- A
Data poisoning
Why wrong: Poisoning affects model training, not inference confidence patterns.
- B
Evasion attack
Why wrong: Evasion causes misclassification, not overconfidence on specific individuals.
- C
Model inversion attack
Inversion exploits confidence scores to infer private training data, often showing high confidence on seen data.
- D
Model extraction attack
Why wrong: Extraction aims to steal model parameters, not produce confidence anomalies.
Quick Answer
The correct answer is model inversion attack. This attack exploits the confidence scores an AI model outputs to reconstruct private training data, which explains why a facial recognition system would show unusually high confidence for familiar individuals while misidentifying others—the model is essentially revealing its training set through overconfident predictions. On the CompTIA AI+ AI0-001 exam, this question tests your ability to distinguish inference-time attacks from data poisoning or evasion; a common trap is confusing model inversion with extraction attacks, but remember that inversion targets data reconstruction from scores, not parameter theft. A useful memory tip: think “inversion inverts the model’s confidence into a mirror of its training data.”
AI0-001 AI Security, Ethics and Governance Practice Question
This AI0-001 practice question tests your understanding of ai security, ethics and governance. 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 security analyst notices that an AI model used for facial recognition is returning unusually high confidence scores for certain individuals while consistently misidentifying others. Which type of attack is most likely occurring?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
Model inversion attack
Option C is correct because a model inversion attack aims to reconstruct training data by exploiting confidence scores, leading to overconfidence on familiar data. Option A is wrong because poisoning corrupts training data, not inference behavior. Option B is wrong because evasion attacks craft adversarial inputs to cause misclassification, not systematic overconfidence. Option D is wrong because extraction attacks steal model parameters through queries, not cause confidence anomalies.
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.
- ✗
Data poisoning
Why it's wrong here
Poisoning affects model training, not inference confidence patterns.
- ✗
Evasion attack
Why it's wrong here
Evasion causes misclassification, not overconfidence on specific individuals.
- ✓
Model inversion attack
Why this is correct
Inversion exploits confidence scores to infer private training data, often showing high confidence on seen data.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Model extraction attack
Why it's wrong here
Extraction aims to steal model parameters, not produce confidence anomalies.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Identify which AI0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
- →
AI Security, Ethics and Governance — study guide chapter
Learn the concepts, then practise the questions
- →
AI Security, Ethics and Governance practice questions
Targeted practice on this topic area only
- →
All AI0-001 questions
500 questions across all exam domains
- →
CompTIA AI+ AI0-001 study guide
Full concept coverage aligned to exam objectives
- →
AI0-001 practice test guide
How to use practice tests most effectively before exam day
Related practice questions
Related AI0-001 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
AI Concepts and Foundations practice questions
Practise AI0-001 questions linked to AI Concepts and Foundations.
Machine Learning and Deep Learning practice questions
Practise AI0-001 questions linked to Machine Learning and Deep Learning.
AI Models and Data Engineering practice questions
Practise AI0-001 questions linked to AI Models and Data Engineering.
AI Implementation and Operations practice questions
Practise AI0-001 questions linked to AI Implementation and Operations.
AI Security, Ethics and Governance practice questions
Practise AI0-001 questions linked to AI Security, Ethics and Governance.
CompTIA A+ hardware practice questions
Practise AI0-001 questions linked to CompTIA A+ hardware.
CompTIA A+ mobile devices practice questions
Practise AI0-001 questions linked to CompTIA A+ mobile devices.
CompTIA A+ networking practice questions
Practise AI0-001 questions linked to CompTIA A+ networking.
CompTIA A+ operating systems practice questions
Practise AI0-001 questions linked to CompTIA A+ operating systems.
CompTIA A+ security practice questions
Practise AI0-001 questions linked to CompTIA A+ security.
CompTIA A+ software troubleshooting questions
Practise AI0-001 questions linked to CompTIA A+ software troubleshooting questions.
CompTIA A+ operational procedures questions
Practise AI0-001 questions linked to CompTIA A+ operational procedures questions.
Practice this exam
Start a free AI0-001 practice session
Short sessions build daily habit. Longer sessions build exam-day stamina. Try a timed session to simulate real conditions.
FAQ
Questions learners often ask
What does this AI0-001 question test?
AI Security, Ethics and Governance — This question tests AI Security, Ethics and Governance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Model inversion attack — Option C is correct because a model inversion attack aims to reconstruct training data by exploiting confidence scores, leading to overconfidence on familiar data. Option A is wrong because poisoning corrupts training data, not inference behavior. Option B is wrong because evasion attacks craft adversarial inputs to cause misclassification, not systematic overconfidence. Option D is wrong because extraction attacks steal model parameters through queries, not cause confidence anomalies.
What should I do if I get this AI0-001 question wrong?
Identify which AI0-001 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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: Jun 23, 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.
Question Discussion
Share a tip, memory trick, or ask about the reasoning behind this question. Do not post real exam questions, leaked content, braindumps, or copyrighted exam material. Comments are moderated and may be removed without notice.
Sign in to join the discussion.