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AI0-001 AI Security Practice Question

An LLM-based chatbot is being deployed for customer support. The security team wants to prevent the bot from generating toxic or harmful responses. Which defense is MOST appropriate?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Output filtering and guardrails

Output filtering and guardrails can block harmful content before it reaches the user. Input validation sanitizes inputs, red teaming identifies vulnerabilities, and rate limiting prevents abuse but not toxic content.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Input validation and sanitization

    Why it's wrong here

    Input validation helps prevent injection but does not stop the model from generating toxic outputs.

  • Rate limiting on API requests

    Why it's wrong here

    Rate limiting limits request volume but does not filter content.

  • Output filtering and guardrails

    Why this is correct

    Output filters and guardrails can detect and block harmful content in real-time.

  • Red teaming the AI system

    Why it's wrong here

    Red teaming is a testing methodology, not a runtime defense.

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JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.