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[General] AAISM Latest Dumps Book, Authorized AAISM Test Dumps

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【General】 AAISM Latest Dumps Book, Authorized AAISM Test Dumps

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PassTestking would give you access to ISACA Advanced in AI Security Management (AAISM) Exam (AAISM) exam questions that are factual and unambiguous, as well as information that is important for the preparation of the AAISM exam. You won't be anxious because the available ISACA Advanced in AI Security Management (AAISM) Exam (AAISM) exam dumps are structured instead of distributed. ISACA Advanced in AI Security Management (AAISM) Exam (AAISM) certification exam candidates have specific requirements and anticipate a certain level of satisfaction before buying a ISACA AAISM practice exam. The ISACA Advanced in AI Security Management (AAISM) Exam (AAISM) practice exam applicants can rest assured that PassTestking's round-the-clock support staff will answer their questions.
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 (Q34-Q39):NEW QUESTION # 34
After deployment, an AI model's output begins to drift outside of the expected range. Which of the following is the development team's BEST course of action?
  • A. Take the AI model offline
  • B. Return to an earlier phase in the AI life cycle
  • C. Create an emergency change request to correct the issue
  • D. Adjust the hyperparameters of the AI model
Answer: B
Explanation:
AAISM emphasizes that when model drift occurs, the best response is not a quick fix but rather to revisit an earlier phase of the AI life cycle to address data quality, retraining, or evaluation processes. Simply taking the model offline halts functionality without resolution, while adjusting hyperparameters or issuing emergency changes treats the symptom rather than the root cause. Proper governance requires returning to the design or training phases to re-establish stability, accuracy, and compliance of the model. Thus, the correct approach is to return to an earlier AI lifecycle phase.
References:
AAISM Exam Content Outline - AI Risk Management (Model Drift and Lifecycle Responses) AI Security Management Study Guide - Continuous Improvement in AI Lifecycle

NEW QUESTION # 35
Which of the following AI system vulnerabilities is MOST easily exploited by adversaries?
  • A. Inaccurate generalizations from new data by the AI model
  • B. Inability to detect input modifications causing inappropriate AI outputs
  • C. Weak controls for access to the AI model
  • D. Lack of protection against denial of service (DoS) attacks
Answer: C
Explanation:
AAISM study materials stress that weak access controls are the most easily exploited vulnerability in AI systems. Without strong access restrictions, adversaries can directly query, extract, manipulate, or overload models, leading to data leakage or compromised outputs. While inaccurate generalizations, DoS vulnerabilities, or susceptibility to input manipulation are serious, they typically require more effort or specific conditions. Weak access control provides the most direct and immediate entry point for attackers. As such, it is identified as the most easily exploited vulnerability.
References:
AAISM Exam Content Outline - AI Risk Management (Access and Authentication Vulnerabilities) AI Security Management Study Guide - Exploitable Weaknesses in AI Systems

NEW QUESTION # 36
An organization plans to use AI to analyze the shopping patterns of its customers to predict interests and send targeted, customized marketing emails. Which of the following should be done FIRST?
  • A. Verify customer email addresses
  • B. Update the terms of service
  • C. Obtain customer consent
  • D. Train the marketing department
Answer: C
Explanation:
The first action, before any processing of personal data for AI-driven profiling and targeted communications, is to establish a lawful basis for processing. Under AAISM-aligned privacy governance, explicit and informed consent is prioritized for new or sensitive uses such as interest profiling and targeted marketing.
Consent ensures purpose limitation, transparency, and user control prior to model ingestion and campaign activation. Training teams, updating terms of service, or verifying contact details are important, but they do not provide legal authority to process data; therefore, they follow after consent is obtained.
References: AI Security Management (AAISM) Body of Knowledge - Privacy Governance and Lawful Basis; Purpose Limitation and Transparency; Consent Management in AI-enabled Marketing. AAISM Study Guide - Data Protection Controls for AI Profiling; Consent Capture and Record-Keeping.

NEW QUESTION # 37
Which approach should an organization prioritize to effectively verify the security of its AI models?
  • A. Automating vulnerability identification
  • B. Using standard penetration testing methods
  • C. Developing a testing strategy including AI-specific threat modeling and adversarial attack simulations
  • D. Testing team competencies in IT threat mitigation
Answer: C
Explanation:
The AAISM standard explicitly states that traditional penetration tests alone are insufficient for AI systems.
Effective AI security testing requires:
* AI-specific threat modeling (e.g., data poisoning, prompt injection, model theft)
* Adversarial attack simulations (white-box, black-box, gradient-based attacks)
* Evaluation of robustness and manipulation resistance
Option B captures these requirements precisely.
Options A, C, and D do not address AI-specific attack vectors.
References: AAISM Study Guide - AI Security Testing and Adversarial Evaluation.

NEW QUESTION # 38
Which of the following would BEST help an organization align its AI initiatives with business objectives?
  • A. Complying with applicable AI-related regulations
  • B. Ensuring ethical use of AI technologies in projects
  • C. Protecting enterprise information used by AI projects
  • D. Establishing an AI governance committee
Answer: D
Explanation:
An AI governance committee provides cross-functional oversight to align AI strategy, investment, and risk appetite with business goals. It sets policies, prioritizes portfolios, ensures accountability, and integrates compliance, ethics, and security into decision-making. While compliance, ethics, and information protection are essential, governance is the primary mechanism that systematically connects AI initiatives to enterprise objectives.
References: AI Security Management (AAISM) Body of Knowledge: AI Governance Operating Model- Structures, Roles, and Decision Rights; AAISM Study Guide: Strategic Alignment, Portfolio Oversight, and Accountability Mechanisms.

NEW QUESTION # 39
......
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