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NEW QUESTION # 296
Security and assurance requirements for AI systems should FIRST be embedded in the:
Answer: C
Explanation:
AAISM directs organizations to embed security, safety, and compliance controls at design time ("secure-by- design" and "shift-left"), ensuring requirements for robustness, privacy, and governance are defined as non- functional constraints on architecture, data sourcing, model choices, and evaluation criteria before any model is trained. Deferring these requirements to training, testing, or deployment increases residual risk and rework, and weakens traceability of control coverage.
References:* AI Security Management™ (AAISM) Body of Knowledge: Governance-Secure-by-Design; Policy-to-Control Traceability; Requirements Management* AAISM Study Guide: AI Program Lifecycle- Planning & Design Controls; Design-time Threat Modeling and Control Selection* AAISM Mapping to Standards: Design-phase Risk Identification and Requirements Engineering for AI
NEW QUESTION # 297
A global organization has experienced multiple incidents of staff copying confidential data into public chatbots and acting on the model outputs. Which of the following is MOST important to reduce short-term risk when launching an AI security awareness initiative?
Answer: B
Explanation:
AAISM prescribes targeted, role-based, scenario-driven training aligned to policy and job tasks as the highest-impact near-term intervention for human-factor AI risks. By mapping concrete "do/don't" behaviors (e.g., what data may/may not be pasted into public chatbots, required redaction steps, approved tools, verification of outputs) to specific roles, organizations rapidly reduce incident likelihood and harmful actions.
* A (blocking) is a technical containment option but is not an awareness-initiative control and may cause workarounds; AAISM treats it as complementary, not a substitute for behavior change.
* B generic modules fail to address the specific misuse pattern.
* D signatures provide attestations without ensuring comprehension or changed behavior.
References:* AI Security Management (AAISM) Body of Knowledge: Human-centric Controls-Role- based training, policy-to-practice mapping, and scenario exercises for rapid risk reduction.* AI Security Management Study Guide: Awareness program design for generative AI misuse; behavior-anchored training outcomes.
NEW QUESTION # 298
When generative AI output data is developed by a third party, which of the following MUST be in place to protect against code-level vulnerabilities?
Answer: D
Explanation:
Robust third-party contracts establish security requirements, responsibilities, and accountability for addressing code-level vulnerabilities, ensuring the vendor implements appropriate controls and remediation processes.
NEW QUESTION # 299
Secure aggregation enhances federated learning security by:
Answer: A
Explanation:
AAISM explains that secure aggregation ensures the server only sees aggregated model updates--not individual client contributions--so privacy is preserved even if the server is breached.
NEW QUESTION # 300
A health services organization is developing a proprietary generative AI chatbot to assist patients with medical devices. Which of the following should be the organization's HIGHEST priority?
Answer: D
Explanation:
AAISM prioritizes training data suitability--lawful sourcing, provenance, quality, representativeness, and safety--especially in health-related applications. The correctness and appropriateness of training data determine clinical safety, reduction of harmful outputs, and compliance with data protection/sector obligations. Larger models or more data do not compensate for inappropriate or low-quality datasets; tuning is secondary to ensuring the right data with rigorous curation, labeling quality, and guardrails aligned to patient safety requirements.
NEW QUESTION # 301
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