AI0-001 AI Security Practice Question
An organization is evaluating a third-party large language model to integrate into their customer-facing application. As part of supply chain security, which THREE steps should they take to vet the model before deployment?
⚠ Common exam trap
AI0-001 often tests whether candidates confuse offensive security techniques (model inversion) or training methodologies (federated learning) with the standard vetting triad of red teaming, model card review, and SBOM analysis.
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
✓
Conduct security testing, including red teaming, to identify vulnerabilities in the model
Option A is correct because security testing such as red teaming is a core supply chain vetting step that probes the third-party LLM for prompt injection, jailbreaks, data leakage, and other adversarial vulnerabilities before it is exposed to customers. Option C is correct because reviewing the model card and documentation reveals the model's intended use, limitations, training provenance, and known biases, allowing the organization to assess whether the model is suitable and safe for its customer-facing scenario. Option E is correct because an SBOM for AI components enumerates the model's dependencies, libraries, and versions, enabling the organization to identify known vulnerabilities and manage supply chain risk. Option B does not belong because federated learning is a training technique for building or adapting models on distributed internal data, not a vetting step for evaluating a third-party model. Option D does not belong because running a model inversion attack is an offensive research technique that could itself compromise privacy, rather than a standard supply chain security review step.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Conduct security testing, including red teaming, to identify vulnerabilities in the model
Why this is correct
Red teaming actively probes the third-party model for exploitable weaknesses, such as jailbreaks or harmful outputs, before it faces customers. This directly satisfies the supply chain security requirement to validate the model's behaviour rather than trusting vendor claims alone.
- ✗
Use federated learning to retrain the model on internal data
Why it's wrong here
Federated learning retrains a model on distributed internal data, which is a development approach rather than a pre-deployment supply-chain check of a third-party model. It is tempting because it improves privacy during training, but the organisation is evaluating, not rebuilding, the vendor's model.
- ✓
Review the model card and documentation for intended use, limitations, and known biases
Why this is correct
The model card documents intended use, limitations and known biases, letting the organisation assess whether the third-party model suits its customer-facing context. This satisfies supply chain security by verifying provenance and disclosed risk before deployment.
- ✗
Run a model inversion attack on the model to verify training data privacy
Why it's wrong here
Running a model inversion attack is an offensive research technique, not a supply-chain vetting step an organisation performs on a vendor's model before deployment. It is tempting because inversion tests training-data privacy, but that belongs to red-team evaluation, whereas vetting requires reviewing provenance, licences and documented privacy controls.
- ✓
Obtain a software bill of materials (SBOM) for AI components to identify dependencies and known vulnerabilities
Why this is correct
An SBOM enumerates the model's constituent components, libraries and dependencies, exposing known vulnerabilities and provenance gaps that direct inspection of the model artefact alone cannot reveal. This satisfies the supply chain security constraint by making third-party dependencies auditable before deployment, enabling the organisation to assess inherited risk from upstream providers.
About these practice questions
This AI0-001 question is part of Courseiva's 962-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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.