AIF-C01 Security, Compliance, and Governance for AI Solutions — Timed 10 Questions

Question 1

A data scientist needs to allow a foundation model in Amazon Bedrock to access a specific S3 bucket containing reference documents. The bucket is in a different AWS account. What is the MOST secure way to grant access?

10 minute time limit — choose an answer to begin.

Accepted Answer

Configure the S3 bucket policy to allow access from the Bedrock service role and add a Bedrock resource policy allowing the bucket. Cross-account access requires both the S3 bucket policy to grant the Bedrock service role and the Bedrock resource policy to allow the bucket, ensuring least privilege.

Answer

Use AWS Lake Formation to grant cross-account access to the bucket

Answer

Copy the S3 bucket to the same account as Bedrock

Answer

Make the S3 bucket public and use a pre-signed URL

Question 2

An organization uses AWS Lake Formation to govern a data lake used for SageMaker training. They need to enforce row-level security so that different teams only see data relevant to their projects. Which Lake Formation feature should they use?

Accepted Answer

Row-level security. Lake Formation's row-level security uses filters to restrict access to specific rows based on conditions.

Answer

Cell-level security

Answer

Column-level security

Answer

Tag-based access control

Question 3

A company wants to use a third-party foundation model in Bedrock and is concerned about the provider's data handling policies. Which action should they take to ensure their data is not used for model training by the provider?

Accepted Answer

Review the provider's data privacy policy and enable the opt-out option for training data use if available. AWS provides model access approval settings where customers can review and accept data handling policies; many providers offer opt-out options for training data use.

Answer

Use Bedrock's content filters to block sensitive data

Answer

Encrypt all data with KMS before sending to Bedrock

Answer

Use a custom model hosted on SageMaker instead

Question 4

A company wants to enforce strict data residency for training data used in SageMaker. The data must never leave a specific AWS Region. Which THREE actions should they take? (Choose 3)

Accepted Answer

Use KMS customer managed keys specific to the region. Option A is correct because KMS customer managed keys are Region-specific resources, so using a CMK created in the target Region ensures that encryption/decryption of training data stays bound to that Region and cannot be performed by a key in another Region. Option C is correct because S3 bucket policies can include conditions such as aws:RequestedRegion or aws:SourceRegion (or aws:SourceVpc/aws:SourceVpce) to explicitly deny requests that do not originate from within the required Region, enforcing data residency at the access-control layer. Option E is correct because creating a VPC in the desired Region and placing SageMaker resources (notebook instances, training jobs, endpoints) inside that VPC keeps compute and network traffic local to the Region, preventing data from being processed elsewhere. Option B is incorrect because KMS multi-Region keys are designed to replicate key material across Regions, which directly conflicts with strict data residency. Option D is incorrect because enabling cross-region replication for the S3 bucket would copy the training data into another Region, violating the requirement that data never leave the specified Region.

Answer

Use AWS KMS multi-Region keys to encrypt data

Answer

Enable cross-region replication for the S3 bucket

Question 5

A healthcare company uses Amazon SageMaker to train a model on patient data. To meet HIPAA compliance, they must ensure training data is encrypted at rest and in transit. Additionally, the training job should not have internet access. Which combination of actions should the company take?

Accepted Answer

Specify a KMS key for SageMaker's VolumeKmsKeyId and configure the training job to run in a VPC without a public internet route. Specifying a KMS key via VolumeKmsKeyId encrypts the SageMaker training volume at rest, and running the training job in a VPC without a public internet route enforces network isolation. Together these satisfy HIPAA requirements for encryption at rest and in transit plus no internet access. This is the standard SageMaker secure training pattern.

Answer

Use AWS Certificate Manager (ACM) to issue a certificate for the training job and enable network isolation

Answer

Enable SageMaker data capture and use a private VPC with an internet gateway

Answer

Store training data in an encrypted S3 bucket and use a SageMaker notebook instance inside a VPC

Question 6

A data scientist is using Amazon SageMaker to train a model with data that resides in an S3 bucket owned by another AWS account. The training job fails with access denied errors. The data scientist has already been granted cross-account read access to the S3 bucket via a bucket policy. What additional configuration is required?

Accepted Answer

Modify the SageMaker execution role to include an s3:GetObject permission for the bucket and ensure the bucket policy grants access to that role. SageMaker training jobs run within a SageMaker execution role. The role must have a trust policy allowing SageMaker to assume it, and the role must have permissions to read from the S3 bucket. The bucket policy alone is insufficient if the execution role does not have the necessary S3 permissions.

Answer

Add an AWS KMS key policy to allow cross-account decryption

Answer

Create a new VPC peering connection between the two accounts

Answer

Use AWS Lake Formation to grant cross-account permissions on the S3 data

Question 7

A machine learning team uses Amazon SageMaker to train and deploy models. They need to ensure that only approved base models from the AWS Marketplace are used. Which feature should they use to enforce this policy?

Accepted Answer

IAM policies that allow only specific model package ARNs from the AWS Marketplace. SageMaker Role Manager helps administrators create least-privilege IAM roles, but it does not restrict which models can be used. Model access in SageMaker is controlled via IAM policies on the CreateTrainingJob and CreateModel APIs, combined with resource-level permissions.

Answer

SageMaker Role Manager

Answer

AWS Config rules to detect non-compliant models

Answer

SageMaker Model Registry

Question 8

A financial institution is using Amazon Bedrock for a customer-facing application. They must ensure compliance with data residency requirements: model inputs and outputs must not leave a specific AWS Region. Which THREE steps should they take? (Choose THREE)

Accepted Answer

Enable Bedrock model invocation logging to an S3 bucket and CloudWatch Logs in the same Region. Option B is correct because enabling Bedrock model invocation logging to an S3 bucket and CloudWatch Logs in the same Region keeps the captured inputs and outputs within the required Region, satisfying data residency. Option C is correct because using AWS KMS with a customer managed key in the desired Region ensures data at rest is encrypted with a key that never leaves that Region, which is essential for residency compliance. Option D is correct because configuring an AWS PrivateLink VPC endpoint for Amazon Bedrock in the desired Region keeps invocation traffic on the AWS network within that Region and avoids cross-Region endpoints. Option A is incorrect because storing invocation logs in a different Region for disaster recovery would move model inputs and outputs outside the required Region, violating residency. Option E is incorrect because AWS Global Accelerator routes traffic across Regions for performance, which would not help and could conflict with keeping data within a single Region.

Answer

Set up an S3 bucket for model invocation logs in a different Region for disaster recovery

Answer

Use AWS Global Accelerator to route traffic to Bedrock across regions for better performance

Question 9

A data scientist needs to restrict access to a specific Amazon SageMaker notebook instance so that only a designated IAM role can invoke the CreatePresignedNotebookInstanceUrl API. Which IAM policy element should be used to achieve this?

Accepted Answer

Add a Condition block in the IAM policy attached to the user's role. Amazon SageMaker notebook instances do not support resource-based policies. The correct way to restrict the CreatePresignedNotebookInstanceUrl API to a specific IAM role is to attach an identity-based policy to the user's role that includes a Condition block specifying the resource ARN of the notebook instance. This ensures only that role can generate presigned URLs for that instance.

Answer

Modify the trust policy of the IAM role

Answer

Place the notebook instance in a private VPC subnet

Answer

Use a resource-based policy on the notebook instance

Question 10

A company is using Amazon Bedrock to generate text summaries of customer emails. The compliance team requires that any email containing a Social Security Number (SSN) must be blocked from being sent to the model for summarization. Which Bedrock Guardrail configuration should be used?

Accepted Answer

Use a content policy with a PII filter set to 'Deny' for SSN. Bedrock Guardrails can be configured to filter content before it is sent to the model. PII redaction with a deny action will block the input if SSNs are detected. The guardrail is applied at invocation time.

Answer

Configure a topic restriction to block 'PII' topics

Answer

Enable model invocation logging and manually review all inputs

Answer

Add a word filter with a list of common SSN patterns