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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | Advanced in AI Security Management (AAISM) Exam |
| Exam Number: | AAISM |
| Related Certifications: | CISSP CISM |
| Exam Price: | USD 459 (member) / USD 599 (non-member) |
| Passing Score: | 450/800 |
| Exam Format: | Multiple-choice questions |
| Real Exam Qty: | 90 |
| Exam Duration: | 150 minutes |
| Available Languages: | English, Spanish |
| Certificate Validity Period: | 3 years (continuing professional education required for renewal) |
| Recommended Training: | ISACA Official Training & Review Materials |
| Exam Registration: | ISACA AAISM Credentialing Page |
| Sample Questions: | ISACA AAISM Sample Questions |
| Exam Way: | Computer-based exam (online proctored or authorized test center) |
| Pre Condition: | Recommended: Active CISM or CISSP certification and experience in IT/security management or advisory roles |
| Official Syllabus URL: | https://www.isaca.org/credentialing/aaism |
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NEW QUESTION # 44
An organization concerned about the ethical and responsible use of a newly developed AI product should consider implementing:
Answer: D
Explanation:
The AAISM framework highlights that organizations adopting AI must ensure accountability structures are in place to govern ethical and responsible use. An accountability model assigns clear responsibility for decisions, outputs, and risks related to AI systems. While model cards provide transparency about a model's design and performance, they are primarily documentation tools. Vendor monitoring focuses on third-party oversight, not internal accountability. Security by design improves resilience but does not by itself address ethical use. The governance approach that most directly supports responsible and ethical AI deployment is an accountability model.
References:
AAISM Study Guide - AI Governance and Program Management (Ethical AI and Accountability) ISACA AI Security Management - Responsible AI Practices
NEW QUESTION # 45
Which of the following BEST ensures the integrity of data sets used to train AI models?
Answer: B
Explanation:
AAISM defines cryptographic tracking and verification as the best control for ensuring the integrity of training data. By applying hashing and verification methods, organizations can confirm that datasets remain unaltered and authentic throughout collection, storage, and processing. Collecting only necessary data, proper storage, or clear documentation all support governance and compliance, but they do not guarantee that the data has not been tampered with. Integrity is specifically ensured by cryptographic verification techniques.
References:
AAISM Exam Content Outline - AI Risk Management (Data Integrity and Protection) AI Security Management Study Guide - Cryptographic Controls for Dataset Integrity
NEW QUESTION # 46
Which of the following would BEST help mitigate vulnerabilities associated with hidden triggers in generative AI models?
Answer: A
Explanation:
Hidden triggers are adversarial backdoors planted in AI models, activated only by specific inputs. The AAISM materials specify that the best mitigation is to use adversarial training, which deliberately exposes the model to potential trigger inputs during training so it can learn to neutralize or resist them. Retraining with diverse data reduces bias but does not address hidden triggers. Differential privacy is focused on privacy preservation, not adversarial resilience. Monitoring outputs can help with detection but is reactive rather than preventative. The proactive solution highlighted in the study guide is adversarial training.
References:
AAISM Exam Content Outline - AI Risk Management (Backdoors and Hidden Triggers) AI Security Management Study Guide - Adversarial Training as a Mitigation Control
NEW QUESTION # 47
An attacker is able to exploit the intended behavior of an AI system using a specific input or classes of inputs. Which type of attack is this an example of?
Answer: A
Explanation:
An evasion attack occurs when an attacker crafts specific inputs designed to exploit the AI system during operation, causing the model to produce incorrect or unintended behavior while still functioning within its deployed environment.
NEW QUESTION # 48
A newly hired programmer suspects that the organization's AI solution is inferring users' sensitive information and using it to advise future decisions. Which of the following is the programmer's BEST course of action?
Answer: C
Explanation:
AAISM directs personnel to use established AI governance channels for suspected privacy, ethics, or compliance risks. The governance panel (risk, privacy, legal/compliance, security, product/data science) is chartered to triage, record, investigate, and direct remediation for potential inference of sensitive attributes and resulting decision impacts. Direct technical action (A or C) bypasses due process and accountability; escalating directly to a single executive (B) lacks the structured, cross-functional oversight required for regulated and ethical AI risk handling.
References:AI Security Management (AAISM) Body of Knowledge: AI Governance Operating Model; Roles & Responsibilities; Risk Intake and Triage for Privacy/Inference Risks.AAISM Study Guide: Ethics & Responsible AI Escalation Pathways; Governance Board Procedures; Documentation and Decision Records.
NEW QUESTION # 49
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