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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q171-Q176):
NEW QUESTION # 171
An organization has implemented a natural language processing model to respond to customer questions when personnel are not available. A pre-implementation security assessment revealed attackers could access sensitive company data through a chat interface injection attack. Which of the following is the BEST way to prevent this attack?
Answer: B
Explanation:
To prevent prompt/interface injection, AAISM prioritizes preventive technical controls at the boundary: input validation/sanitization, structured templates/system prompts, allow/deny lists, and context isolation. These measures constrain user-supplied content and block adversarial instructions from being interpreted as system directives. Monitoring (A) and audits (D) are detective/assurance activities; manual output review (B) is compensating but less scalable and does not prevent injection.
References: AI Security Management™ (AAISM) Body of Knowledge - Secure Prompting & Input Controls; Interface Injection Mitigations; Context and Instruction Isolation Patterns.
NEW QUESTION # 172
During the deployment of a generative AI platform, a risk assessment highlighted threats such as data leakage and prompt manipulation. Which of the following is the BEST way to ensure appropriate control selection?
Answer: B
Explanation:
AAISM requires that control selection be threat-led and context-specific, aligning AI threats to the organization's existing enterprise control catalogs (security, privacy, resilience) and augmenting them with AI- specific safeguards where coverage is insufficient. This ensures consistency with the risk appetite, removes duplication, and closes AI-unique gaps (e.g., prompt injection, data leakage from context windows, model misuse). Generic reliance on vendors or uncustomized external frameworks does not ensure fit-for-purpose coverage, and deferring control selection to post-deployment contradicts proactive risk treatment.
References: AI Security Management™ (AAISM) Body of Knowledge - Governance & Program Controls; Control Selection and Tailoring; Threat-to-Control Mapping for AI Systems; Risk Appetite & Control Assurance Alignment.
NEW QUESTION # 173
A school district contracts a third-party provider for AI-based curriculum recommendations. Which of the following is the BEST way to ensure the vendor uses AI responsibly?
Answer: A
Explanation:
AAISM emphasizes transparency artifacts from vendors to enable due diligence and assurance. A model card documents intended use, data sources, limitations, performance across subgroups, known risks, and evaluation procedures-information necessary to assess safety, fairness, and compliance for sensitive contexts like education. SSO and support are useful operational features; generic ToS updates are insufficient without model-specific disclosures.
References: AI Security Management™ (AAISM) Body of Knowledge - Third-Party & Supply Chain Governance; Transparency Artifacts (Model Cards, Datasheets). AAISM Study Guide - Vendor Due Diligence Requirements; Documentation for Risk, Fairness, and Intended Use.
NEW QUESTION # 174
Which of the following BEST ensures AI components are validated as part of disaster recovery testing?
Answer: D
Explanation:
Business continuity and disaster recovery (BC/DR) exercises for AI must validate that critical AI components (feature stores, model registries, inference services, pipelines) operate within agreed recovery objectives during failover and restoration. Monitoring and evaluating model performance and stability during DR tests provides objective evidence that AI services remain functional, accurate, and reliable under contingency conditions, thereby validating the AI stack end-to-end.
Option A focuses on retraining during outages (a niche scenario) rather than validating service continuity for production inference. Option B is security testing, not BC/DR validation. Option C tests data loss handling but does not comprehensively validate AI service behavior across failover and recovery.
References: AI Security Management (AAISM) Body of Knowledge: "Operational Resilience-BC/DR for AI Systems," "Validation and Evidence of Continuity"; AAISM Study Guide: "AI DR Test Planning- Metrics, Model Performance Validation, and Recovery Readiness."
NEW QUESTION # 175
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?
Answer: B
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 # 176
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