- A
Supply chain attack
Why wrong: Supply chain attacks target hardware or software before deployment.
- B
Model inversion attack
Why wrong: Inversion aims to extract training data, not alter predictions.
- C
Adversarial example attack
Small manipulation of input causes incorrect output.
- D
Data poisoning attack
Why wrong: Poisoning occurs during training, not at inference on physical objects.
Question 686 of 1,000
Understanding Adversarial Example Attacks
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.
An AI system in a self-driving car misinterprets a stop sign due to a small sticker placed on it. This is an example of which security vulnerability?
Quick Answer
The correct answer is adversarial example attack. This vulnerability occurs when small, carefully crafted perturbations—like a sticker on a stop sign—are added to input data during inference, causing the AI model to misclassify the object even though the change is imperceptible to humans. On the CompTIA AI+ AI0-001 exam, this scenario tests your understanding of attacks that target the model’s decision-making at runtime, distinct from data poisoning (which corrupts training data) or model stealing (which extracts parameters). A common trap is confusing adversarial examples with data poisoning, but remember: adversarial attacks happen after training, during live use. To lock it in, think “sticker on a sign = adversarial at inference time.”
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
✓
Adversarial example attack
Option C is correct because the sticker on the stop sign creates a small perturbation that causes the AI model's image classifier to misclassify the sign (e.g., as a speed limit sign). This is the defining characteristic of an adversarial example attack, where crafted input perturbations exploit model vulnerabilities to cause incorrect predictions.
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.
- ✗
Supply chain attack
Why it's wrong here
Supply chain attacks target hardware or software before deployment.
- ✗
Model inversion attack
Why it's wrong here
Inversion aims to extract training data, not alter predictions.
- ✓
Adversarial example attack
Why this is correct
Small manipulation of input causes incorrect output.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Data poisoning attack
Why it's wrong here
Poisoning occurs during training, not at inference on physical objects.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between attacks that occur during training (data poisoning) versus attacks that occur during inference (adversarial examples), and candidates mistakenly choose data poisoning because they think the sticker 'poisons' the input, but the key is that the model's training data is unaffected.
Detailed technical explanation
How to think about this question
Adversarial examples exploit the linear nature of neural networks in high-dimensional spaces, where small perturbations in pixel space can push the input across decision boundaries. In real-world scenarios, physical adversarial patches (like stickers) must survive environmental variations (lighting, angle) to remain effective, a field known as robust physical adversarial attacks. This vulnerability is particularly critical for safety-critical systems like autonomous vehicles, where a single misclassification can have severe consequences.
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 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: Adversarial example attack — Option C is correct because the sticker on the stop sign creates a small perturbation that causes the AI model's image classifier to misclassify the sign (e.g., as a speed limit sign). This is the defining characteristic of an adversarial example attack, where crafted input perturbations exploit model vulnerabilities to cause incorrect predictions.
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
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Last reviewed: Jul 4, 2026
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