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ISACA AAISM Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: AI Governance and Program Management31%- Stakeholder considerations and governance frameworks
  • 1. Industry frameworks and regulatory requirements
  • 2. AI governance models and oversight
- AI security program management
  • 1. Incident response and business continuity
  • 2. Program development and maintenance
- AI policies and procedures
  • 1. Policy implementation and compliance
  • 2. AI-related strategy development
- AI asset and data lifecycle management
  • 1. AI asset inventory and management
  • 2. Data governance
Topic 2: AI Risk Management31%- Third-party and supply chain risk management
  • 1. Supply chain security controls
  • 2. Vendor risk evaluation
- AI threat and vulnerability management
  • 1. Threat modeling for AI systems
  • 2. AI vulnerability assessment
- AI risk assessment and treatment
  • 1. Risk thresholds and mitigation
  • 2. Risk identification and analysis
Topic 3: AI Technologies and Controls38%- Trust, safety and compliance controls
  • 1. Compliance and governance validation
  • 2. Responsible AI practices
- Data management and privacy controls
  • 1. Privacy and ethical AI controls
  • 2. Data integrity and protection
- AI security monitoring and operations
  • 1. Security monitoring and logging
  • 2. Operational AI controls
- AI security architecture and design
  • 1. AI infrastructure protection
  • 2. Secure AI system architecture

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q360-Q365):

NEW QUESTION # 360
A programmer suspects an AI system is inferring sensitive user information. What is the BEST action?

Answer: C

Explanation:
AAISM directs that potential privacy, ethical, or compliance risks must be escalated to the AI Governance Panel, the body responsible for oversight, risk approval, and corrective action.
Fine-tuning (B) is premature and may worsen risk. Code review (C) does not address model-level inference issues. Escalating directly to the CIO (D) bypasses the required governance process.
References: AAISM Study Guide - AI Governance Committees; Escalation Procedures.


NEW QUESTION # 361
Which of the following is the MOST effective way to prevent a model inversion attack?

Answer: B

Explanation:
AAISM identifies differential privacy as the primary mitigation technique against model inversion attacks, which attempt to reconstruct sensitive training data by probing model outputs.


NEW QUESTION # 362
A security operation center (SOC) analyst detects repetitive API calls sending inputs to an AI solution. Which of the following attacks has MOST likely occurred?

Answer: C

Explanation:
Repetitive API calls with systematically crafted inputs are characteristic of attempts to query a model extensively to reconstruct its behavior or parameters, which is indicative of a model extraction attack.


NEW QUESTION # 363
Which testing technique is BEST for determining how an AI model makes decisions?

Answer: D

Explanation:
AAISM indicates that white-box testing allows evaluators full visibility into:
* internal logic
* weights
* decision pathways
* model architecture
This makes it ideal for understanding how decisions are made.
Black box (B) provides no internal visibility. Red/blue team tests (A, D) focus on security, not decision mechanics.
References: AAISM Study Guide - AI Testing; Explainability Through White-Box Analysis.


NEW QUESTION # 364
Which of the following BEST enables an organization to maintain visibility to its AI usage?

Answer: D

Explanation:
The AAISM framework stresses that the most effective way to maintain oversight of organizational AI usage is by maintaining a comprehensive inventory of all AI systems and the business units using them. Such an inventory provides a centralized, transparent record of where AI is deployed, ensuring accountability, monitoring, and compliance. While board approval, dashboards, and KPIs are important governance tools, they do not provide holistic visibility across the enterprise. The inventory ensures traceability and governance alignment, making it the best method to maintain visibility of AI usage.
References:
AAISM Study Guide - AI Governance and Program Management (AI Inventories) ISACA AI Security Management - Centralized Oversight of AI Assets


NEW QUESTION # 365
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