Training AAISM Pdf - Certification AAISM Test Answers

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ISACA AAISM Exam Overview:

Certification Vendor:ISACA
Exam Name:Advanced in AI Security Management (AAISM) Exam
Exam Number:AAISM
Certificate Validity Period:3 years (continuing professional education required for renewal)
Available Languages:English, Spanish
Exam Format:Multiple-choice questions
Related Certifications:CISSP
CISM
Real Exam Qty:90
Exam Duration:150 minutes
Passing Score:450/800
Exam Price:USD 459 (member) / USD 599 (non-member)
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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AAISM Practice Test: ISACA Advanced in AI Security Management (AAISM) Exam & AAISM Exam Braindumps

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ISACA AAISM Exam Syllabus Topics:

TopicDetails
Topic 1
  • 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 2
  • 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.
Topic 3
  • 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.

ISACA Advanced in AI Security Management (AAISM) Exam Sample Questions (Q356-Q361):

NEW QUESTION # 356
Which strategy BEST ensures generative AI tools do not expose company data?

Answer: D

Explanation:
AAISM identifies the strongest immediate control for preventing data leakage into generative AI systems as technically restricting or blocking user entry of sensitive data.
Audits (A) are retrospective. Testing tools (C) does not prevent user error. Regulatory compliance (D) does not stop operational leakage.
References: AAISM Study Guide - Data Leakage Prevention and Input Restriction Controls.


NEW QUESTION # 357
When addressing privacy concerns related to AI, what is the GREATEST significance of user consent?

Answer: A

Explanation:
AAISM clarifies that the primary regulatory purpose of user consent is to provide lawful authorization for processing personal data, including use in AI models.
Consent does not directly prevent unauthorized access (A). Deletion rights (B) relate to data subject rights but are not the purpose of consent. Bias detection (D) is unrelated.
References: AAISM Study Guide - AI Privacy and Legal Basis for Processing Data.


NEW QUESTION # 358
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: C

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.
References:
AAISM Exam Content Outline - AI Technologies and Controls (Prompt Security and Input Manipulation) AI Security Management Study Guide - Threats to Output Integrity


NEW QUESTION # 359
Which of the following MOST effectively secures ongoing stakeholder support for AI initiatives?

Answer: D

Explanation:
AAISM governance guidance emphasizes that stakeholder buy-in is sustained when the measurable value of AI initiatives is clearly communicated. Value demonstrations include:
- improved efficiency
- reduced cost
- reduced risk
- business growth


NEW QUESTION # 360
Which of the following recommendations would BEST help a service provider mitigate the risk of lawsuits arising from generative AI's access to and use of internet data?

Answer: C

Explanation:
The AAISM materials highlight that one of the primary legal risks with generative AI systems is the unauthorized use of copyrighted or intellectual property-protected data drawn from internet sources. To mitigate lawsuits, the most effective recommendation is to implement filtering logic that actively excludes data flagged for intellectual property risks before ingestion or generation. While disclosing compliance policies, appointing governance roles, or reviewing logs are supportive measures, they do not directly prevent the core liability of using restricted content. The study guide explicitly emphasizes that proactive filtering and data governance controls are the most effective safeguards against legal disputes concerning content origin.
References:
AAISM Exam Content Outline - AI Risk Management (Legal and Intellectual Property Risks) AI Security Management Study Guide - Generative AI Data Governance


NEW QUESTION # 361
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