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AI0-001 AI Security Practice Question

An organization uses a fine-tuned LLM for generating financial reports. An attacker gains access to the model's API and sends a series of queries that gradually reconstruct the training data of the fine-tuned model. This is an example of which attack?

⚠ Common exam trap

Candidates may confuse model inversion with model extraction; extraction steals the model parameters, inversion reconstructs training data.

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

Model inversion attacks aim to reconstruct training data from model outputs. Data poisoning corrupts training, model extraction steals the model, and membership inference determines presence, not reconstruction.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Membership inference

    Why it's wrong here

    Membership inference only determines if a data point was in training, not reconstruct the data itself.

  • Data poisoning

    Why it's wrong here

    Data poisoning involves corrupting training data, not reconstructing it.

  • Model extraction

    Why it's wrong here

    Model extraction copies the model's behavior, not the training data.

  • Model inversion

    Why this is correct

    Model inversion uses model outputs to infer or reconstruct training data.

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.