[Q85-Q105] Try AAISM Free Now! Real Exam Question Answers Updated [Mar 17, 2026]

Posted On March 17, 2026

Try AAISM Free Now! Real Exam Question Answers Updated [Mar 17, 2026]

Get Ready to Pass the AAISM exam with ISACA Latest Practice Exam

ISACA AAISM Exam Syllabus Topics:

Topic	Details
Topic 1	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.
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 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.

NEW QUESTION 85
Personal data used to train AI systems can BEST be protected by:

Erasing personal data after training

Ensuring the quality of personal data

Anonymizing personal data

Hashing personal data

NEW QUESTION 86
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?

Monitoring AI systems for suspicious activities

Updating deployed training data with new adversarial data

Replacing the AI model with a new model that hides confidence levels

Implementing strict access controls to the model’s architecture

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 87
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?

Assess the vendor’s publicly available AI usage policy

Ensure vendors disclose how the application uses the organization’s data

Mandate an AI security audit by an external auditor before procurement

Initiate discussions between the organization’s and the vendor’s legal teams

NEW QUESTION 88
Which of the following would MOST effectively obtain ongoing support from stakeholders to align AI initiatives with business objectives?

Conducting periodic organization-wide AI staff training

Addressing and optimizing AI-related risk

Developing and monitoring the AI strategic roadmap

Quantifying and communicating the value of AI solutions

NEW QUESTION 89
An AI research team is developing a natural language processing model that relies on several open-source libraries. Which of the following is the team’s BEST course of action to ensure the integrity of the software packages used?

Maintain a list of frequently used libraries to ensure consistent application in projects

Scan the packages and libraries for malware prior to installation

Use the latest version of all libraries from public repositories

Retrain the model regularly to handle package and library updates

NEW QUESTION 90
A post-incident investigation finds that an AI-powered anti-money laundering system inadvertently allowed suspicious transactions because certain risk signals were disabled to reduce false positives. Which of the following governance failures does this BEST demonstrate?

Lack of sufficient computing resources for the AI system

Excessive reliance on external consultants for model design

Absence of metrics and dashboards for analysts

Insufficient model validation and change control processes

NEW QUESTION 91
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?

Implementing an AI threat control matrix that maps threats to specific controls and assurance activities

Applying control baselines from a recognized industry standard to AI components

Relying on vendor independent audit reports and service level agreements (SLAs) as evidence of AI risk coverage

Focusing resources on post-deployment red teaming and deferring control selection until post go-live feedback is received

NEW QUESTION 92
Secure aggregation enhances federated learning security by:

Encrypting individual model updates so only the server can access them

Applying differential privacy to training data

Ensuring client contributions remain confidential even if the server is compromised

Processing client updates in isolation

NEW QUESTION 93
Which of the following datasets is used to tune hyperparameters?

Validation

Test

Configuration

Training

NEW QUESTION 94
Which of the following BEST describes how supervised learning models help reduce false positives in cybersecurity threat detection?

They analyze patterns in data to group legitimate activity from actual threats

They use real-time feature engineering to automatically adjust decision boundaries

They learn from historical labeled data

They dynamically generate new labeled data sets

NEW QUESTION 95
A military contractor discovered that its large language model (LLM) is at high risk of being targeted by advanced persistent threat (APT) actors seeking to exploit the model to access confidential information.
Which of the following attacks is the HIGHEST priority to protect against?

Model inversion

Data poisoning

Unauthorized tuning

Model distillation

NEW QUESTION 96
Which of the following is the GREATEST benefit of performing AI security risk assessments?

Appropriate privacy risk controls are implemented for AI models

The appropriate level of funding is secured for AI security risk

The risk register is updated with the latest AI risk

Risk prioritization decisions are made for AI security

NEW QUESTION 97
When evaluating a new AI tool for intrusion prevention, which of the following is the MOST important consideration to ensure the tool fits within the existing program architecture?

Confirm tool capabilities align with the control objectives.

Select a tool that integrates with the existing SIEM.

Prioritize a tool that offers real-time anomaly detection.

Ensure automated response orchestration.

NEW QUESTION 98
Which of the following is the BEST way to ensure role clarity and staff effectiveness when implementing AI- assisted security monitoring tools?

Delay implementation until more data scientists are hired

Increase budgets for AI certifications

Update the security program to include cross-functional AI-specific responsibilities

Transition responsibilities to external consultants

NEW QUESTION 99
Which of the following is the GREATEST concern when a vendor enables generative AI features for an organization’s critical system?

Access to the model

Proposed regulatory enhancements

Security monitoring and alerting

Bias and ethical practices

NEW QUESTION 100
An organization has discovered that employees have started regularly utilizing open-source generative AI without formal guidance. Which of the following should be the CISO’s GREATEST concern?

Lack of monitoring

Policy violations

Data leakage

Model hallucinations

NEW QUESTION 101
A financial services firm received a regulatory fine after a vendor switched its chatbot’s AI model without due diligence, resulting in unethical investment advice to the firm’s clients. Which of the following controls should be implemented by the firm to BEST prevent recurrence of this scenario?

Master services agreement

Shared responsibility model

Data minimization

Change management

NEW QUESTION 102
A regulator warns of increased risk of AI re-identification attacks on anonymized datasets. What should the information security manager do FIRST?

Assume anonymization is permanent and continue operations

Immediately delete anonymized datasets and suspend AI services

Implement a monitoring program including privacy audits and adversarial testing

Establish strong access controls for services using anonymized data

NEW QUESTION 103
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:

synthetic intrusion data to train the tool’s components

validation data sets to enable highly realistic AI decisions

automated rule creation to increase model performance

classified real intrusion data based on labeled data

NEW QUESTION 104
Which of the following employee awareness topics would MOST likely be revised to account for AI-enabled cyber risk?

Clean desk policy

Social engineering

Malicious insider threats

Authentication controls

NEW QUESTION 105
An automotive manufacturer uses AI-enabled sensors on machinery to monitor variables such as vibration, temperature, and pressure. Which of the following BEST demonstrates how this approach contributes to operational resilience?

Scheduling repairs for critical equipment based on real-time condition monitoring

Performing regular maintenance based on manufacturer recommendations

Conducting monthly manual reviews of maintenance schedules

Automating equipment repairs without any human intervention