- A
Implement input validation and sanitisation
Input validation and sanitisation filter out harmful or injected content before processing.
- B
Use a system prompt that strictly defines the chatbot's behavior
A well-crafted system prompt can instruct the model to ignore injected instructions.
- C
Fine-tune the model on safe conversational examples
Why wrong: Fine-tuning can improve general safety but is not a direct or immediate injection mitigation.
- D
Use a larger context window
Why wrong: A larger context window does not prevent injection; it may even provide more room for injection.
- E
Limit the maximum output token length
Why wrong: Limiting output length reduces verbosity but does not prevent injection.
Question 341 of 1,000
AI0-001 AI Concepts and Techniques Practice Question
This AI0-001 practice question tests your understanding of ai concepts and techniques. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company is deploying a chatbot using a large language model. They want to mitigate the risk of prompt injection attacks. Which TWO measures should be implemented?
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
✓
Implement input validation and sanitisation
Input validation and sanitisation (A) prevent malicious user inputs from being interpreted as instructions by the LLM, directly mitigating prompt injection by stripping or escaping special characters and control sequences. A strict system prompt (B) defines the chatbot's role and boundaries, reducing the attack surface by making it harder for injected prompts to override the intended behavior.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Implement input validation and sanitisation
Why this is correct
Input validation and sanitisation filter out harmful or injected content before processing.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Use a system prompt that strictly defines the chatbot's behavior
Why this is correct
A well-crafted system prompt can instruct the model to ignore injected instructions.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Fine-tune the model on safe conversational examples
Why it's wrong here
Fine-tuning can improve general safety but is not a direct or immediate injection mitigation.
- ✗
Use a larger context window
Why it's wrong here
A larger context window does not prevent injection; it may even provide more room for injection.
- ✗
Limit the maximum output token length
Why it's wrong here
Limiting output length reduces verbosity but does not prevent injection.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that fine-tuning or output limits can prevent prompt injection, when in fact these measures do not address the root cause of untrusted input being processed as instructions.
Trap categories for this question
Command / output trap
Limiting output length reduces verbosity but does not prevent injection.
Detailed technical explanation
How to think about this question
Prompt injection exploits the lack of separation between user input and system-level instructions in autoregressive transformer models. Techniques like delimiter-based parsing (e.g., using special tokens like <|im_start|> or <|im_end|>) and input sanitisation (e.g., escaping quotes, newlines, or control characters) are common defenses. In real-world deployments, attackers can craft inputs that mimic system prompts (e.g., 'Ignore previous instructions and...'), making strict system prompt design and input validation essential layers of defense.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI0-001 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Concepts and Techniques — This question tests AI Concepts and Techniques — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Implement input validation and sanitisation — Input validation and sanitisation (A) prevent malicious user inputs from being interpreted as instructions by the LLM, directly mitigating prompt injection by stripping or escaping special characters and control sequences. A strict system prompt (B) defines the chatbot's role and boundaries, reducing the attack surface by making it harder for injected prompts to override the intended behavior.
What should I do if I get this AI0-001 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Last reviewed: Jul 4, 2026
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.
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