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NEW QUESTION # 39
Which of the following is the MOST important course of action prior to placing an in-house developed AI solution into production?
Answer: C
Explanation:
AAISM lifecycle governance guidance specifies that before any AI solution is moved into production, it must undergo testing, evaluation, validation, and verification to ensure accuracy, resilience, security, and compliance with standards. These steps confirm that the solution performs as expected under varied conditions. Conducting gap analysis is part of compliance checks but comes earlier in design. Management sign-off provides approval but cannot substitute for assurance of technical reliability. Deploying prototypes is a testing method but not the final assurance step. The critical requirement is a complete cycle of testing, validation, and verification.
NEW QUESTION # 40
How can an organization BEST protect itself from payment diversions caused by deepfake attacks impersonating management?
Answer: C
Explanation:
AAISM's risk management framework stresses that the most effective defense against deepfake-enabled fraud, such as payment diversion, is resilient payment approval processes. This includes multi-step verification, segregation of duties, and independent confirmations for high-value transactions. Employee training, policies, or limiting payment frequency may reduce exposure, but they cannot guarantee prevention.
Only process-based controls enforce structural safeguards that prevent fraudulent instructions from being executed, even if a deepfake impersonation attempt is successful.
References:
AAISM Exam Content Outline - AI Risk Management (Fraud and Deepfake Risk) AI Security Management Study Guide - Transactional Resilience and Controls
NEW QUESTION # 41
When evaluating a new AI tool for intrusion prevention, which is MOST important to ensure fit within the existing program architecture?
Answer: B
Explanation:
AAISM stresses that AI tools must align with the organization's existing control objectives and governance requirements, ensuring consistency with risk management, detection philosophy, and operational processes.
NEW QUESTION # 42
An organization uses an AI tool to scan social media for product reviews. Fraudulent social media accounts begin posting negative reviews attacking the organization's product. Which type of AI attack is MOST likely to have occurred?
Answer: B
Explanation:
The AAISM materials classify availability attacks as attempts to disrupt or degrade the functioning of an AI system so that its outputs become unreliable or unusable. In this scenario, the fraudulent social media accounts are deliberately overwhelming the AI tool with misleading negative reviews, undermining its ability to deliver accurate sentiment analysis. This aligns directly with the concept of an availability attack. Model inversion relates to reconstructing training data from outputs, deepfakes involve synthetic content generation, and data poisoning corrupts the training set rather than manipulating inputs at runtime. Therefore, the fraudulent review campaign is most accurately identified as an availability attack.
NEW QUESTION # 43
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?
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 # 44
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