Summary
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. We identified an issue where SSL certificate verification was globally disabled in the Triton Python backend.
Impact
Arbitrary Code Execution: Disabling SSL verification allows third parties to intercept HTTPS traffic and replace models or dependencies with inappropriate versions. This could lead to remote code execution in the Triton container.
Impacted versions
- SageMaker Python SDK v3 < v3.1.1
- SageMaker Python SDK v2 < v2.256.0
Patches
This issue has been addressed in SageMaker Python SDK version v3.1.1 and v2.256.0. We recommend upgrading to the latest version immediately and ensuring any forked or derivative code is patched to incorporate the new fixes.
Workarounds
Customers using self-signed certificates for internal model downloads should add their private Certificate Authority (CA) certificate to the container image rather than relying on the SDK’s previous insecure configuration. This opt-in approach maintains security while accommodating internal trusted domains.
References
If you have any questions or comments about this advisory, we ask that you contact AWS Security via our vulnerability reporting page or directly via email to aws-security@amazon.com. Please do not create a public GitHub issue.
Summary
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. We identified an issue where SSL certificate verification was globally disabled in the Triton Python backend.
Impact
Arbitrary Code Execution: Disabling SSL verification allows third parties to intercept HTTPS traffic and replace models or dependencies with inappropriate versions. This could lead to remote code execution in the Triton container.
Impacted versions
Patches
This issue has been addressed in SageMaker Python SDK version v3.1.1 and v2.256.0. We recommend upgrading to the latest version immediately and ensuring any forked or derivative code is patched to incorporate the new fixes.
Workarounds
Customers using self-signed certificates for internal model downloads should add their private Certificate Authority (CA) certificate to the container image rather than relying on the SDK’s previous insecure configuration. This opt-in approach maintains security while accommodating internal trusted domains.
References
If you have any questions or comments about this advisory, we ask that you contact AWS Security via our vulnerability reporting page or directly via email to aws-security@amazon.com. Please do not create a public GitHub issue.