Insertion of Sensitive Information Into Sent Data Affecting sagemaker package, versions [,2.256.0)[3.0,3.2.0)
Threat Intelligence
The probability is the direct output of the EPSS model, and conveys an overall sense of the threat of exploitation in the wild. The percentile measures the EPSS probability relative to all known EPSS scores. Note: This data is updated daily, relying on the latest available EPSS model version. Check out the EPSS documentation for more details.
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Test your applications- Snyk IDSNYK-PYTHON-SAGEMAKER-15182664
- published12 Feb 2026
- disclosed2 Feb 2026
- creditUnknown
Introduced: 2 Feb 2026
CVE-2026-1777 (opens in a new tab)How to fix?
Upgrade sagemaker to version 2.256.0, 3.2.0 or higher.
Overview
sagemaker is an Open source library for training and deploying models on Amazon SageMaker.
Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data via the storage of HMAC keys and disclosure through the DescribeTrainingJob API. An attacker can extract secret keys from environment variables to insert in malicious serialized payloads by leveraging API permissions. When combined with write access to output locations, this can result in arbitrary code execution, unauthorized access to sensitive data, and the compromise of adjacent services or data in shared environments.
Note: In multi-tenant environments, with shared S3 buckets, a disclosed HMAC key could act as a pivot point to perform actions against other users' remote function workloads.
Workaround
This vulnerability can be mitigated by adding the private Certificate Authority (CA) certificate to the container image when using self-signed certificates for internal model downloads.