of the following should be the CISO's GREATEST concern?

Answer: B

Explanation:
The greatest immediate risk from unsanctioned use of public or open-source generative AI tools is data leakage-employees may paste confidential or regulated information into third-party systems, resulting in loss of confidentiality, regulatory exposure, and loss of intellectual property. AAISM emphasizes that when AI use occurs outside approved channels, the top control priority is preventing exfiltration of sensitive data via prompts, attachments, and context sharing. Monitoring and policy are necessary enablers, but leakage is the highest-impact failure mode in the short term; hallucinations primarily affect accuracy, not confidentiality.
References:* AI Security Management (AAISM) Body of Knowledge: Generative AI governance; human- in-the-loop risks; data loss and exfiltration vectors in prompts; sanctioned vs. unsanctioned AI usage.* AI Security Management Study Guide: Immediate risk triage for shadow AI; DLP and input-control safeguards; confidentiality-first posture for generative AI adoption.


NEW QUESTION # 391
Which of the following is the GREATEST benefit of employing human-in-the-loop when deploying AI models?

Answer: D

Explanation:
Human-in-the-loop provides oversight and intervention in AI decision-making, reducing the risk of harmful or unintended outcomes and ensuring safe operation, especially in critical or high-impact scenarios.


NEW QUESTION # 392
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. Topics like bias/fairness (B) and policy/hallucinations (C) are important but are governance/assurance concerns; API abuse and plug-in risk (D) matter, yet the core, developer-controlled attack surface for agents is injection and unsafe tool/memory design.
References:* AI Security Management (AAISM) Body of Knowledge: Agent Security-prompt injection defenses, tool execution constraints, memory governance* AAISM Study Guide: Developer controls for agent frameworks; input validation, sandboxing, scoped permissions, guardrail patterns


NEW QUESTION # 393
An AI research team is developing a natural language processing model that relies on several open-source libraries. Which of the following is the team's BEST course of action to ensure the integrity of the software packages used?

Answer: D

Explanation:
AAISM's technical control guidance emphasizes that when using open-source libraries, the best safeguard for integrity is to scan the packages for malware before installation. This ensures that compromised or malicious code does not enter the AI system environment. Maintaining lists aids consistency but not security. Always using the latest versions may introduce unverified vulnerabilities. Retraining models addresses functionality but not software integrity. Therefore, the strongest protective measure is pre-installation malware scanning of open-source packages.


NEW QUESTION # 394
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