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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • AI Governance and Program Management: This section of the exam measures the abilities of AI Security Governance Professionals and focuses on advising stakeholders in implementing AI security through governance frameworks, policy creation, data lifecycle management, program development, and incident response protocols.
Topic 2
  • AI Risk Management: This section of the exam measures the skills of AI Risk Managers and covers assessing enterprise threats, vulnerabilities, and supply chain risk associated with AI adoption, including risk treatment plans and vendor oversight.
Topic 3
  • AI Technologies and Controls: This section of the exam measures the expertise of AI Security Architects and assesses knowledge in designing secure AI architecture and controls. It addresses privacy, ethical, and trust concerns, data management controls, monitoring mechanisms, and security control implementation tailored to AI systems.

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ISACA AAISM Exam Book | AAISM Test Dumps Pdf

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ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q357-Q362):

NEW QUESTION # 357
An organization uses a vendor's AI service to screen job applicants. The master service agreement includes a clause related to accountability models. Which of the following is the PRIMARY purpose of this clause in managing AI-specific risk?

Answer: B

Explanation:
Accountability clauses in AI service agreements are primarily intended to clearly define the responsibilities, obligations, and liabilities of each party involved in the use, operation, governance, and oversight of the AI system. This helps manage AI-specific risks related to compliance, security, ethics, and operational failures.


NEW QUESTION # 358
An attack has occurred on an AI system that has been in use for two years. Which of the following would BEST mitigate the impact of the attack?

Answer: C

Explanation:
When an AI system experiences an attack after being in production for an extended period, the most effective mitigation strategy is to update the deployed training data with new adversarial data. This process strengthens the model's resilience by retraining it to recognize and resist attack vectors that were previously unknown or unaccounted for. According to the AI Security Management (AAISM) framework, risk mitigation for AI systems must address model robustness through adversarial retraining, data quality improvement, and model lifecycle hardening rather than relying solely on reactive measures.
Why Option B is Correct:
* Incorporating adversarial examples into the training set enhances the system's ability to correctly classify and withstand malicious inputs.
* This approach directly mitigates the vulnerability exploited in the attack and supports a proactive, continuous risk management cycle.
Why Other Options Are Incorrect:
* Option A: Monitoring helps detect suspicious activity but does not resolve the underlying vulnerability.
* Option C: Concealing confidence scores may reduce model transparency but does not address the attack mechanism or its root cause.
* Option D: Implementing access controls protects the model's architecture but does not improve model robustness against input manipulation attacks.
Exact Extract from Official AAISM Study Guide:
"AI risk management requires continuous improvement following incidents. After an adversarial or data poisoning event, the preferred risk treatment involves retraining the model using adversarial data and updated datasets to enhance robustness. This ensures the AI model adapts to evolving threat landscapes rather than merely restricting access or obscuring outputs." References:
AI Security Management (AAISM) Body of Knowledge: AI Risk Treatment and Mitigation Strategies, Adversarial Robustness and Resilience Engineering.
AI Security Management Study Guide: Model Lifecycle Security, Continuous Risk Treatment through Adversarial Retraining.
ISO/IEC 23894:2023, Clause 8.3.2 - Risk treatment through robustness improvement and adversarial data inclusion.


NEW QUESTION # 359
During the deployment of a generative AI platform, a risk assessment highlighted threats such as data leakage and prompt manipulation. Which of the following is the BEST way to ensure appropriate control selection?

Answer: C

Explanation:
AAISM requires that control selection be threat-led and context-specific, aligning AI threats to the organization's existing enterprise control catalogs (security, privacy, resilience) and augmenting them with AI- specific safeguards where coverage is insufficient. This ensures consistency with the risk appetite, removes duplication, and closes AI-unique gaps (e.g., prompt injection, data leakage from context windows, model misuse). Generic reliance on vendors or uncustomized external frameworks does not ensure fit-for-purpose coverage, and deferring control selection to post-deployment contradicts proactive risk treatment.
References: AI Security Management™ (AAISM) Body of Knowledge - Governance & Program Controls; Control Selection and Tailoring; Threat-to-Control Mapping for AI Systems; Risk Appetite & Control Assurance Alignment.


NEW QUESTION # 360
A financial organization is deploying an AI-driven customer service platform that uses customer financial data and personalized responses. To ensure the platform remains compliant with data protection regulations, which of the following controls would be MOST important to implement?

Answer: C

Explanation:
Clear, granular, and revocable customer consent is essential for compliance with data protection regulations when processing personal financial data. It ensures customers understand and control how their information is used by the AI platform, supporting lawful processing, transparency, and user rights management.


NEW QUESTION # 361
Which BEST describes the role of model cards in AI solutions?

Answer: B

Explanation:
AAISM explains that model cards provide structured documentation about AI models, including:
- intended use cases
- training data characteristics
- ethical considerations
- known limitations
- risk factors
- performance benchmarks


NEW QUESTION # 362
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