AAISM Exam Cram Questions | AAISM Guide

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ISACA AAISM Exam Syllabus Topics:

Section	Weight	Objectives
AI Technologies and Controls	38%	- Data management and protection controls for AI - Security monitoring, testing, and continuous assurance for AI systems - Privacy, ethics, trust, and safety controls - AI security architecture and secure design principles - AI lifecycle security: model selection, training, validation, and deployment
AI Risk Management	31%	- AI vendor and supply chain risk management - AI risk assessment, thresholds, and treatment strategies - AI threat and vulnerability management - Regulatory compliance and ethical considerations in AI
AI Governance and Program Management	31%	- AI asset and data lifecycle management - AI governance frameworks and alignment with business objectives - AI security program development and management - AI security policies, standards, and procedures - Business continuity and incident response for AI systems

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100% Pass Quiz 2026 AAISM: High Hit-Rate ISACA Advanced in AI Security Management (AAISM) Exam Exam Cram Questions

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q296-Q301):

NEW QUESTION # 296
Which of the following is the MOST effective defense against cyberattacks that alter input data to avoid detection by the model?

A. Conducting periodic monitoring activities on the model's decisions
B. Enhancing model robustness through adversarial training
C. Applying differential privacy controls on training datasets
D. Implementing restricted access to the model's internal parameters

Answer: B

Explanation:
Evasion attacks manipulate inputs to induce misclassification while leaving the model unchanged.
AAISM prescribes adversarial robustness controls, with adversarial training as a primary measure:
incorporate adversarially perturbed examples into training/validation to harden decision boundaries and improve resilience across threat models (e.g., Lp-bounded perturbations).

NEW QUESTION # 297
A critical AI system shows biased outcomes. What is the BEST course of action?

A. Activate the kill switch
B. Perform root cause analysis to identify mitigation
C. Retrain the model with a new diverse dataset
D. Conduct audits of data and model

Answer: B

Explanation:
AAISM emphasizes root cause analysis as the primary step when AI behavior deviates unexpectedly.
RCA determines whether issues stem from:
- data drift
- model drift
- poisoned data
- missing features
- logic errors
- configuration changes

NEW QUESTION # 298
Which of the following is the MOST effective way to prevent a model inversion attack?

A. Monitor model output for anomalies
B. Ensure data minimization
C. Implement differential privacy during model training
D. Utilize data pseudonymization

Answer: C

Explanation:
AAISM identifies differential privacy as the primary mitigation technique against model inversion attacks, which attempt to reconstruct sensitive training data by probing model outputs.

NEW QUESTION # 299
An organization is implementing AI agent development across multiple engineering teams. Which of the following is the MOST important focus of AI-specific security training for developers?

A. Prompt injection, agent memory control, and insecure tool execution
B. Output moderation, hallucination handling, and policy alignment
C. Dataset bias, explainability, and fairness in model decisions
D. API abuse, data leakage, and third-party plug-in risk

Answer: A

Explanation:
For developer-facing, near-term hardening of AI agents, AAISM prioritizes secure agent design and runtime controls against prompt injection, unsafe memory/tool use, and tool-execution compromise. These are primary exploitation paths for agents that read external content, persist memory, and call tools with elevated privileges. Training must center on: guarding tool invocation, constraining memory scope, sanitizing/validating inputs, and isolating high-risk actions.

NEW QUESTION # 300
An organization engages its end users to be involved in the AI life cycle to validate security controls. Which of the following MOST effectively supports decision-making regarding ethical and safety controls?

A. Engaging independent expert assistance
B. Providing context and understanding potential risk
C. Defining and documenting technical controls
D. Updating the software development life cycle methodology

Answer: B

Explanation:
Providing context and understanding potential risk enables end users to make informed judgments about how AI systems may impact safety and ethics in real-world scenarios, directly supporting effective decision-making for appropriate controls.

NEW QUESTION # 301
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