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AIF-C01 Practice Question: A company uses Amazon SageMaker to train a model…

A company uses Amazon SageMaker to train a model on customer transaction data. The data is stored in an S3 bucket encrypted with SSE-KMS. The data scientists are using a SageMaker notebook instance to preprocess the data. The security team notices that the notebook instance can access the KMS key directly through the SageMaker console, even when the data scientists do not have explicit KMS permissions. What is the MOST likely reason for this behavior?

⚠ Common exam trap

Test-takers frequently assume the user's own IAM permissions are the only factor, but AWS services like SageMaker can proxy requests using the execution role attached to the resource, effectively decoupling the user's identity from the data access permissions.

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

The SageMaker execution role attached to the notebook instance has permission to use the KMS key for the S3 bucket, and the SageMaker console uses that role to perform decryption operations on behalf of the user.

The SageMaker notebook instance uses an execution IAM role that is assumed when performing operations. If that execution role has permissions to use the KMS key (e.g., kms:Decrypt, kms:GenerateDataKey) for the S3 bucket, the SageMaker console can leverage that role to decrypt data on behalf of the user, even if the user's own IAM identity lacks explicit KMS permissions. The console acts as a proxy, using the notebook's execution role to access the key.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • The KMS key policy allows the SageMaker service to decrypt using the key, and the console displays this permission globally.

    Why it's wrong here

    KMS key policies can allow the SageMaker service, but the console shows access based on the user's effective permissions, not the key policy alone.

  • The S3 bucket has a bucket policy that grants s3:GetObject access using the SageMaker service principal, bypassing KMS permissions.

    Why it's wrong here

    S3 bucket policies do not bypass KMS; KMS still requires separate permissions.

  • The SageMaker execution role attached to the notebook instance has permission to use the KMS key for the S3 bucket, and the SageMaker console uses that role to perform decryption operations on behalf of the user.

    Why this is correct

    The SageMaker execution role is assumed by the notebook instance and has KMS permissions. The console uses the role to show decryption status.

  • The SageMaker notebook instance is using an IAM role that has the AWS managed policy AmazonSageMakerFullAccess, which includes kms:Decrypt for all keys.

    Why it's wrong here

    AmazonSageMakerFullAccess does not include kms:Decrypt for all keys; it only includes permissions for SageMaker resources.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-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.