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| Section | Weight | Objectives |
|---|---|---|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI-driven threats and risks
|
| Securing AI Systems | 40% | - Defending against AI-specific attacks
|
| AI-assisted Security | 24% | - Security automation and orchestration
|
| AI Governance, Risk and Compliance | 19% | - Risk management for AI
|
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NEW QUESTION # 36
Which of the following attacks would be the best to automate with AI during dynamic application software testing (DAST)?
Answer: A
Explanation:
Basic Concept: Dynamic Application Security Testing (DAST) tests running applications by sending various inputs to discover vulnerabilities. AI can significantly enhance DAST by intelligently generating diverse, targeted test payloads that traditional tools might miss. CompTIA SecAI+ covers AI augmentation of security testing methodologies.
Why C is Correct: Payload creation is highly suitable for AI automation during DAST. AI can generate diverse, contextually appropriate attack payloads such as SQL injection strings, XSS vectors, command injection attempts, and format string exploits tailored to the specific application ' s behavior observed during testing. AI can learn from the application ' s responses to previous payloads and generate increasingly targeted inputs, discovering vulnerabilities more efficiently than static payload databases.
Why A is Wrong: DDoS attacks are volume-based attacks designed to overwhelm network or application infrastructure. Automating DDoS during DAST is inappropriate as it would disrupt service availability rather than discover application security vulnerabilities, and it is harmful to legitimate operations.
Why B is Wrong: Data poisoning is an attack targeting AI/ML model training data integrity. It is relevant to securing AI systems but is not a DAST technique for testing web or software application security vulnerabilities during dynamic testing.
Why D is Wrong: Threat modeling is a structured analysis process performed before development or testing to identify potential threats and design appropriate countermeasures. It is a planning activity, not an attack technique that can be automated during dynamic application security testing.
NEW QUESTION # 37
A company launches an AI application to monitor cloud misconfiguration and compliance. The AI application is shutting down development servers and opening ports during a client demonstration. Which of the following actions should the company take to return to normal operations and prevent future issues?
Answer: B
Explanation:
Option D is correct because the AI application is taking high-impact remediation actions without adequate human authorization. Human-in-the-loop control requires a qualified person to review and approve consequential actions, such as stopping servers or changing firewall exposure, before execution. The system may still detect misconfigurations, rank risks, and recommend fixes, but it should not autonomously disrupt development or alter network access during a demonstration. Option A restores service temporarily but leaves the unsafe decision path unchanged. Option B removes useful monitoring and does not correct the excessive automation. Option C might close improperly opened ports, yet it addresses only one symptom and does not prevent the AI from repeating other damaging actions. The stronger design is to roll back the unauthorized changes, restrict the agent's permissions, require approval for disruptive operations, and maintain an auditable record of recommendations and approvals. The NIST AI Risk Management Framework calls for appropriate human-oversight processes to be defined, assessed, and documented, supporting this governance pattern.
NEW QUESTION # 38
SIMULATION
Instructions
Click the (+) to assign each threat category into its appropriate framework.
If at any time you would like to bring back the initial state of the simulation, please click the Reset All button.
An architect is modeling an agentic system to meet security standards.
Answer:
Explanation:
Explanation:
MAESTRO: Overreliance, Insecure plug-in design
OWASP Top 10: Broken access control, Identification and authentication failures OWASP Top 10 LLM: Prompt injection, Model denial of service STRIDE: Elevation of privilege, Repudiation, Supply chain vulnerabilities, Insecure design MAESTRO addresses AI-specific misuse such as excessive trust in outputs (overreliance) and unsafe plug-in design.
OWASP Top 10 maps to classic web threats: broken access control and authentication failures are key risks.
OWASP Top 10 LLM focuses on LLM-related threats like prompt injection and denial of service targeting the model.
STRIDE categories cover privilege escalation, repudiation (denying actions), supply chain risks, and insecure design flaws.
NEW QUESTION # 39
Which of the following International Organization for Standardization (ISO) standards should be selected for certification to use for third-party assurance for responsible AI practices?
Answer: A
Explanation:
Basic Concept: ISO develops international standards for management systems across various domains. For organizations seeking third-party certification demonstrating commitment to responsible AI governance practices, the appropriate ISO standard must specifically address AI management systems. CompTIA SecAI+ Exam Objectives cover ISO standards relevant to AI governance under Domain 4.
Why D is Correct: ISO 42001 is the International Standard for Artificial Intelligence Management Systems (AIMS). It provides a framework for establishing, implementing, maintaining, and continually improving an AI management system within organizations. ISO 42001 certification provides third-party assurance specifically for responsible AI practices including risk management, transparency, human oversight, and ethical AI governance - directly answering the question.
Why A is Wrong: ISO 20000 is the standard for IT Service Management (ITSM). It provides requirements for establishing and maintaining a service management system for IT services. It does not address AI governance or responsible AI practices.
Why B is Wrong: ISO 27001 is the standard for Information Security Management Systems (ISMS). It addresses general information security risk management, not AI-specific governance or responsible AI practices such as fairness, transparency, and AI lifecycle management.
Why C is Wrong: ISO 27701 extends ISO 27001 to address Privacy Information Management (PIMS), covering personal data protection requirements aligned with GDPR. While relevant to data privacy in AI systems, it does not specifically certify responsible AI governance practices.
NEW QUESTION # 40
A developer is proposing a new AI application for human resources systems. Which of the following are the most important considerations?
Answer: B
Explanation:
Option B is correct because a human resources AI application processes highly sensitive employee and applicant information and may influence consequential employment decisions. Privacy and security therefore determine whether the system can be deployed responsibly. The design must address data minimization, lawful collection, access control, encryption, retention, auditability, secure model integration, and protection against unauthorized disclosure. It should also evaluate whether training data or outputs expose protected or confidential information and whether human review is required before decisions affect candidates or employees. Option A concerns friendliness and presentation, not the protection of people or organizational data. Option C may improve usability, but visual design cannot compensate for insecure handling of resumes, performance records, or identity data. Option D can make outputs easier to consume, yet brevity and summarization do not control privacy risk or system compromise. The NIST AI Risk Management Framework identifies privacy enhancement, security, resilience, accountability, and transparency as characteristics of trustworthy AI, making privacy and security the controlling considerations in this scenario.
NEW QUESTION # 41
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