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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q213-Q218):
NEW QUESTION # 213
An organization is deploying an automated AI cybersecurity system. Which of the following would be the MOST effective strategy to minimize human error and improve overall security?
Answer: D
Explanation:
Training detection models on relevant, representative historical data improves signal quality, reduces false positives, and automates triage-directly lowering human workload and error rates (e.g., alert fatigue, missed correlations). Penetration testing is valuable but episodic and does not systematically reduce day-to-day operator error. "Ensure responsible use" is a governance aim, not a concrete method to cut human error in detection. Manual monitoring increases reliance on human judgment and is prone to inconsistency.
References: AI Security Management™ (AAISM) Body of Knowledge: Model Development & Evaluation Controls; Data Selection and Representativeness; Operationalization to Reduce Human Error. AAISM Study Guide: Tuning Detection Systems with Historical Corpora; Alert Quality, Precision/Recall, and SOC Workflow Integration.
NEW QUESTION # 214
Which approach should an organization prioritize to effectively verify the security of its AI models?
Answer: A
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 # 215
Which of the following would BEST ensure a proper business continuity plan (BCP) is in place for an AI solution?
Answer: D
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 # 216
Which of the following employee awareness topics would MOST likely be revised to account for AI-enabled cyber risk?
Answer: C
Explanation:
AAISM training guidance specifies that social engineering is the awareness topic most impacted by AI- enabled risks. With generative AI and deepfake technologies, attackers can create highly convincing phishing messages, synthetic voices, or fake executive requests, increasing the sophistication of social engineering attacks. Clean desk policies, insider threat awareness, and authentication procedures remain relevant but are not directly altered by AI advancements. The most likely revision to employee awareness programs in the AI era is therefore enhanced social engineering awareness.
References:
AAISM Exam Content Outline - AI Risk Management (Human Factors and Awareness) AI Security Management Study Guide - Social Engineering Risks with AI
NEW QUESTION # 217
As organizations increasingly rely on vendors to develop AI systems, which of the following is the MOST effective way to monitor vendors and ensure compliance with ethical and security standards?
Answer: B
Explanation:
AAISM vendor governance guidance identifies regular audits of vendor processes as the most effective method of ensuring compliance with ethical and security standards. Independent audits provide verifiable assurance that vendors are meeting agreed-upon requirements. Self-attestation, internal monitoring, or documentation sharing provide some transparency but do not guarantee compliance. The best practice, particularly for high-risk AI deployments, is independent and recurring audits of vendor processes.
References:
AAISM Exam Content Outline - AI Risk Management (Vendor Oversight)
AI Security Management Study Guide - Vendor Audit and Compliance Assurance
NEW QUESTION # 218
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