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AIF-C01 Practice Question: A machine learning team needs to share a trained…
A machine learning team needs to share a trained model with multiple teams across different AWS accounts. The model artifacts are stored in an S3 bucket in the central account. What is the most secure way to grant cross-account read access to the model artifacts?
⚠ Common exam trap
Watch out — candidates often assume S3 bucket policies alone are sufficient for cross-account access, overlooking the need for KMS key policies and IAM role permissions when encryption is involved, which is a common real-world requirement for securing sensitive ML artifacts.
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
✓
Use AWS KMS to encrypt the artifacts and share the KMS key with the target accounts, then use bucket policies and IAM roles in the target accounts.
It implements a defense-in-depth approach: AWS KMS encrypts the model artifacts at rest, and cross-account access is granted by combining an S3 bucket policy that allows the target accounts' IAM roles to read the objects, with those roles assuming the necessary permissions. This ensures that only authenticated and authorized IAM principals in the target accounts can decrypt and access the artifacts, preventing unauthorized access even if the bucket policy is misconfigured.
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 an S3 bucket policy that grants access to the root user of each target account.
Why it's wrong here
Root user access is too broad; best practice is to use IAM roles.
- ✗
Make the S3 bucket public.
Why it's wrong here
Public bucket exposes data to the internet, which is insecure.
- ✗
Use S3 cross-region replication to copy the artifacts to each target account's bucket.
Why it's wrong here
Replication does not control access and may not comply with data residency requirements.
- ✓
Use AWS KMS to encrypt the artifacts and share the KMS key with the target accounts, then use bucket policies and IAM roles in the target accounts.
Why this is correct
This ensures least privilege and encryption in transit and at rest.
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.