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| Certification Vendor: | ISACA |
|---|---|
| Exam Name: | Advanced in AI Security Management (AAISM) Exam |
| Exam Number: | AAISM |
| Related Certifications: | CISM CISSP |
| Exam Duration: | 150 minutes |
| Exam Price: | USD 459 (member) / USD 599 (non-member) |
| Certificate Validity Period: | 3 years (continuing professional education required for renewal) |
| Available Languages: | Spanish, English |
| Real Exam Qty: | 90 |
| Exam Format: | Multiple-choice questions |
| Passing Score: | 450/800 |
| 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 # 66
An organization is adopting an agentic AI solution from an external vendor to support internal IT operations.
Which of the following provides the MOST reliable and independently verifiable evidence of implemented security controls?
Answer: A
Explanation:
AAISM states that when evaluating external AI vendors, independently issued third-party audit reports (SOC, ISO, AI assurance assessments) provide the strongest evidence of implemented controls because they are objective, repeatable, and externally verified.
Peer reviews (A) lack formality, internal red-team reports (C) are non-independent, and whitepapers (D) are marketing documents without assurance value.
References: AAISM Study Guide - Third-Party AI Risk Management; Independent Assurance and Audit Requirements.
NEW QUESTION # 67
An AI system sponsored by an organization has expanded by connecting with an increased number of third-party systems. Which of the following would be an information security manager's BEST recommendation in this situation?
Answer: A
Explanation:
Expanding connections to third-party systems increases the attack surface and dependency risks.
Conducting due diligence ensures that each third party meets security, privacy, and compliance requirements before integration, directly addressing the most critical risk introduced by this expansion.
NEW QUESTION # 68
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?
Answer: B
Explanation:
According to the AAISM framework, prompt injection is the act of deliberately crafting malicious or manipulative inputs to override, bypass, or exploit the model's intended controls. In this case, the attacker is targeting the integrity of the model's outputs by exploiting weaknesses in how it interprets and processes prompts. Jailbreaking is a subtype of prompt injection specifically designed to override safety restrictions, while evasion attacks target classification boundaries in other ML contexts, and remote code execution refers to system-level exploitation outside of the AI inference context. The most accurate classification of this attack is prompt injection.
NEW QUESTION # 69
A health organization wants to use an AI tool for diagnostic decisions. Which of the following would BEST help the organization comply with privacy regulations?
Answer: D
Explanation:
Conducting a privacy impact assessment (PIA) is the best way to help ensure compliance with privacy regulations because it systematically identifies, evaluates, and mitigates privacy risks associated with the collection, processing, and use of sensitive health data within the AI diagnostic system.
NEW QUESTION # 70
An organization is deploying a large language model (LLM) and is concerned that input manipulations may compromise its integrity. Which of the following is the MOST effective way to determine an acceptable risk threshold?
Answer: C
Explanation:
AAISM requires that risk thresholds/tolerances be set by aligning threat likelihood and impact with the organization's business context and risk appetite. Determining "acceptable" risk starts with assessing business impact of credible threats (e.g., prompt injection leading to data exfiltration, policy evasion, or harmful actions), then translating this into control intensity and thresholds. Hard input restrictions (A) and static output caps (C) are blunt measures that may degrade utility without ensuring alignment to risk appetite.
Monitoring (B) is essential for detection, but it does not, by itself, define what level of risk is acceptable.
References: AI Security Management (AAISM) Body of Knowledge - Risk Appetite and Tolerance for AI; Threat Modeling for LLMs; Business Impact Analysis and Risk Acceptance Criteria.
NEW QUESTION # 71
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