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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Exam Price:USD 459 (member) / USD 599 (non-member)
Exam Duration:150 minutes
Exam Format:Multiple-choice questions
Related Certifications:CISM
CISSP
Certificate Validity Period:3 years (continuing professional education required for renewal)
Passing Score:450/800
Available Languages:Spanish, English
Real Exam Qty:90
Recommended Training:ISACA Official Training & Review Materials
Exam Registration:ISACA AAISM Credentialing Page
Sample Questions:ISACA AAISM Sample Questions
Exam Way:Computer-based exam (online proctored or authorized test center)
Pre Condition:Recommended: Active CISM or CISSP certification and experience in IT/security management or advisory roles
Official Syllabus URL:https://www.isaca.org/credentialing/aaism

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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 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 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 (Q390-Q395):

NEW QUESTION # 390
An organization is evaluating a SaaS-based HR system that uses AI for resume vetting. Which control is MOST important?

Answer: B

Explanation:
AAISM states that HR systems performing candidate evaluation must prioritize training data fairness, representativeness, and bias mitigation because biased HR decisions carry regulatory, ethical, and litigation risks.
Backups (B) and encryption (D) relate to availability and confidentiality, not fairness. Conformity assessments (C) are helpful but secondary.
References: AAISM Study Guide - AI Bias and Fairness; High-Risk HR Use Cases.


NEW QUESTION # 391
Which of the following should be included in an AI acceptable use policy?

Answer: A

Explanation:
An AI acceptable use policy (AUP) sets the organizational expectations and boundaries for how AI systems may be used by employees and third parties. AAISM guidance places emphasis on ethical and legal compliance standards as core elements of an AUP to govern responsible behavior, prevent misuse, and align with regulatory and organizational principles. While data requirements, collection/storage processes, and monitoring may be covered in adjacent standards and procedures (e.g., data management policies, SOPs, and operational runbooks), the AUP's essential function is to codify permissible use anchored to ethics, legality, and organizational values.
References: AI Security Management (AAISM) Body of Knowledge - AI Governance Policies and Codes of Conduct; Responsible Use Principles. AAISM Study Guide - Policy Hierarchy and Control Mapping; Acceptable Use and Staff Obligations.


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: D

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
Which of the following approaches BEST enables the separation of sensitive and shareable data to prevent an AI chatbot from inadvertently disclosing confidential information?

Answer: A

Explanation:
AAISM materials describe data segregation and segmented access as core technical controls to prevent unintended information disclosure by AI systems. Siloing refers to logically or physically separating data into distinct repositories or contexts, ensuring that sensitive datasets are not available to components or applications that only require non-sensitive information. This is directly aligned with preventing a chatbot from accessing or mixing confidential data with general conversational content. Zero Trust (A) is an overarching security architecture principle, focusing on identity and continuous verification; it does not by itself guarantee separation of data. Sandboxing (B) isolates processes but is less about fine-grained data separation. Containerization (D) packages applications and their dependencies, again not necessarily solving the specific problem of mixing sensitive and non-sensitive datasets. Siloing is explicitly highlighted as a way to prevent cross-context leakage in AI use cases.
References: AI Security Management™ (AAISM) Study Guide - Technical Controls for AI Data Protection; Data Segregation and Access Boundaries.


NEW QUESTION # 394
Which of the following BEST enables an organization to minimize risk from shadow AI?

Answer: B

Explanation:
Detective controls provide visibility into unauthorized AI usage, while employee training promotes awareness and responsible behavior. Together, they address both detection and prevention, making them the most effective approach to minimizing risks associated with shadow AI.


NEW QUESTION # 395
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