AAISM AI Risk Management Practice Question
You are assessing a supply chain risk where an AI model uses a pre-trained base model from a third-party hub. Which action most effectively mitigates the risk of model poisoning during the integration phase?
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
✓
Validate the model hash against the vendor's provided checksum manifest.
Verifying the cryptographic hash of the model weights against the provider's manifest ensures integrity before deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Implement role-based access control for the training pipeline.
Why it's wrong here
RBAC controls access but does not validate the integrity of external dependencies.
- ✗
Run a sensitivity analysis on the model output.
Why it's wrong here
Sensitivity analysis identifies stability issues but not integrity tampering.
- ✓
Validate the model hash against the vendor's provided checksum manifest.
Why this is correct
Cryptographic verification ensures the model has not been altered since publication.
- ✗
Enable MFA for the model registry access.
Why it's wrong here
MFA secures access but does not verify the integrity of the binary itself.
About these practice questions
Courseiva writes every AAISM question from scratch — 205 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or 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 August 2026 · checked against the official ISACA exam blueprint
This AAISM practice question is part of Courseiva's free ISACA 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 AAISM exam.