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| Section | Weight | Objectives |
|---|---|---|
| AI-Assisted Security | 24% | - Operational Use of AI
|
| Basic AI Concepts Related to Cybersecurity | 17% | - AI Threat Landscape
|
| Securing AI Systems | 40% | - AI System Protection
|
| AI Governance, Risk, and Compliance | 19% | - AI Governance Frameworks
|
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NEW QUESTION # 67
A human resources officer is using AI to evaluate resumes and help select candidates that meet minimum criteria. To improve the results, the human resources officer adjusts the query parameters and includes an example resume that matches a successful candidate.
Which of the following best describes this query?
Answer: B
Explanation:
Basic Concept: Prompting techniques determine how effectively an LLM is guided to produce desired outputs. Providing a single example within a prompt is a well-established technique known as one-shot prompting, which leverages in-context learning. CompTIA SecAI+ Study Guide covers prompting strategies under basic AI concepts.
Why C is Correct: One-shot prompting involves providing exactly one example of the desired input-output format within the prompt to guide the model ' s responses. In this scenario, the HR officer includes one example resume matching a successful candidate to show the model what a qualifying candidate looks like.
This single example instructs the model on the evaluation criteria through demonstration rather than explicit description.
Why A is Wrong: Distillation is a model training technique where a smaller student model is trained to replicate the behavior of a larger teacher model. It is a model compression methodology, not a prompting technique used at query time.
Why B is Wrong: A prompt template is a reusable, structured format for prompts with placeholders that can be filled in for different queries. While templates may incorporate examples, the term specifically describes the structural framework, not the act of providing a single example.
Why D is Wrong: A system role defines the AI model ' s persona, context, and behavioral guidelines at the system level before user interaction begins. It sets the model ' s overall behavior, not a specific technique of providing examples within queries.
NEW QUESTION # 68
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: D
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 # 69
An organization is concerned with the exposure of sensitive data. Which of the following is the most relevant security concern?
Answer: C
Explanation:
Model inversion is a security concern where attackers can reconstruct or infer sensitive training data from the AI model's outputs. This directly threatens data confidentiality, making it the most relevant concern for sensitive data exposure.
NEW QUESTION # 70
A recently deployed AI system becomes persistently unavailable. A restart temporarily fixes the issue, but the issue happens again. Upon examination of API logs, an analyst finds that external calls continued to use system resources after the action completed.
Which of the following is the best way to improve availability of the system?
Answer: C
Explanation:
Basic Concept: When API sessions or connections remain active and consuming resources after their intended operations have completed, they create resource leaks that progressively degrade system availability. Session lifecycle management is critical for maintaining AI system health. CompTIA SecAI+ Study Guide covers session management as an availability control for AI systems.
Why B is Correct: Enforcing session expiration ensures that external API sessions and connections are automatically terminated after a defined idle period or maximum duration. This prevents resource-consuming zombie sessions from accumulating and exhausting system memory, thread pools, or connection limits. The observed pattern - persistent unavailability that resolves temporarily with restart - is classic resource leak behavior from sessions that never close, making session expiration the direct fix.
Why A is Wrong: Token limits cap the number of tokens processed per request. While useful for controlling per-request resource consumption, they do not address the root cause of sessions persisting and consuming resources long after their operations complete.
Why C is Wrong: Increasing system memory defers the problem rather than solving it. The leak will eventually consume the additional memory too, requiring another restart. Addressing the root cause through session management is superior to scaling resources to accommodate the leak.
Why D is Wrong: MFA adds an additional authentication factor for users accessing the system. It is a security control for identity verification, not a mechanism for managing session lifecycle or preventing resource exhaustion from lingering sessions.
NEW QUESTION # 71
User experience is declining since the launch of a large language model (LLM) in internal networks.
Which of the following should be the highest priority for the prompt engineers?
Answer: C
Explanation:
Basic Concept: Prompt engineers are responsible for designing and refining the prompts and instructions that guide an LLM ' s behavior. When user experience is declining after an LLM launch, this signals that the model ' s outputs are not meeting quality standards. CompTIA SecAI+ addresses prompt engineering quality management under securing and optimizing AI systems.
Why C is Correct: Quality control should be the highest priority when user experience is declining. Prompt engineers must systematically evaluate model responses against quality benchmarks, identify failure patterns causing poor user experience, and iteratively refine prompts to produce accurate, relevant, and appropriately formatted responses. Quality control encompasses testing, evaluation, and continuous improvement of prompt performance.
Why A is Wrong: Customer success management is a business function focused on customer relationship management and retention. While related to user experience outcomes, it is not a technical priority that prompt engineers can directly address through their core competency of prompt design and refinement.
Why B is Wrong: Sales life cycle management is a business process for managing customer acquisition and revenue. It is entirely outside the scope of prompt engineering activities and does not address declining LLM user experience.
Why D is Wrong: Business objectives define what the organization aims to achieve with the LLM deployment. These are set at the strategic level and inform the direction for prompt engineering. They are inputs to the quality control process rather than the priority action prompt engineers should take when experience is declining.
NEW QUESTION # 72
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