AWS Sagemaker Python Sdk vulnerabilities

3 vulnerabilities

Known vulnerabilities in AWS Sagemaker Python Sdk, newest first, with CVSS severity, EPSS, KEV listings, ransomware use and the affected versions.

7.8CVE-2024-34072awssagemaker-python-sdk+1
EPSS score
0.41%
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 pickled object arrays. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity. Users are advised to upgrade to version 2.218.0. Users unable to upgrade should not pass pickled numpy object arrays which originated from an untrusted source, or that could have been tampered with. Only pass pickled numpy object arrays from trusted sources.7.8CVE-2024-34073awssagemaker-python-sdk+1
EPSS score
1.15%
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 Operating System (OS) Command Injection if inappropriate command is passed as the “requirements_path” parameter. This consequently may allow an unprivileged third party to cause remote code execution, denial of service, affecting both confidentiality and integrity. This issue has been addressed in version 2.214.3. Users are advised to upgrade. Users unable to upgrade should not override the “requirements_path” parameter of capture_dependencies function in `sagemaker.serve.save_retrive.version_1_0_0.save.utils`, and instead use the default value.8.5CVE-2026-83551awssagemaker-python-sdk
EPSS score
0.80%
Cleartext storage of sensitive information in the @step and @remote decorator pipeline component in Amazon SageMaker Python SDK before v3.11.0 and v2.256.0 might allow an authenticated remote user to extract the HMAC signing key from SageMaker DescribePipeline API responses and forge valid integrity signatures for specially crafted function payloads, achieving code execution in another user's pipeline execution context within the same AWS account.