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ISACA AAISM Exam Overview:

Certification Vendor:	ISACA
Exam Name:	ISACA Advanced in AI Security Management (AAISM) Exam
Exam Number:	AAISM
Exam Duration:	150 minutes
Related Certifications:	CISSP CISM
Certificate Validity Period:	3 years
Available Languages:	English
Exam Format:	Scenario-based, Multiple-choice
Real Exam Qty:	90
Exam Price:	US$459 (members), US$599 (non-members)
Passing Score:	450 (out of 800)
Recommended Training:	ISACA Official AAISM Training
Exam Registration:	ISACA AAISM Registration
Sample Questions:	ISACA AAISM Sample Questions
Exam Way:	Computer-based; available at authorized PSI testing centers or via remote proctoring
Pre Condition:	Hold an active CISM or CISSP certification
Official Syllabus URL:	https://www.isaca.org/credentialing/aaism/aaism-exam-content-outline

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ISACA AAISM Prüfungsplan:

Thema	Einzelheiten
Thema 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.
Thema 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.
Thema 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.

ISACA Advanced in AI Security Management (AAISM) Exam AAISM Prüfungsfragen mit Lösungen (Q308-Q313):

308. Frage
Which of the following is the BEST control to mitigate injection attacks on an AI agent?

A. Implement input filtering to detect and block malicious or manipulated prompts.
B. Apply strict access controls and perform security testing on AI components.
C. Use sandboxing and least-privilege container configurations to isolate the AI runtime.
D. Deploy data loss prevention (DLP) tools and log monitoring to detect abnormal behaviors.

Antwort: A

Begründung:
Injection attacks against AI agents commonly rely on malicious or manipulated prompts designed to alter system behavior or bypass safeguards. Implementing input filtering directly addresses this threat by detecting and blocking harmful inputs before they are processed by the AI system.

309. Frage
When a retail organization uses an AI credit fraud detection system, which of the following BEST prevents false positives that may negatively affect customer satisfaction?

A. Increasing the model decision parameters
B. Optimizing for accuracy over precision
C. Fine tuning confidence score threshold
D. Employing cluster analysis algorithms

Antwort: C

Begründung:
Fine tuning confidence score thresholds helps balance fraud detection sensitivity with the reduction of false positives. Adjusting the threshold allows the organization to minimize incorrect fraud flags that could negatively impact legitimate customers and customer satisfaction.

310. Frage
When generative AI output data is developed by a third party, which of the following MUST be in place to protect against code-level vulnerabilities?

A. Robust third-party contracts
B. User provisioning
C. Model transparency
D. Rights management

Antwort: A

Begründung:
Robust third-party contracts establish security requirements, responsibilities, and accountability for addressing code-level vulnerabilities, ensuring the vendor implements appropriate controls and remediation processes.

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

A. Implement a monitoring program including privacy audits and adversarial testing
B. Assume anonymization is permanent and continue operations
C. Immediately delete anonymized datasets and suspend AI services
D. Establish strong access controls for services using anonymized data

Antwort: A

Begründung:
AAISM states that anonymization is not permanent and may be reversible through re-identification attacks.
The first action should be to evaluate and measure the actual privacy risk through:
* adversarial re-identification testing
* privacy audits
* monitoring for misuse
This provides the factual basis needed before making destructive or operational decisions.
Access control (D) is important but not the FIRST step. Deleting datasets (B) is premature. Assuming anonymization is permanent (A) violates AI privacy principles.
References: AAISM Study Guide - Privacy Risk, Re-Identification Threats, Adversarial Testing.

312. Frage
After implementing a third-party generative AI tool, an organization learns about new regulations related to how organizations use AI. Which of the following would be the BEST justification for the organization to decide not to comply?

A. The AI tool is widely used within the industry
B. The cost of noncompliance was not determined
C. The risk is within the organization's risk appetite
D. The AI tool is regularly audited

Antwort: C

Begründung:
The AAISM framework clarifies that compliance decisions must always be tied to an organization's risk appetite and tolerance. When new regulations emerge, management may choose not to comply if the associated risk remains within the documented and approved risk appetite, provided that accountability is established and governance structures support this decision. Other options such as widespread industry use, third-party audits, or lack of cost assessment do not justify noncompliance under the governance principles. The risk appetite framework is the only recognized justification under AI governance principles.

313. Frage
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