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5 CVE

Critique 0 Élevée 4 Moyenne 1 Faible 0 Non évaluée 0 Exploitées (KEV) Tri : plus récentes « AWS Amazon SageMaker Python SDK » ✕
  1. CVE-2026-112408 8.1 Élevée

    AWS Amazon SageMaker Python SDK

    Missing verification of source of a communication channel in the default_bucket() function in Amazon SageMaker Python SDK V3 before 3.10.0 and V2 before 2.257.3 might allow remote actors to achieve code execution in the target SageMaker execution environment and obtain IAM credentials via pre-creation of a predictably named S3 bucket that the SDK uses without ownership validation. To remediate this issue, users should upgrade to Amazon SageMaker Python SDK 3.10.0 (V3) or 2.257.3 (V2).

  2. CVE-2026-110248 5.3 Moyenne

    AWS SageMaker Python SDK

    Insertion of sensitive information into log files in the git_utils[.]py component in Amazon SageMaker Python SDK V3 before 3.10.0 and V2 before 2.257.3 might allow an authenticated remote user to obtain plaintext repository credentials from CloudWatch Logs when a git clone operation fails, because the runclone_command() function does not redact credentials from subprocess error output. To remediate this issue, users should upgrade to Amazon SageMaker Python SDK V3 3.10.0 or V2 2.257.3.

  3. CVE-2026-83551 7.2 Élevée

    AWS sagemaker-python-sdk

    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.

  4. CVE-2026-8597 7.2 Élevée

    AWS 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 in S3 with a specially crafted pickle payload that is deserialized without verification. This issue requires a remote authenticated actor with S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any Triton models previously created with ModelBuilder using the updated SDK.

  5. CVE-2026-8596 7.2 Élevée

    AWS Amazon SageMaker Python SDK

    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 valid integrity signatures for specially crafted model artifacts, achieving code execution in inference containers. This issue requires a remote authenticated actor with permissions to call SageMaker describe APIs and S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any models previously created with ModelBuilder using the updated SDK.