CVE-2026-8597: Amazon SageMaker Python SDK cleartext storage of HMAC key in ModelBuilder

CVE-2026-8597 · Severity: high · CVSS 7.2 · Published 2026-05-14

The Amazon SageMaker Python SDK is a library used to build, train, and deploy machine learning models on AWS. A security issue was identified where sensitive signing keys used to verify the integrity of model files were stored in plain text within container environment variables. An attacker with specific administrative permissions could retrieve these keys to bypass security checks and run unauthorized code within the machine learning environment, potentially gaining access to sensitive data or AWS resources.

Technologies: Amazon AWS, Amazon SageMaker Python SDK, sagemaker (PyPI). Vendors: Amazon, PyPI.

Quick answers

Is CVE-2026-8597 exploited in the wild?
No. Junglewise Threat Intelligence has no report of CVE-2026-8597 being exploited in the wild.
How severe is CVE-2026-8597?
High severity, with a CVSS score of 7.2, published 14 May 2026.
Which products and versions are affected?
Amazon SageMaker Python SDK >= v2.199.0, <= v2.257.1; >= v3.0.0, <= v3.7.1; sagemaker (PyPI) ECOSYSTEM:introduced=2.199.0,fixed=2.257.2, ECOSYSTEM:introduced=2.199.0,fixed=2.257.2,introduced=3.0.0,fixed=3.8.0.
Is there a fix for CVE-2026-8597?
Yes. sagemaker (PyPI): upgrade to 2.257.2, 3.8.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.
How is CVE-2026-8597 attacked?
It is attacked over the network, in a software library.
Am I affected by CVE-2026-8597?
Check whether you run Amazon AWS, Amazon SageMaker Python SDK or sagemaker (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

How to fix

  • sagemaker (PyPI): upgrade to 2.257.2, 3.8.0 or later
    pip install "sagemaker>=3.8.0"

Technical details

The vulnerability (CWE-312) exists in the ModelBuilder/Serve component of the Amazon SageMaker Python SDK. When deploying models using servers like TorchServe or TensorFlow Serving, the SDK generates an HMAC secret key for artifact integrity verification but stores it in the SAGEMAKER_SERVE_SECRET_KEY environment variable. This variable is exposed in plaintext via SageMaker 'describe' APIs (e.g., DescribeModel). An authenticated attacker with permissions to call these APIs and write access to the S3 model artifact path can extract the key, forge signatures for malicious artifacts, and achieve code execution within the inference container. The issue is resolved in versions 2.257.2 and 3.8.0; however, existing models must be rebuilt to rotate the compromised keys.

Affected products

  • Amazon SageMaker Python SDK >= 2.199.0, <= 2.257.1; >= 3.0.0, <= 3.7.1

Identifiers

  • CVE-2026-8597
  • CVE-2026-8596
  • GHSA-7hh5-prp2-mfh5
  • PYSEC-2026-3059

Timeline

  • 2026-05-14: disclosed
  • 2026-05-14: patched: Versions 2.257.2 and 3.8.0 released
  • 2026-05-21: advisory

References

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