AIF-C01 Guidelines for Responsible AI Practice Question
Exhibit
{
"eventName": "PutRolePolicy",
"requestParameters": {
"roleName": "SageMakerExecutionRole",
"policyDocument": {
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": "sagemaker:InvokeEndpoint",
"Resource": "*"
}
]
}
}
}Refer to the exhibit. An AWS CloudTrail log shows the creation of an IAM policy for a SageMaker execution role. Which responsible AI concern does this configuration raise?
⚠ Common exam trap
AWS often tests the distinction between operational security concerns (like least privilege) and other responsible AI pillars (like data governance or model monitoring), so candidates may confuse a broad IAM policy with a data residency or monitoring issue.
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
✓
Lack of least privilege access control
The CloudTrail log shows the creation of an IAM policy for a SageMaker execution role. If this policy grants overly broad permissions (e.g., `s3:*` or `iam:PassRole` to all resources), it violates the principle of least privilege, which is a core responsible AI concern. Overly permissive roles can lead to unauthorized access to training data, models, or other AWS resources, undermining security and governance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Insufficient training data
Why it's wrong here
Training data volume is unrelated to an IAM policy's permissions; the exhibit concerns which AWS services and resources the SageMaker execution role can reach, so the concern is excessive privilege or unauthorised access. Data sufficiency would be the issue if the question described model accuracy problems or unrepresentative datasets.
- ✓
Lack of least privilege access control
Why this is correct
The created IAM policy grants broader permissions than the SageMaker execution role requires, violating least privilege. Over-scoped role permissions expand the blast radius if the role is compromised, which is the responsible AI access-control concern raised by this CloudTrail configuration.
- ✗
Violation of data residency requirements
Why it's wrong here
Data residency concerns where personal data is physically stored or processed, not which API actions an IAM role may invoke. An IAM policy governs permissions, so the exhibit raises excessive privilege or unauthorised access. Residency would be the answer if the stem showed data replicated to an unapproved AWS Region.
- ✗
Absence of model monitoring
Why it's wrong here
CloudTrail records the IAM policy creation itself, which concerns permissions and least privilege, not runtime model behaviour. Absence of model monitoring is a separate concern detectable through CloudWatch or SageMaker Model Monitor, not through an IAM policy creation event.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services 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 AIF-C01 exam.