Free AAISM Exam Braindumps
ISACA Advanced in AI Security Management Questions 81–85 (page: 18)

Updated On: 13-Sep-2026

A PRIMARY objective of responsibly providing AI services is to:

  1. ensure the confidentiality and integrity of data processed by AI models.
  2. build trust for decisions and predictions made by AI models.
  3. enable AI models to operate autonomously.
  4. improve the ability of AI models to learn from new data.

Answer(s): B

Explanation:

Responsible AI focuses on transparency, fairness, accountability, and ethical practices. Building trust in AI outputs ensures that stakeholders can rely on the decisions and predictions made by AI systems, fostering adoption while mitigating ethical, legal, and reputational risks.



When integrating AI for innovation, which of the following can BEST help an organization manage security risk?

  1. Evaluating compliance requirements
  2. Re-evaluating the risk appetite
  3. Adopting a phased approach
  4. Seeking third-party advice

Answer(s): C

Explanation:

Implementing AI in stages allows the organization to test, monitor, and validate security measures incrementally. A phased approach helps identify vulnerabilities early, apply corrective actions, and ensure that AI-driven innovations do not introduce unacceptable security risks.



A model producing contradictory outputs based on highly similar inputs MOST likely indicates the presence of:

  1. evasion attacks.
  2. poisoning attacks.
  3. membership inference.
  4. model exfiltration.

Answer(s): A

Explanation:

Evasion attacks involve crafting inputs that are designed to exploit weaknesses in a model, causing it to produce inconsistent or incorrect outputs even for inputs that are highly similar. This behavior indicates that the model is vulnerable to manipulation that bypasses its intended logic or defenses.



An attacker crafts inputs to a large language model (LLM) to exploit output integrity controls.
Which of the following types of attacks is this an example of?

  1. Evasion
  2. Jailbreaking
  3. Remote code execution
  4. Prompt injection

Answer(s): D

Explanation:

Prompt injection attacks involve manipulating the input provided to an LLM to override or bypass its intended behavior and output controls. By crafting malicious prompts, attackers can influence the model to produce unauthorized or harmful outputs.



Which of the following MOST effectively minimizes the attack surface when securing AI agent components during their development and deployment?

  1. Schedule periodic manual code reviews.
  2. Implement compartmentalization with least privilege enforcement.
  3. Consolidate event logs for correlation and centralized analysis.
  4. Deploy pre-trained models directly into production.

Answer(s): B

Explanation:

Compartmentalization isolates AI agent components, and enforcing least privilege ensures each component has only the access necessary to perform its function. This approach minimizes the attack surface by limiting potential points of exploitation and reducing the impact of any successful attack.



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