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NEW QUESTION # 87
Which of the following is BEST to review in order to detect issues related to data used throughout an AI system's life cycle?
Answer: C
Explanation:
Data flow diagrams provide a comprehensive view of how data moves through the system across all stages of the AI life cycle, enabling identification of issues related to data handling, transformation, and usage.
NEW QUESTION # 88
A pharmaceutical organization uses an AI solution from a third-party vendor to analyze confidential research and development data. Which of the following controls is MOST essential to ensure the vendor's AI solution complies with the organization's security requirements?
Answer: C
Explanation:
Reviewing the vendor's independent security audit report provides objective assurance that the vendor's AI solution and related controls have been evaluated against recognized security standards and requirements. This is essential for validating compliance with the organization's security expectations when handling confidential research data.
NEW QUESTION # 89
Which of the following is the GREATEST benefit of implementing an AI tool to safeguard sensitive data and prevent unauthorized access?
Answer: D
Explanation:
The AAISM study materials highlight that AI-powered security tools provide the greatest benefit by reducing false positives in monitoring and access control systems. This improves efficiency, prevents alert fatigue, and enables security teams to focus on true threats. While timely analysis and incident response are benefits, they are not unique to AI-based tools and can be achieved with traditional methods. AI also does not remove the need for data classification, as classification underpins governance and compliance. The standout advantage is the improved accuracy and reduced false positives provided by AI.
References:
AAISM Study Guide - AI Technologies and Controls (Security Tools and Access Management) ISACA AI Security Management - Benefits of AI-Enabled Security
NEW QUESTION # 90
Which of the following is MOST important to ensure security throughout the AI data life cycle?
Answer: A
Explanation:
AAISM emphasizes data lineage, provenance tracking, and inventory completeness as essential controls to ensure data security and accountability across all AI data life-cycle phases. This enables detection of unauthorized modifications, improper use, and compliance violations.
Periodic reviews (B) are necessary but insufficient without lineage. Restricting third-party use (C) is one control but not comprehensive. Open-source model choice (A) does not secure data.
References: AAISM Study Guide - AI Data Governance; Lineage and Traceability.
NEW QUESTION # 91
An organization implementing a large language model (LLM) application notices significant and unexpected cost increases due to excessive computational resource usage. Which vulnerability is MOST likely in need of mitigation?
Answer: C
Explanation:
AAISM highlights unbounded consumption (token/payment exhaustion, unmetered tool calls, prompt bombs) as a key LLM risk affecting cost and availability. Controls include request quotas, max tokens, rate-limits, budget guards, circuit breakers, and cost-aware routing. Excessive agency (A) relates to unsupervised actions; sensitive disclosure (B) and prompt leakage (C) are confidentiality risks, not primary drivers of runaway compute spend.
References: AI Security Management™ (AAISM) Body of Knowledge - LLM Risk Taxonomy (Abuse & Cost Risks); Guardrails: Rate-Limiting, Quotas, and Budget Controls; Resilience and Cost-Containment Patterns.
NEW QUESTION # 92
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