AI0-001 AI Security, Ethics and Governance Practice Question
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?
⚠ Common exam trap
The AI0-001 exam 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.
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
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Adversarial example attack
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.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Supply chain attack
Why it's wrong here
A supply chain attack compromises a third-party component, library or model artefact before deployment; the sticker is an adversarial input crafted at inference. It is tempting because supply chain risks also undermine AI integrity, but they originate in the development pipeline, not the environment.
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Model inversion attack
Why it's wrong here
Model inversion reconstructs training data by querying a model's outputs, whereas the sticker directly manipulates a live input to force misclassification. It is tempting because both exploit model behaviour, but inversion targets privacy of training data, not physical-world input tampering.
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Adversarial example attack
Why this is correct
A small sticker deliberately alters pixel patterns the model relies on, causing misclassification while appearing benign to humans. This is a crafted input perturbation, the defining characteristic of an adversarial example attack, distinct from data poisoning or model inversion.
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Data poisoning attack
Why it's wrong here
Data poisoning corrupts the training dataset to embed malicious behaviour in the model, whereas this sticker is applied at inference time to the physical sign. It is tempting because poisoning also degrades model accuracy, but it occurs during training, not through real-world input manipulation.
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.