8 results · Feed
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High 7.2
Missing integrity verification in Triton inference handler in Amazon SageMaker Python SDK
Missing integrity verification in the Triton inference handler in Amazon SageMaker Python SDK v2 before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to achieve code execution in inference containers via replacement of model artifacts…
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High 7.2
Cleartext storage of HMAC signing key in Amazon SageMaker Python SDK ModelBuilder/Serve path
Cleartext storage of sensitive information in the ModelBuilder/Serve component in Amazon SageMaker Python SDK before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to extract the HMAC signing key from SageMaker API responses and forge …
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High —
SageMaker Python SDK replaced eval() with safe parser in JumpStart search functionality
## Summary This advisory addresses the use of the search_hub() function within the SageMaker Python SDK's JumpStart search functionality. An actor with the ability to control query parameters passed to the search_hub() function could potentially provide malfo…
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Medium 5.9
TLS disabled by default in select aws/sagemaker-python-sdk configurations
Amazon SageMaker Python SDK before v3.1.1 or v2.256.0 disables TLS certificate verification for HTTPS connections made by the service when a Triton Python model is imported, incorrectly allowing for requests with invalid and self-signed certificates to succee…
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High 7.2
Cleartext transmission of sensitive materials in aws/sagemaker-python-sdk
The Amazon SageMaker Python SDK before v3.2.0 and v2.256.0 includes the ModelBuilder HMAC signing key in the cleartext response elements of the DescribeTrainingJob function. A third party with permissions to both call this API and permissions to modify object…
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Medium 5.9
MD5 Hash Collision in SageMaker Workflow in aws/sagemaker-python-sdk
A vulnerability in the SageMaker Workflow component of aws/sagemaker-python-sdk allows for the possibility of MD5 hash collisions in all versions. This can lead to workflows being inadvertently replaced due to the reuse of results from different configuration…
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High 7.8
Deserialization of Untrusted Data in sagemaker-python-sdk
sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. The sagemaker.base_deserializers.NumpyDeserializer module before v2.218.0 allows potentially unsafe deserialization when untrusted data is passed as pick…
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High 7.8
Command Injection in sagemaker-python-sdk
sagemaker-python-sdk is a library for training and deploying machine learning models on Amazon SageMaker. In affected versions the capture_dependencies function in `sagemaker.serve.save_retrive.version_1_0_0.save.utils` module allows for potentially unsafe Op…