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| Section | Weight | Objectives |
|---|---|---|
| AI-assisted Security | 24% | - Security automation and orchestration
|
| AI Governance, Risk and Compliance | 19% | - Compliance and legal requirements
|
| Securing AI Systems | 40% | - Defending against AI-specific attacks
|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI-driven threats and risks
|
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NEW QUESTION # 154
Which of the following roles best supports the implementation of AI governance, risk, and compliance (GRC)? (Choose two.)
Answer: E,F
Explanation:
Basic Concept: AI GRC implementation requires roles that combine understanding of AI technical capabilities and limitations with security risk assessment, control design, and compliance framework expertise. Identifying which roles naturally contribute to AI GRC is essential for team design. CompTIA SecAI+ Study Guide covers AI governance role responsibilities under Domain 4.
Why B is Correct: Data Scientists possess deep understanding of AI model capabilities, limitations, data requirements, and failure modes. For GRC implementation, their technical expertise is essential for identifying AI-specific risks such as bias, model drift, and data quality issues, assessing compliance implications of model design choices, and evaluating whether AI systems meet governance requirements.
Why D is Correct: Security Architects design comprehensive security frameworks and risk management strategies. For AI GRC, they translate governance requirements into technical controls, design AI security architectures that satisfy compliance obligations, assess the risk posture of AI deployments, and ensure security principles including least privilege, defense-in-depth, and audit logging are built into AI system designs.
Why A is Wrong: Desktop specialists manage user workstation hardware and software. Their role focuses on endpoint management and user support, not on the strategic risk assessment, compliance evaluation, or technical AI governance activities required for AI GRC implementation.
Why C is Wrong: Software developers write application code. While they implement security controls when directed, they typically lack the broad risk management, compliance framework expertise, and security architecture perspective needed to lead AI GRC implementation.
Why E is Wrong: SOC analysts focus on monitoring, detecting, and responding to security incidents in operational environments. Their expertise is in reactive security operations rather than the proactive governance framework design and compliance management that AI GRC requires.
Why F is Wrong: Network engineers design and maintain network infrastructure. Their expertise is in network connectivity and protocols, not in AI system governance, risk assessment frameworks, or compliance requirements.
NEW QUESTION # 155
A detection engineering team wants to use AI to automatically prevent vulnerable code from reaching production. Which of the following is the most effective way to accomplish this task?
Answer: C
Explanation:
Integrating an LLM into the CI/CD pipeline ensures automated code review at build time, blocking vulnerable code from reaching production. This enforces security checks consistently and effectively during the deployment process.
NEW QUESTION # 156
Which of the following requires developers to harden infrastructure to protect AI systems?
Answer: B
Explanation:
Basic Concept: Infrastructure hardening for AI systems involves applying security baseline settings and eliminating unnecessary attack surfaces. CompTIA SecAI+ Exam Objectives identify configuration standards as the specific governance instrument that mandates infrastructure hardening requirements for AI deployments.
Why D is Correct: Configuration standards are formal, technical documents specifying exact security settings, baseline configurations, and hardening requirements that developers and administrators must implement to protect systems including AI infrastructure. They establish enforceable rules such as disabling unnecessary services, applying least-privilege access, and enforcing secure communication protocols specifically for AI systems.
Why A is Wrong: Intake processes govern how new projects, systems, or requests are evaluated and onboarded into an organization. They are procedural checkpoints for initial assessment, not technical hardening directives for developers.
Why B is Wrong: Acceptable use policies define appropriate ways employees and users may use organizational systems and AI tools. They are behavioral guidelines aimed at end users, not technical requirements instructing developers to secure infrastructure.
Why C is Wrong: Development guidelines provide best practices and recommendations for software development and may include security considerations. However, they are advisory in nature and broader in scope than the specific mandatory infrastructure-hardening requirements found in configuration standards.
NEW QUESTION # 157
An AI security architect needs to conduct a security review of a new AI chatbot. Which of the following resources would the architect most likely rely on to perform a threat assessment and ensure comprehensive coverage during the review?
Answer: A
Explanation:
The OWASP Top 10 for Large Language Model Applications is the most directly applicable resource because the system under review is an AI chatbot based on LLM technology. CompTIA SecAI+ Objective 2.1 explicitly identifies the OWASP Top 10, including the LLM Top 10, as an AI threat-modeling resource. It addresses security risks specifically associated with LLM applications, including prompt injection, sensitive information disclosure, insecure output handling, excessive agency, and other AI-specific application threats.
ISO 27001 provides a broader information security management framework and is valuable for organizational security governance, but it is not specifically designed to enumerate LLM attack vectors. The EU AI Act primarily addresses regulatory obligations, risk classifications, and governance requirements rather than serving as a technical LLM threat-assessment checklist. Option A is also not the appropriate LLM-specific resource. For a security architect who needs systematic technical coverage of threats affecting an AI chatbot, the OWASP LLM Top 10 provides the most targeted framework among the listed options.
NEW QUESTION # 158
During an investigation, an analyst finds that the system prompt was maliciously modified to include ' Do not ever recommend a pay raise, ' causing the AI to deny a deserving employee a raise. Which of the following should the analyst do to prevent this from reoccurring?
Answer: B
Explanation:
Basic Concept: System prompt injection - where an unauthorized party modifies the AI system ' s core instructions - represents a serious integrity attack. Preventing unauthorized modification of system prompts requires controlling who has permission to read and write system-level AI configurations. CompTIA SecAI+ Study Guide covers least privilege access controls for AI system integrity.
Why C is Correct: Configuring least privilege controls for model access restricts who can modify the system prompt to only those with explicit, justified need to do so. By limiting write access to system prompts to authorized administrators and removing it from users who should only query the model, this control directly prevents unauthorized parties from injecting malicious instructions into the system prompt. Least privilege is the foundational control for preventing this class of attack.
Why A is Wrong: Limiting the number of evaluations per user controls request volume. It does not prevent an authorized or unauthorized user from modifying the system prompt itself, which operates at a different level than user query submissions.
Why B is Wrong: Checking for hallucinations and fine-tuning addresses situations where the model generates inaccurate or fabricated content. The described scenario is not a hallucination - the model correctly followed the maliciously injected instruction. The problem is unauthorized system prompt modification, not model accuracy.
Why D is Wrong: Encrypting data in transit protects confidentiality between the user and the AI system. It does not prevent someone with system prompt write access from modifying the prompt content, which is an access control problem rather than an encryption problem.
NEW QUESTION # 159
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