AIF-C01 Practice Question: Security, Compliance and Governance for AI Solutions
This AIF-C01 practice question tests your understanding of security, compliance and governance for ai solutions. 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.
A data science team is using Amazon SageMaker to build a model. They want to ensure that only authorized users can deploy models to production. Which TWO methods can they use to enforce this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use SageMaker Model Registry to require approval before deployment.
Option A is correct because SageMaker Model Registry allows you to set up an approval workflow for model versions. By requiring explicit approval before a model can be deployed to production, you enforce a governance gate that prevents unauthorized or unverified models from being used in production endpoints.
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.
✓
Use SageMaker Model Registry to require approval before deployment.
Why this is correct
Model Registry can enforce an approval workflow before a model is deployed.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable multi-factor authentication (MFA) for all AWS accounts.
Why it's wrong here
MFA provides an extra layer of login security but does not prevent authorized users from deploying.
✓
Use IAM policies to restrict the sagemaker:CreateEndpoint action to specific users.
Why this is correct
This directly controls who can create endpoints.
Related concept
Read the scenario before looking for a memorised answer.
✗
Use AWS CloudTrail to audit deployment actions.
Why it's wrong here
CloudTrail logs actions but does not enforce restrictions.
✗
Use Amazon GuardDuty to monitor for unauthorized deployment.
Why it's wrong here
GuardDuty detects threats but does not prevent authorized users from deploying.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse auditing or monitoring services (like CloudTrail or GuardDuty) with preventive controls, failing to recognize that only IAM policies and registry approval workflows can actively block unauthorized deployment actions.
Detailed technical explanation
How to think about this question
Under the hood, SageMaker Model Registry integrates with AWS IAM and AWS CodePipeline to enforce approval gates. When a model version is marked as 'Approved' in the registry, it can be used in a production endpoint; otherwise, any attempt to deploy an unapproved version will fail. This is often combined with a CI/CD pipeline that triggers a Lambda function to validate the approval status before allowing the CreateEndpoint API call.
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 company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Security, Compliance and Governance for AI Solutions — This question tests Security, Compliance and Governance for AI Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use SageMaker Model Registry to require approval before deployment. — Option A is correct because SageMaker Model Registry allows you to set up an approval workflow for model versions. By requiring explicit approval before a model can be deployed to production, you enforce a governance gate that prevents unauthorized or unverified models from being used in production endpoints.
What should I do if I get this AIF-C01 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.
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Question Discussion
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