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CY0-001: CompTIA SecAI+ Beta
Free Practice Exam Questions (page: 8)
Updated On: 10-Jan-2026

Page 3 of 17
PDF with 78 Questions

A security operations center (SOC) has a very high volume of logs and alerts. The manager proposes the implementation of machine learning (ML) system to help with triage.
Which of the following tasks is most suitable?

  1. Applying filters on specific alerts
  2. Automatically patching vulnerable systems
  3. Identifying and classifying alerts
  4. Summarizing the content of alerts

Answer(s): C

Explanation:

Machine learning is best suited for analyzing large volumes of security data and distinguishing between true threats and false positives. By identifying and classifying alerts, the ML system helps the SOC prioritize incidents and reduce analyst workload.



An organization recently created a custom model that integrates with a language model (LLM). The developer notices that the application programming interface (API) costs have increased.
Which of the following is the best control to reduce cost?

  1. Implementing prompt templates
  2. Increasing central processing unit (CPU) and memory
  3. Reducing the model size
  4. Adjusting token limits

Answer(s): D

Explanation:

API costs for large language model integrations are directly tied to token usage (input + output tokens). By adjusting token limits, the organization can reduce unnecessary processing of overly long prompts or responses, thereby lowering overall API costs without changing model size or infrastructure resources.



A security administrator needs to improve an AI model. During an initial investigation, the administrator notices that two successive login features are recorded every day, and then a successful login occurs after a specific time interval. All the successful login attempts have been during office hours.
Which of the following techniques should the administrator use to improve the AI model's security?

  1. Access management
  2. Pattern recognition
  3. Signature matching
  4. Vulnerability analysis

Answer(s): B

Explanation:

The administrator is analyzing repeated login behaviors and time-based patterns that precede successful access. Pattern recognition allows the AI model to detect these behavioral trends, improving its ability to identify anomalies or potential attacks while aligning with normal office-hour login behavior.



Which of the following is the most concerning risk for a company that allows corporate end users to use public- facing large language models (LLMs)?

  1. Inaccuracies due to hallucinations
  2. Out-of-date acceptable use policies
  3. Data security regulatory violations
  4. Malicious code generation

Answer(s): C

Explanation:

The greatest concern with employees using public-facing LLMs is the potential exposure of sensitive or regulated corporate data. Submitting such information to external systems may violate data protection laws (e.g., GDPR, HIPAA), creating legal and compliance risks that outweigh issues like hallucinations or malicious outputs.



Which of the following requires developers to harden infrastructure to protect AI systems?

  1. Intake processes
  2. Acceptable use policies
  3. Development guidelines
  4. Configuration standards

Answer(s): D

Explanation:

Configuration standards define how infrastructure and systems must be securely set up and maintained. By following these standards, developers harden the environment that supports AI systems, reducing risks from misconfigurations and vulnerabilities.



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Viewing questions 36 - 40 out of 78 questions



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