Isaca AAISM Dumps
| Exam Code | AAISM |
| Exam Name | ISACA Advanced in AI Security Management (AAISM) Exam |
| Update Date | 29 Aug, 2026 |
| Total Questions | 255 Questions Answers With Explanation |
| Exam Code | AAISM |
| Exam Name | ISACA Advanced in AI Security Management (AAISM) Exam |
| Update Date | 29 Aug, 2026 |
| Total Questions | 255 Questions Answers With Explanation |
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When evaluating a third-party AI service provider, which master services agreement (MSA) provision is MOST critical for managing security risk?
A. Guaranteeing unlimited model retraining requests
B. Sharing real-time log information
C. Prohibiting the use of customer data for model training
D. Restricting query volume thresholds
A security assessment revealed that attackers could access sensitive company data through chat interface injection. What is the BEST mitigation?
A. Conducting regular security audits
B. Manually reviewing AI model outputs
C. Implementing input validation and templates
D. Ensuring continuous monitoring and tagging
Which of the following would MOST effectively obtain ongoing support from stakeholders to align AI initiatives with business objectives?
A. Conducting periodic organization-wide AI staff training
B. Addressing and optimizing AI-related risk
C. Developing and monitoring the AI strategic roadmap
D. Quantifying and communicating the value of AI solutions
Which of the following AI data management techniques involves creating validation and test data?
A. Training
B. Annotating
C. Splitting
D. Learning
Which of the following is the MOST critical success factor for an AI implementation project?
A. Developing and using model cards
B. Ensuring AI risk is captured in the risk register
C. Mapping data throughout the life cycle
D. Obtaining senior management buy-in
Which of the following BEST ensures AI components are validated during disaster recovery testing?
A. Running simulated data-loss scenarios by deleting test feature-store records
B. Disconnecting model training clusters to test retraining workflows
C. Simulating DoS attacks on AI APIs
D. Monitoring model performance during failover and recovery
AI developers often find it difficult to explain the processes inside deep learning systems PRIMARILY because:
A. Training data input for learning is spread throughout the public domain and continues to
change
B. Generated knowledge dynamically changes in memory without being tracked by change history logs
C. Applied algorithms are based on probability theories to improve system performance
D. Neural network architectures can include statistical methods that are not fully understood
A preliminary risk assessment of a SaaS-based large language model (LLM) business support system has identified prompt injection, data poisoning, and model exfiltration as material threats. Which of the following is the BEST approach to ensure risks are treated consistently?
A. Implementing an AI threat control matrix that maps threats to specific controls and
assurance activities
B. Applying control baselines from a recognized industry standard to AI components
C. Relying on vendor independent audit reports and service level agreements (SLAs) as evidence of AI risk coverage
D. Focusing resources on post-deployment red teaming and deferring control selection until post go-live feedback is received
A vendor switched its chatbot’s AI model without due diligence, causing unethical investment advice. What control BEST prevents this scenario?
A. Master services agreement
B. Change management
C. Shared responsibility model
D. Data minimization
Which of the following is MOST important to ensure security throughout the AI data life cycle?
A. Leveraging selected open-source models
B. Conducting periodic data reviews
C. Restricting use of data in third-party models
D. Maintaining a complete inventory with data lineage records
A critical AI system shows biased outcomes. What is the BEST course of action?
A. Activate the kill switch
B. Conduct audits of data and model
C. Perform root cause analysis to identify mitigation
D. Retrain the model with a new diverse dataset
What is the GREATEST concern when a vendor enables generative AI features for an organization’s critical system?
A. Security monitoring and alerting
B. Bias and ethical practices
C. Proposed regulatory enhancements
D. Access to the model
Which of the following should be the PRIMARY objective of implementing differential privacy techniques in AI models used for fraud detection systems?
A. Reducing computational resources
B. Enhancing the accuracy of predictions
C. Protecting individual data contributions while allowing statistical analysis
D. Increasing model training speed
Which of the following involves documenting and monitoring the complete journey of data as it flows through an AI system?
A. Lineage
B. Transformation
C. Origin
D. Processing
Within an incident handling process, which of the following would BEST help restore enduser trust in an AI system?
A. Remediation of the AI system based on lessons learned
B. The AI model’s outputs are validated by team members
C. AI is used to monitor incident detection and alerts
D. The AI model prioritizes incidents based on business impact
Which of the following datasets is used to tune hyperparameters?
A. Validation
B. Test
C. Configuration
D. Training
A financial organization relies on AI-based identity verification and fraud detection services. Which of the following BEST integrates AI security risk into the business continuity plan (BCP)?
A. Using explainable AI to document decision paths
B. Periodic retraining using pre-labeled data
C. Including AI model supporting infrastructure in disaster recovery scenarios
D. Duplicating AI microservices across multiple availability zones
Which of the following BEST enables an organization to strengthen information security controls around the use of generative AI applications?
A. Ensuring controls exceed industry benchmarks
B. Monitoring AI outputs against policy
C. Validating AI model training data
D. Implementing a kill switch
Implementing which of the following would MOST effectively address bias in generative AI models?
A. Data augmentation
B. Data minimization
C. Adversarial training
D. Fairness constraints
Which of the following BEST describes an adversarial attack on an AI model?
A. Attacking underlying hardware
B. Providing inputs that mislead the model into incorrect predictions
C. Reverse-engineering the model using social engineering
D. Conducting denial-of-service attacks on AI APIs
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