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ISACA AAISM Prüfungsplan:

Thema	Einzelheiten
Thema 1	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.
Thema 2	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.
Thema 3	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.

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ISACA AAISM Online Prüfung & AAISM Probesfragen

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ISACA Advanced in AI Security Management (AAISM) Exam AAISM Prüfungsfragen mit Lösungen (Q251-Q256):

251. Frage
A global financial organization wants to deploy an AI solution for credit scoring. Which of the following should the organization do FIRST?

A. Perform bias assessments based on cultural differences and demographic landscapes.
B. Maintain thorough documentation of the validation process, data used, and results.
C. Create a test, evaluation, verification and validation (TEVV) strategy for AI solutions.
D. Verify that the AI solution meets compliance requirements for local laws and regulations.

Antwort: D

Begründung:
Ensuring the solution complies with applicable laws and regulations is the foundational step before any deployment activities. Regulatory compliance defines permissible data use, model behavior, and governance requirements, which must be established before conducting assessments, testing strategies, or documentation.

252. Frage
A healthcare provider uses an AI system to support patient diagnoses. Physicians note recommendations are often accurate but limit their ability to justify treatment decisions to patients and regulators. Management argues that improved outcomes outweigh transparency concerns.
Which of the following is BEST for the information security manager to recommend?

A. Implement explainable AI techniques and document model decision logic.
B. Discontinue the AI system immediately because lack of transparency makes it inherently unsafe.
C. Continue using the system and focus on accuracy improvement.
D. Retain the system but disclose to patients that AI is used in decision-making.

Antwort: A

Begründung:
Implementing explainable AI techniques and documenting model decision logic addresses the core concern of transparency while allowing the organization to continue benefiting from the AI system's diagnostic accuracy. This supports accountability, regulatory compliance, and informed communication with patients and regulators.

253. Frage
An organization uses an AI tool to scan social media for product reviews. Fraudulent social media accounts begin posting negative reviews attacking the organization's product. Which type of AI attack is MOST likely to have occurred?

A. Data poisoning
B. Availability attack
C. Deepfake
D. Model inversion

Antwort: B

Begründung:
The AAISM materials classify availability attacks as attempts to disrupt or degrade the functioning of an AI system so that its outputs become unreliable or unusable. In this scenario, the fraudulent social media accounts are deliberately overwhelming the AI tool with misleading negative reviews, undermining its ability to deliver accurate sentiment analysis. This aligns directly with the concept of an availability attack. Model inversion relates to reconstructing training data from outputs, deepfakes involve synthetic content generation, and data poisoning corrupts the training set rather than manipulating inputs at runtime. Therefore, the fraudulent review campaign is most accurately identified as an availability attack.
References:
AAISM Study Guide - AI Risk Management (Adversarial Threats and Availability Risks) ISACA AI Security Management - Attack Classifications

254. Frage
An organization implementing an LLM application sees unexpected cost increases due to excessive computational resource usage. Which vulnerability is MOST likely in need of mitigation?

A. Sensitive information disclosure
B. Excessive agency
C. Unbounded consumption
D. System prompt leakage

Antwort: C

Begründung:
AAISM categorizes unbounded consumption (also known as "resource exhaustion" or "infinite queries") as an AI-specific vulnerability where attackers (or faulty prompts) trigger excessive computation, leading to high costs and degraded service.
This aligns precisely with unexpected large compute bills.
Excessive agency (A) refers to unsafe autonomy, while disclosure (B) and prompt leakage (D) do not relate to compute overuse.
References: AAISM Study Guide - AI Abuse and Unbounded Consumption Risk.

255. Frage
Which of the following AI controls would BEST protect against deepfake content?

A. AI model testing
B. Data ownership
C. AI prompt validation
D. Data provenance

Antwort: D

Begründung:
Data provenance establishes the origin and authenticity of content, enabling verification of whether media has been altered or fabricated, which is essential for detecting and protecting against deepfakes.

256. Frage
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