AI0-001 AI Security Practice Question
A company is developing a chatbot that helps users write code. They are concerned about the chatbot being used to generate malicious code. Which defense should they implement to reduce this risk?
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 to detect malicious code patterns
Output filtering and guardrails can detect and block malicious code generation. Input validation helps but the risk is in the output. Red teaming is testing, and data poisoning is a different attack vector.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Output filtering and guardrails to detect malicious code patterns
Why this is correct
Output filtering can prevent the chatbot from returning harmful code.
- ✗
Input validation to block special characters
Why it's wrong here
Input validation is important but the main risk is the chatbot outputting malicious code.
- ✗
Data poisoning prevention during training
Why it's wrong here
Data poisoning is a training-time attack, not directly related to malicious code generation.
- ✗
Red teaming the model before deployment
Why it's wrong here
Red teaming identifies issues but is not a runtime defense.
About these practice questions
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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.