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NEW QUESTION # 252
A post-incident investigation finds that an AI-powered anti-money laundering system inadvertently allowed suspicious transactions because certain risk signals were disabled to reduce false positives. Which of the following governance failures does this BEST demonstrate?
Answer: C
Explanation:
AAISM requires formal model change governance: documented justification, risk assessment, validation
/verification (V&V), approvals, and post-deployment monitoring when altering features, thresholds, or signals. Disabling risk indicators to reduce false positives without rigorous validation and controlled rollout reflects a failure in model validation and change control, which AAISM treats as a core safeguard against unintended harms and regulatory breaches.
References: AI Security Management (AAISM) Body of Knowledge - Model Risk Governance; Change Management & Approvals; Validation/Verification Requirements. AAISM Study Guide - Control Gates for Feature/Threshold Changes; Post-Change Monitoring and Backout Criteria.
NEW QUESTION # 253
A bank is training an AI credit scoring model on a vast amount of sensitive customer data. Which of the following is the MOST critical security risk in this training process?
Answer: A
NEW QUESTION # 254
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.
References:
AAISM Study Guide - AI Risk Management (Adversarial Threats and Availability Risks) ISACA AI Security Management - Attack Classifications
NEW QUESTION # 255
Which of the following is MOST important to consider when validating a third-party AI tool?
Answer: B
Explanation:
The AAISM framework specifies that when adopting third-party AI tools, the right to audit is the most critical contractual and governance safeguard. This ensures that the organization can independently verify compliance with security, privacy, and ethical requirements throughout the lifecycle of the tool. Terms and conditions provide general usage guidance but often limit liability rather than ensuring transparency. Industry certifications may indicate good practice but do not substitute for direct verification. Roundtable testing is useful for evaluation but lacks enforceability. Only the contractual right to audit provides formal assurance that the tool operates in accordance with organizational policies and external regulations.
References:
AAISM Exam Content Outline - AI Governance and Program Management (Third-Party Governance) AI Security Management Study Guide - Vendor Oversight and Audit Rights
NEW QUESTION # 256
Which of the following BEST ensures the integrity of data sets used to train AI models?
Answer: B
Explanation:
AAISM defines cryptographic tracking and verification as the best control for ensuring the integrity of training data. By applying hashing and verification methods, organizations can confirm that datasets remain unaltered and authentic throughout collection, storage, and processing.
Collecting only necessary data, proper storage, or clear documentation all support governance and compliance, but they do not guarantee that the data has not been tampered with. Integrity is specifically ensured by cryptographic verification techniques.
NEW QUESTION # 257
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