Free AAISM Exam Braindumps
ISACA Advanced in AI Security Management Questions 176–180 (page: 37)

Updated On: 13-Sep-2026

An organization decides to use an anomaly-based intrusion detection system (IDS) integrated with a generative adversarial network enabled AI tool. The integrated tool would MOST effectively detect intrusions by leveraging:

  1. validation data sets to enable highly realistic AI decisions.
  2. classified real intrusion data based on labeled data.
  3. automated rule creation to increase model performance.
  4. synthetic intrusion data to train the tool's components.

Answer(s): D

Explanation:

Generative adversarial networks can create realistic synthetic intrusion data, which enhances training coverage for rare or novel attack patterns and significantly improves the effectiveness of anomaly-based intrusion detection.



A financial organization is concerned about the risk of prompt injection attacks on its customer service chatbot.
Which of the following controls BEST addresses this concern?

  1. Human-in-the-loop
  2. Input validation
  3. Increasing model parameters
  4. Continuous monitoring

Answer(s): B

Explanation:

Input validation directly addresses prompt injection risk by constraining, sanitizing, and filtering user inputs, preventing malicious prompts from manipulating the chatbot’s behavior or accessing unauthorized information.



Which of the following is the MOST important consideration when an organization is adopting generative AI for personalized advertising?

  1. Fraud risk
  2. Reputational risk
  3. Commercial risk
  4. Regulatory risk

Answer(s): B

Explanation:

Reputational risk is the most important consideration because generative AI used for personalized advertising can produce inappropriate, biased, or intrusive content, which can quickly damage customer trust and brand reputation if perceived as unethical or manipulative.



Which of the following is MOST important for effective AI risk management?

  1. Utilization of best practice AI risk management frameworks
  2. Internal stakeholder participation in AI risk management processes
  3. Risk measurement during an early stage of the AI system life cycle
  4. Creation of separate risk management processes for AI-specific risk

Answer(s): B

Explanation:

Internal stakeholder participation is most important because effective AI risk management depends on cross-functional involvement to identify, assess, and manage risks across technical, business, legal, ethical, and security domains throughout the AI life cycle.



An organization is looking to purchase an AI application from a vendor but is concerned about the security of its data.
Which of the following is the MOST effective way to address this concern?

  1. Mandate an AI security audit by an external auditor before procurement.
  2. Initiate discussions between the organization's and the vendor's legal teams.
  3. Ensure vendors disclose how the application uses the organization's data.
  4. Assess the vendor's publicly available AI usage policy.

Answer(s): C

Explanation:

Ensuring vendors disclose how the application uses the organization’s data directly addresses data security concerns by providing transparency into data handling, processing, storage, and reuse practices, which is essential for assessing confidentiality, privacy, and misuse risk before procurement.



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