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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Basic AI Concepts Related to Cybersecurity | 17% | - AI applications in security
|
| Topic 2: Securing AI Systems | 40% | - Security controls for AI systems
|
| Topic 3: AI-assisted Security | 24% | - AI in security strategy and operations
|
| Topic 4: AI Governance, Risk and Compliance | 19% | - Compliance and legal requirements
|
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NEW QUESTION # 129
Which of the following is the first step before using an online data set?
Answer: A
Explanation:
A third-party risk management assessment is the best first step because an externally obtained online dataset introduces risks concerning source trustworthiness, provenance, licensing, privacy, integrity, security, and regulatory compliance. CompTIA SecAI+ requires candidates to understand third-party compliance evaluations as part of AI governance and also emphasizes trustworthiness and authenticity during the AI lifecycle ' s data-collection stage. Before incorporating an externally sourced dataset into model development or training, the organization should determine who created or controls the data, whether its collection and distribution are legitimate, whether contractual or usage restrictions exist, and whether sensitive or malicious content could be present. A legal review may subsequently be required for licensing, copyright, privacy, and contractual issues, but third-party risk assessment provides the broader initial evaluation. A feasibility study addresses whether the proposed project is practical from a business perspective rather than whether the dataset is trustworthy. Model design review occurs later and focuses on architecture and implementation.
Consequently, third-party risk management provides the most comprehensive initial gate before introducing an online dataset into the organization ' s AI lifecycle.
NEW QUESTION # 130
Which of the following corporate policies would a security architect most likely reference when configuring an AI system to conduct input filtering?
Answer: D
Explanation:
Data governance is the most relevant corporate policy because input filtering depends on knowing what information may enter the AI system, how that information is classified, and which categories of sensitive or regulated data must be blocked, redacted, masked, or otherwise controlled. CompTIA SecAI+ specifically includes sensitive data governance under corporate AI policies and separately identifies data classification labels, redaction, masking, minimization, and related data-safety controls. A security architect can therefore translate the organization ' s data governance rules into technical input-filtering requirements, such as preventing credentials, customer PII, financial information, confidential intellectual property, or restricted datasets from being submitted to a model. A public-model usage policy governs whether and how employees may use externally hosted models, but it is narrower than the underlying data-handling rules. Third-party compliance evaluates external providers and contractual or regulatory obligations. Terms of use describe permitted user behavior but normally do not provide the detailed data-classification requirements required to implement technical filtering. Data governance is therefore the authoritative basis for determining what input the AI system should accept or reject.
NEW QUESTION # 131
A manufacturing company wants to use AI within its operations to improve the efficiency and accuracy of its processes. Which of the following should the organization do first to enable adoption and achieve the business objectives?
Answer: A
Explanation:
The first step in adopting AI to meet business objectives is to establish the right expertise. A data and AI architect can design the overall strategy, infrastructure, and data pipelines needed for effective AI integration, ensuring alignment with operational goals before selecting specific models or certifications.
NEW QUESTION # 132
A company uses human review for software development validation and wants to add another validation layer.
Which of the following should a security administrator use to accomplish this task?
Answer: A
Explanation:
Basic Concept: Adding validation layers to software development processes improves security assurance by catching issues that human reviewers might miss. AI-assisted validation provides an automated, systematic review that complements human judgment. CompTIA SecAI+ Study Guide covers AI-assisted development security controls.
Why A is Correct: AI-assisted approval adds an intelligent automated review layer that works alongside existing human review. AI can systematically analyze code for security vulnerabilities, coding standard violations, dependency risks, and policy compliance with greater consistency and speed than manual review.
This creates a defense-in-depth validation approach where both AI and human reviewers must approve changes, catching issues that either layer might miss independently.
Why B is Wrong: A low-code plug-in provides simplified visual development tools that reduce the amount of manual code writing required. It is a development productivity tool, not a security validation layer for reviewing already-written code.
Why C is Wrong: Automated rollback is a deployment safety mechanism that reverts a deployment to the previous version when errors are detected after deployment. It is a recovery control, not a validation layer applied during the development review process.
Why D is Wrong: Regression testing verifies that new code changes have not broken existing functionality. It tests functional correctness, not security vulnerabilities, and does not add an AI-powered security validation capability to the existing human review process.
NEW QUESTION # 133
A SOC team has an AI agent that performs web searches and calls to the SOAR solution. The team is concerned about enterprise uptime and case resolution time.
Which of the following is the most appropriate use of the AI agent?
Answer: B
Explanation:
Basic Concept: AI agents in SOC environments can automate repetitive, rules-based response actions that previously required human intervention. When the primary concerns are enterprise uptime and case resolution time, the AI agent ' s ability to autonomously execute containment actions through SOAR is the most impactful application. CompTIA SecAI+ Study Guide covers AI agent use cases in security operations.
Why A is Correct: Using the AI agent to analyze incidents and execute containment actions through SOAR playbooks directly addresses both uptime and resolution time concerns. The agent can immediately analyze alert details, determine the appropriate playbook, and execute containment actions such as isolating compromised hosts or disabling compromised accounts autonomously, without waiting for human intervention. This dramatically reduces mean time to contain threats, improving both uptime and resolution speed.
Why B is Wrong: Enriching alerts with open-source intelligence improves analyst context but is a preparatory step rather than a response action. While valuable, it does not directly reduce resolution time by taking containment actions to stop ongoing threats.
Why C is Wrong: Aggregating metrics and generating leadership reports is an administrative function that consumes agent capacity for non-operational purposes. It improves visibility but does not directly improve uptime or case resolution time for active incidents.
Why D is Wrong: Creating tabletop exercises improves team preparedness over time through training scenarios. While beneficial for long-term capability development, it does not directly address the immediate concerns of enterprise uptime and active case resolution time.
NEW QUESTION # 134
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