AAISM Exam Topic, AAISM Valid Test Book

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ISACA AAISM Exam Syllabus Topics:

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

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q59-Q64):

NEW QUESTION # 59
Which of the following controls BEST builds user trust in AI application output?

Answer: C

Explanation:
Displaying model reasoning helps users understand how conclusions are reached, increasing transparency and confidence in the output, which directly builds trust.


NEW QUESTION # 60
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: A

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 # 61
The PRIMARY objective of performing tests to detect membership inference in machine learning (ML) models is to determine whether the model:

Answer: C

Explanation:
Membership inference testing evaluates whether a model can disclose whether specific data points were part of its training dataset, indicating potential leakage of sensitive information about the data it was trained on.


NEW QUESTION # 62
After implementing a third-party generative AI tool, an organization learns about new regulations related to how organizations use AI. Which of the following would be the BEST justification for the organization to decide not to comply?

Answer: D

Explanation:
The AAISM framework clarifies that compliance decisions must always be tied to an organization's risk appetite and tolerance. When new regulations emerge, management may choose not to comply if the associated risk remains within the documented and approved risk appetite, provided that accountability is established and governance structures support this decision. Other options such as widespread industry use, third-party audits, or lack of cost assessment do not justify noncompliance under the governance principles. The risk appetite framework is the only recognized justification under AI governance principles.


NEW QUESTION # 63
A healthcare provider uses a third-party large language model (LLM) to summarize patient records. A risk analysis indicates a high likelihood of potential data leakage in excess of the organization's risk tolerance. Which of the following is the BEST course of action taken by the vendor to reduce risk to an acceptable level?

Answer: C

Explanation:
Migrating the LLM workload to a private instance and restricting access most effectively reduces the risk of sensitive patient data leakage. This approach provides stronger control over data handling, processing environments, access management, and exposure pathways, making it the most appropriate risk reduction measure for healthcare data.


NEW QUESTION # 64
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