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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Basic AI Concepts Related to Cybersecurity | 17% | - AI and Machine Learning Fundamentals
|
| Topic 2: AI-Assisted Security | 24% | - Security Operations Enhancement
|
| Topic 3: AI Governance, Risk, and Compliance | 19% | - AI Governance Frameworks
|
| Topic 4: Securing AI Systems | 40% | - AI System Protection
|
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NEW QUESTION # 10
An AI security administrator receives an inquiry about an unusually high monthly bill from the AI solution provider. The administrator thinks the majority of staff might be using the most powerful model available.
Which of the following AI measures should the administrator implement to lower costs?
Answer: A
Explanation:
Basic Concept: LLM API billing is primarily based on token consumption. High costs resulting from staff using powerful, verbose models can be controlled by limiting the maximum tokens processed per interaction and restricting which models staff can access. CompTIA SecAI+ Study Guide covers token management as the primary cost control mechanism for AI deployments.
Why D is Correct: Implementing token limits caps the maximum tokens consumed per API call for both input and output. This directly controls the per-interaction cost by preventing excessively long prompts or overly verbose model responses from generating large token bills. Combined with model tier restrictions, token limits ensure that interactions with powerful models remain within budget constraints regardless of how extensively staff use the service.
Why A is Wrong: Storage monitoring tracks the utilization and performance of data storage systems. Storage costs are separate from LLM API token-based billing and monitoring storage does not address the high API charges resulting from excessive model usage by staff.
Why B is Wrong: Modality types refer to the input formats an AI model accepts such as text, images, audio, or video. While different modalities have different pricing, managing modality types is not the direct cost control lever. Token consumption is the primary cost driver for text-based interactions.
Why C is Wrong: Prompt firewalls inspect and filter prompt content for security and policy compliance.
While they can block certain types of queries, they are designed for security purposes, not as financial controls to limit token consumption or enforce cost budgets across staff usage.
NEW QUESTION # 11
Customer feedback for an AI chatbot has a high-rate of non-answers, which is causing higher central processing unit (CPU) utilization. Which of the following should be implemented?
Answer: A
Explanation:
Implementing a response confidence level ensures the chatbot only provides answers when the model is sufficiently confident. This reduces irrelevant or empty responses, improving user experience and lowering unnecessary CPU utilization.
NEW QUESTION # 12
Which of the following corporate policies would a security architect most likely reference when configuring an AI system to conduct input filtering?
Answer: A
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 # 13
Which of the following is required first in order to send a prompt query and response in a language model (LLM) system when authentication is enabled?
Answer: D
NEW QUESTION # 14
During the selection of a machine learning (ML)-based threat classification model, a cybersecurity administrator verifies that label distribution is highly unbalanced. Which of the following processing techniques should the engineer use to balance the model?
Answer: B
Explanation:
When label distribution is highly unbalanced, data augmentation generates additional synthetic samples for the underrepresented classes. This balances the dataset, improving the ML model's ability to classify threats accurately across all categories.
NEW QUESTION # 15
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