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[General] Pass Guaranteed 2026 Updated AAISM: New ISACA Advanced in AI Security Management

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【General】 Pass Guaranteed 2026 Updated AAISM: New ISACA Advanced in AI Security Management

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ISACA AAISM Exam Syllabus Topics:
TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q136-Q141):NEW QUESTION # 136
Which of the following AI system vulnerabilities is MOST easily exploited by adversaries?
  • A. Inability to detect input modifications causing inappropriate AI outputs
  • B. Lack of protection against denial of service (DoS) attacks
  • C. Inaccurate generalizations from new data by the AI model
  • D. Weak controls for access to the AI model
Answer: D
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 # 137
During the creation of a new large language model (LLM), an organization procured training data from multiple sources. Which of the following is MOST likely to address the CISO's security and privacy concerns?
  • A. Data augmentation
  • B. Data minimization
  • C. Data classification
  • D. Data discovery
Answer: B
Explanation:
AAISM guidance highlights data minimization as a critical practice for addressing both security and privacy concerns. By ensuring that only the minimum necessary data is collected and retained, the organization reduces the risk of sensitive information being exposed or misused during training. Data augmentation expands data but does not mitigate privacy risk. Classification organizes data but does not limit exposure.
Data discovery helps locate sources but does not directly reduce risks. The control that directly aligns with privacy-by-design principles is data minimization.
References:
AAISM Exam Content Outline - AI Risk Management (Data Privacy and Minimization) AI Security Management Study Guide - Privacy Safeguards in AI Training

NEW QUESTION # 138
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models leveraging fraud detection systems?
  • A. Enhancing the accuracy of predictions to desired levels
  • B. Increasing model training speed for an efficient launch
  • C. Protecting individual data contributions while allowing statistical analysis
  • D. Reducing computational resources required for the model training phase
Answer: C
Explanation:
Differential privacy aims to protect the privacy of any single individual's data contribution while still enabling useful aggregate learning and statistical analysis. Noise mechanisms are calibrated so that results remain informative for modeling (e.g., fraud patterns) without revealing whether any particular person's data was included or enabling inference about them. Accuracy, speed, and compute efficiency can be secondary considerations, but the primary objective is privacy protection with utility preserved.
References: AI Security Management™ (AAISM) Body of Knowledge: Privacy-Preserving ML; Differential Privacy Objectives and Mechanisms. AAISM Study Guide: Individual Contribution Protection; Utility- Privacy Trade-offs and Calibration in Applied Models.

NEW QUESTION # 139
Which of the following would BEST ensure a proper business continuity plan (BCP) is in place for an AI solution?
  • A. Testing the AI infrastructure failover mechanisms
  • B. Implementing access controls to protect the AI system from unauthorized use
  • C. Increasing the detail of AI solution backup and restoration processes
  • D. Enhancing monitoring and detection of model failures and anomalies
Answer: A
Explanation:
Effective AI BCP requires validation through exercises and controlled failover tests to prove recovery objectives can be met in practice. Merely documenting backups (Option D), hardening access (Option B), or improving monitoring (Option A) does not confirm that the AI stack-data pipelines, feature stores, model registries, inference services, and dependent infrastructure-can actually fail over and recover within RTO
/RPO. AAISM prescribes periodic BCP/DR testing (including model artifact restoration, configuration reconstitution, dependency failover, and data pipeline continuity) to verify readiness and identify gaps before real incidents.
References:AI Security Management™ (AAISM) Body of Knowledge: Business Continuity & Disaster Recovery for AI; Validation and Exercising of Continuity Plans; RTO/RPO for Models, Data, and Pipelines.
AAISM Study Guide: Operational Resilience for AI Systems; BCP/DR Test Scenarios (model registry, feature store, pipeline recovery); Continuity Metrics and Evidence of Readiness.

NEW QUESTION # 140
An organization is facing a deepfake attack intended to manipulate stock prices. The organization's crisis communication plan has been activated. Which of the following is MOST important to include in the initial response?
  • A. Conduct employee awareness training on recognizing deepfake videos and audio
  • B. Engage with brand monitoring services to track social media activity
  • C. Provide clarifying information in a pre-approved public statement
  • D. Conduct a detailed forensic analysis to identify the source of the deepfake
Answer: C
Explanation:
AAISM guidance on crisis management and communication emphasizes that the initial priority in responding to a reputational or market manipulation attack is to provide accurate clarifying information to the public through a pre-approved statement. This ensures stakeholders and markets are given verified facts immediately, limiting the spread of misinformation. While forensic analysis, employee training, and monitoring activities are important, they occur after the immediate need for public trust and damage control is addressed. Pre-approved statements are a central control in AI-related incident response to ensure consistency, timeliness, and credibility in communications.
References:
AAISM Study Guide - AI Governance and Program Management (Incident Response and Crisis Communication) ISACA AI Security Management - Public Communication and Trust Preservation

NEW QUESTION # 141
......
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