ISACA Advanced in AI Security Management AAISM Dumps in PDF

Free ISACA AAISM Real Questions (page: 32)

An organization develops and implements an AI-based plug-in for users that summarizes their individual emails.
Which of the following is the GREATEST risk associated with this application?

  1. Insufficient rate limiting for APIs
  2. Data format incompatibility
  3. Lack of application vulnerability scanning
  4. Inadequate controls over parameters

Answer(s): D

Explanation:

An AI-based email summarization plug-in processes sensitive personal and business information. If parameters controlling data access, processing scope, or output are insufficiently restricted, the application could expose confidential content, mishandle sensitive information, or generate inaccurate summaries, posing the greatest risk.



Which of the following is the GREATEST benefit of implementing an AI tool to safeguard sensitive data and prevent unauthorized access?

  1. Timely initiation of incident response
  2. Reduced number of false positives
  3. Timely analysis of endpoint activities
  4. Reduced need for data classification

Answer(s): A

Explanation:

AI tools that monitor sensitive data and access patterns can quickly detect anomalies or potential breaches. Early detection enables prompt initiation of incident response, minimizing the impact of unauthorized access and improving overall data security posture.



Which of the following would BEST help mitigate vulnerabilities associated with hidden triggers in generative AI
models?

  1. Monitoring model outputs and suspicious patterns to detect trigger activations
  2. Regularly retraining the model using a diverse data set
  3. Applying differential privacy and masking sensitive patterns in the training data
  4. Incorporating adversarial training to expose and neutralize potential triggers

Answer(s): D

Explanation:

Adversarial training involves deliberately introducing challenging or malicious inputs during model development to identify hidden triggers. By exposing these vulnerabilities, the AI model can be adjusted or fortified, reducing the risk of malicious activation of undesired behaviors.



Which of the following is the MOST important course of action prior to placing an in-house developed AI solution into production?

  1. Deploy a prototype of the solution.
  2. Perform a privacy, security, and compliance gap analysis.
  3. Obtain senior management sign-off.
  4. Perform testing, evaluation, validation, and verification.

Answer(s): D

Explanation:

Before deploying an AI solution into production, it is critical to thoroughly test and validate its performance, accuracy, and reliability. Verification ensures the system meets design specifications, while validation confirms it fulfills intended use cases. This step mitigates operational, ethical, and regulatory risks.



Which of the following is a key risk indicator (KRI) for an AI system used for threat detection?

  1. Number of training epochs
  2. Number of layers in the neural network
  3. Training time of the model
  4. Number of system overrides by cyber analysts

Answer(s): D

Explanation:

Frequent overrides indicate that the AI system’s threat detection outputs are often incorrect or require human correction. Monitoring this KRI helps assess the system’s reliability, effectiveness, and risk exposure, guiding improvements and governance decisions.



The PRIMARY benefit of implementing moderation controls in generative AI applications is that it can:

  1. filter out harmful or inappropriate content.
  2. increase the model's ability to generate diverse and creative content.
  3. ensure the generated content adheres to privacy regulations.
  4. optimize the model's response time.

Answer(s): A

Explanation:

Moderation controls act as a safeguard to detect and block outputs that are offensive, unsafe, or otherwise inappropriate. This reduces ethical, legal, and reputational risks associated with generative AI applications while maintaining user trust.



Which of the following should be a PRIMARY consideration when defining recovery point objectives (RPOs) and recovery time objectives (RTOs) for generative AI solutions?

  1. Prioritizing computational efficiency over data integrity to minimize downtime
  2. Maintaining consistent hardware configurations to prevent discrepancies during model restoration
  3. Preserving the most recent versions of data models to avoid inaccuracies in functionality
  4. Ensuring the backup system can restore training data sets within the defined RTO window

Answer(s): C

Explanation:

For generative AI solutions, the latest model versions capture critical learned patterns and performance improvements. Preserving these ensures that, after a disruption, the AI system can resume accurate and reliable functionality, aligning recovery objectives with operational and business requirements.



Which of the following is the MOST effective use of AI in incident response?

  1. Streamlining incident response testing
  2. Automating incident response triage
  3. Ensuring chain of custody
  4. Improving incident response playbook

Answer(s): B

Explanation:

AI can rapidly analyze alerts, prioritize incidents, and categorize threats, enabling faster and more efficient triage. This reduces human workload, accelerates response times, and ensures that critical incidents receive immediate attention, enhancing the overall effectiveness of incident response.



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