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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | Advanced in AI Security Management (AAISM) Exam |
| Exam Number: | AAISM |
| Passing Score: | 450/800 |
| Certificate Validity Period: | 3 years (continuing professional education required for renewal) |
| Exam Price: | USD 459 (member) / USD 599 (non-member) |
| Exam Format: | Multiple-choice questions |
| Available Languages: | Spanish, English |
| Related Certifications: | CISM CISSP |
| Exam Duration: | 150 minutes |
| 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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NEW QUESTION # 239
Which approach should an organization prioritize to effectively verify the security of its AI models?
Answer: D
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
NEW QUESTION # 240
Which of the following AI system use cases would present the GREATEST regulatory compliance risk for an organization expanding into foreign markets?
Answer: B
Explanation:
Employee performance ranking involves evaluating individuals and making decisions that can directly affect employment outcomes. In foreign markets, this type of processing is often subject to strict labor laws, anti-discrimination regulations, and data protection requirements, creating the highest regulatory compliance risk.
NEW QUESTION # 241
Which of the following AI-specific security monitoring metrics BEST enables the real-time detection of attempts to evade an AI model?
Answer: C
Explanation:
Evasion attacks typically involve crafted anomalous inputs designed to manipulate the AI model into producing incorrect or unexpected outputs. Monitoring for anomalous input patterns that result in unusual model behavior provides the most effective real-time indicator of attempted evasion attacks.
NEW QUESTION # 242
A financial organization is concerned about the risk of prompt injection attacks on its customer service chatbot. Which of the following controls BEST addresses this concern?
Answer: A
Explanation:
AAISM emphasizes preventive technical controls for LLM threats such as prompt injection, including input validation/sanitization, instruction isolation, allow/deny lists, context segmentation, and output filtering.
These reduce the model's exposure to adversarial instructions embedded in user prompts or retrieved context.
Monitoring (A) is detective, not preventive; increasing parameters (B) does not inherently improve security against injection; human-in-the-loop (D) is valuable for high-risk decisions but does not directly neutralize injection vectors at the control boundary the way input validation and content filtering do.
References: AI Security Management (AAISM) Body of Knowledge - Technical Controls for LLM Security; Input/Output Filtering and Context Isolation; Secure Inference and Prompt Injection Mitigations.
NEW QUESTION # 243
To ensure the ethical and responsible use of AI, which of the following AI usage policy metrics is MOST important for an organization to monitor?
Answer: D
Explanation:
AAISM emphasizes governance effectiveness metrics tied to real lifecycle checkpoints. The count (and percentage) of AI projects that completed policy compliance review before deployment is a leading indicator of policy enforcement and assurance. It directly reflects whether responsible-AI requirements (risk assessment, impact assessment, data/privacy checks, security controls) are embedded in practice. Consult frequency (A) and review cadence (D) are activity metrics, not outcomes. Reported violations (B) are lagging indicators and can be deceptive (low numbers may indicate under-reporting).
References:* AI Security Management (AAISM) Body of Knowledge: Program KPIs-policy adoption, stage-gate compliance, audit readiness* AAISM Study Guide: Governance metrics for Responsible AI- coverage of reviews, pass/fail rates, exceptions handling
NEW QUESTION # 244
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