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ISACA AAISM Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:	AAISM
Passing Score:	450/800
Available Languages:	English, Spanish
Exam Duration:	150 minutes
Certificate Validity Period:	3 years
Real Exam Qty:	90
Exam Format:	Multiple Choice, Scenario-based Questions
Related Certifications:	ISACA Advanced in AI Security Management (AAISM)
Exam Price:	USD $399
Sample Questions:	ISACA AAISM Sample Questions
Exam Way:	Online remote proctored exam or test center exam
Pre Condition:	Candidates must hold an active CISM or CISSP certification.
Official Syllabus URL:	https://www.isaca.org/credentialing/aaism/aaism-exam-content-outline

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ISACA AAISM Exam Syllabus Topics:

Topic	Details
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 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 3	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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q68-Q73):

NEW QUESTION # 68
Which of the following controls would BEST help to prevent data poisoning in AI models?

A. Establishing continuous monitoring
B. Regularly updating the foundational model
C. Implementing a strict data validation mechanism
D. Increasing the size of the training data set

Answer: C

Explanation:
The most direct preventative control against data poisoning is robust data validation/ingestion gating:
provenance checks, schema and constraint validation, anomaly/outlier screening, label consistency tests, and whitelist/blacklist source controls before data reaches training pipelines. Larger datasets (A) don't inherently prevent poisoning; monitoring (C) is detective; updating a foundation model (D) does not address tainted inputs entering the pipeline.
References: AI Security Management (AAISM) Body of Knowledge - Adversarial ML Threats and Training-Time Attacks; Secure Data Ingestion and Validation Controls. AAISM Study Guide - Poisoning Prevention: Provenance, Validation, and Sanitization Gates.

NEW QUESTION # 69
A SaaS-based LLM system has risks including prompt injection, data poisoning, and model exfiltration. What is the BEST way to ensure consistent risk treatment?

A. Apply control baselines from a recognized industry standard
B. Rely on vendor audit reports and SLAs
C. Focus on post-deployment red teaming
D. Implement an AI threat control matrix mapping threats to controls and assurance

Answer: D

Explanation:
AAISM highlights the importance of an AI threat-control matrix that:
* maps threats (e.g., poisoning, exfiltration, injection)
* identifies required controls
* defines assurance/testing activities
* ensures consistent coverage across all AI components
Control baselines (A) are useful but not AI-specific. Red teaming (C) is reactive and not comprehensive.
Vendor reports (D) are supplemental, not sufficient.
References: AAISM Study Guide - AI Risk Treatment; Threat-Control Mapping.

NEW QUESTION # 70
Which strategy is MOST effective for penetration testers assessing an AI model against membership inference attacks?

A. Disabling model logging
B. Generating synthetic training data
C. Measuring accuracy on the test set
D. Analyzing AI model confidence scores

Answer: D

Explanation:
AAISM specifies that membership inference attacks often exploit unusually high confidence scores when the model encounters data points used during training. Penetration testers identify vulnerability by analyzing model confidence behavior across known and unknown samples.
Synthetic data (A) does not test inference leakage. Disabling logs (C) removes evidence and reduces visibility. Test-set accuracy (D) is unrelated.
References: AAISM Study Guide - AI Privacy Attacks; Membership Inference Testing Techniques.

NEW QUESTION # 71
Which of the following BEST enables an organization to maintain visibility to its AI usage?

A. Maintaining a comprehensive inventory of AI systems and business units that leverage them
B. Maintaining a monthly dashboard that captures all AI vendors
C. Measuring the impact of AI implementation using key performance indicators (KPIs)
D. Ensuring the board approves the policies and standards that define corporate AI strategy

Answer: A

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.

NEW QUESTION # 72
Which of the following is the BEST way to reduce the risk of misuse of an AI agent that has access to critical data and systems?

A. Allow users to configure the agent for productivity
B. Validate agent compliance with output restrictions
C. Limit human review of AI decisions
D. Prohibit users from manipulating agent behavior

Answer: B

Explanation:
AAISM frameworks highlight output-based controls, including output filtering, restriction validation, and policy-aligned guardrails as primary defenses for AI agents with high privileges. Ensuring the agent does not output unauthorized instructions or sensitive data directly mitigates misuse.

NEW QUESTION # 73
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