AWS sagemaker documentation change
Summary
Corrected method name from 'update_userprofile' to 'update_user_profile' in documentation text and code examples
Security assessment
The change fixes a typo in an API method name but does not address any specific security vulnerability or weakness. While proper API usage is important for security posture, this appears to be a documentation accuracy improvement rather than a response to a security issue.
Diff
diff --git a/sagemaker/latest/dg/studio-emr-serverless-permissions.md b/sagemaker/latest/dg/studio-emr-serverless-permissions.md index 724b7919b..9c227b714 100644 --- a//sagemaker/latest/dg/studio-emr-serverless-permissions.md +++ b//sagemaker/latest/dg/studio-emr-serverless-permissions.md @@ -159 +159 @@ Python script -In a JupyterLab application started from a private space using the SageMaker AI execution role whose permissions you updated, run the following command in a terminal. Replace the `domainID`, `user-profile-name`, `studio-accountID`, and `EMRServerlessRuntimeExecutionRole`(s) with their proper values. This code snippet updates the user profile settings for a specific user profile (`client.update_userprofile`) or domain settings (`client.update_domain`), specifically associating the EMR Serverless runtime execution roles you previously created. +In a JupyterLab application started from a private space using the SageMaker AI execution role whose permissions you updated, run the following command in a terminal. Replace the `domainID`, `user-profile-name`, `studio-accountID`, and `EMRServerlessRuntimeExecutionRole`(s) with their proper values. This code snippet updates the user profile settings for a specific user profile (`client.update_user_profile`) or domain settings (`client.update_domain`), specifically associating the EMR Serverless runtime execution roles you previously created. @@ -166 +166 @@ In a JupyterLab application started from a private space using the SageMaker AI - client.update_userprofile( + client.update_user_profile( @@ -381 +381 @@ Python script -In a JupyterLab application started from a private space using the SageMaker AI execution role whose permissions you updated, run the following command in a terminal. Replace the `domainID`, `user-profile-name`, `studio-accountID`, and `EMRServerlessRuntimeExecutionRole` with their proper values. This code snippet updates the user profile settings for a specific user profile (`client.update_userprofile`) or domain settings (`client.update_domain`) within a SageMaker AI domain. Specifically, it sets the runtime execution roles for Amazon EMR Serverless, which you have previously created. It also allows the JupyterLab application to assume a particular IAM role (`AssumableRole`) for running EMR Serverless applications within the Amazon EMR account. +In a JupyterLab application started from a private space using the SageMaker AI execution role whose permissions you updated, run the following command in a terminal. Replace the `domainID`, `user-profile-name`, `studio-accountID`, and `EMRServerlessRuntimeExecutionRole` with their proper values. This code snippet updates the user profile settings for a specific user profile (`client.update_user_profile`) or domain settings (`client.update_domain`) within a SageMaker AI domain. Specifically, it sets the runtime execution roles for Amazon EMR Serverless, which you have previously created. It also allows the JupyterLab application to assume a particular IAM role (`AssumableRole`) for running EMR Serverless applications within the Amazon EMR account. @@ -388 +388 @@ In a JupyterLab application started from a private space using the SageMaker AI - client.update_userprofile( + client.update_user_profile(