CVE-2026-1777: Sagemaker SageMaker Python SDK Has Exposed Vulnerability

HIGH
Advisory Identifier: GHSA-rjrp-m2jw-pv9c
CVSS 7.2
CWE-319 CWE-295 CWE-201
Published
Advisory Summary

CVE-2026-1777 is a HIGH (CVSS 7.2) sagemaker python sdk has exposed vulnerability (CWE-319: Cleartext Transmission of Sensitive Information) affecting Sagemaker libraries in the PyPI ecosystem. The issue involves sagemaker python sdk has exposed hmac. Remediation is available by upgrading affected packages to version 3.2.0, 2.256.0.

CVE-2026-1777 at a Glance

CVE Identifier CVE-2026-1777
GHSA Identifier GHSA-rjrp-m2jw-pv9c
Severity HIGH
CVSS v3.1 Base Score 7.2
CWE Classification CWE-319: Cleartext Transmission of Sensitive Information
Affected Product Sagemaker
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.2

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required High (PR:H)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2026-1777

To remediate this vulnerability, upgrade all affected Sagemaker dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

sagemaker fixed: 3.2.0
pip install sagemaker>=3.2.0
sagemaker fixed: 2.256.0
pip install sagemaker>=2.256.0
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show sagemaker

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2026-1777, inspect your installed packages using pip:

pip show sagemaker

Analyze the terminal output to locate any version of Sagemaker in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 3.2.0), your application is affected.

Note: The pip show sagemaker command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-319: Cleartext Transmission of Sensitive Information, where the product transmits sensitive or security-critical data in cleartext in a communication channel that can be sniffed by unauthorized actors. In Sagemaker, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Summary SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. An issue where the HMAC secret key is stored in environment variables and disclosed via the DescribeTrainingJob API has been identified. ### Impact - Function and Payload Tampering: Attackers with DescribeTrainingJob permissions may extract HMAC secret keys and forge serialized function payloads stored in S3. These tampered payloads would be processed and executed without triggering integrity validation errors, enabling unintended code substitution. - Arbitrary Code Execution in the Training Environment: An third party with both DescribeTrainingJob permissions and write access to the job's S3 output location can extract the HMAC key, craft inappropriate Python objects, and achieve remote code execution in the client's Python process when the victim retrieves remote function results. - Data and Credentials Handling: Arbitrary remote code execution may interact with sensitive data, model artifacts, environment variables, and potentially AWS metadata. - Cross-Tenant or Shared Environment Risks: In multi-tenant, shared S3 bucket, a disclosed HMAC key could act as a pivot point to perform inappropriate actions against other users' remote function workloads. This could leverage the IAM permissions, shared S3 buckets, or VPC resources to compromise adjacent services or data. ### Impacted versions - SageMaker Python SDK v3 < v3.2.0 - SageMaker Python SDK v2 < v2.256.0 ### Patches This issue has been addressed in SageMaker Python SDK version [v3.2.0](https://github.com/aws/sagemaker-python-sdk/tree/22d30f577a6139431a1fb9154b7b88a0e2a1ace6) and [v2.256.0](https://github.com/aws/sagemaker-python-sdk/tree/a140cfcd12abfee10254cb4dea3bb10758e4321c). Upgrading to the latest version immediately and ensuring any forked or derivative code is patched to incorporate the new fixes is recommended. ### Workarounds Customers using self-signed certificates for internal model downloads should add their private Certificate Authority (CA) certificate to the container image rather than relying on the SDK’s previous insecure configuration. This opt-in approach maintains security while accommodating internal trusted domains. ### Resources If there are any questions or comments about this advisory, contact AWS Security via the [vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting) or directly via email to [aws-security@amazon.com](mailto:aws-security@amazon.com). Please do not create a public GitHub issue.

CVE-2026-1777 Affected Sagemaker Versions

2 component(s)
Fixed Versions:
3.2.02.256.0
Product / Package Ecosystem Affected Versions Fixed Version
sagemaker
PyPI
≥ 3.0
< 3.2.0
3.2.0
sagemaker
PyPI
< 2.256.0
2.256.0

References

Frequently Asked Questions

What is CVE-2026-1777?
CVE-2026-1777 is a security vulnerability in Sagemaker involving SageMaker Python SDK has Exposed HMAC under CWE-319: Cleartext Transmission of Sensitive Information.
Which Sagemaker versions are affected?
Affected versions include releases prior to 3.2.0, 2.256.0 across affected packages: sagemaker.
What version fixes CVE-2026-1777?
Upgrading to 3.2.0, 2.256.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is sagemaker affected?
Yes, sagemaker is affected in releases prior to 3.2.0, 2.256.0. Upgrade your dependency to 3.2.0, 2.256.0 or later.
What is the CVSS score of CVE-2026-1777?
CVE-2026-1777 has a CVSS v3.1 base score of 7.2 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2026-1777?
CVE-2026-1777 is classified under CWE-319: Cleartext Transmission of Sensitive Information (The product transmits sensitive or security-critical data in cleartext in a communication channel that can be sniffed by unauthorized actors.).
How can I check PyPI dependencies for CVE-2026-1777?
Run the dependency tree command: 'pip show sagemaker'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-rjrp-m2jw-pv9c",
  "modified" : "2026-02-03T19:01:11Z",
  "published" : "2026-02-02T23:33:32Z",
  "aliases" : [ "CVE-2026-1777" ],
  "summary" : "SageMaker Python SDK has Exposed HMAC",
  "details" : "### Summary\n\nSageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. An issue where the HMAC secret key is stored in environment variables and disclosed via the DescribeTrainingJob API has been identified.\n\n### Impact\n\n- Function and Payload Tampering: Attackers with DescribeTrainingJob permissions may extract HMAC secret keys and forge serialized function payloads stored in S3. These tampered payloads would be processed and executed without triggering integrity validation errors, enabling unintended code substitution.\n- Arbitrary Code Execution in the Training Environment: An third party with both DescribeTrainingJob permissions and write access to the job's S3 output location can extract the HMAC key, craft inappropriate Python objects, and achieve remote code execution in the client's Python process when the victim retrieves remote function results.\n- Data and Credentials Handling: Arbitrary remote code execution may interact with sensitive data, model artifacts, environment variables, and potentially AWS metadata.\n- Cross-Tenant or Shared Environment Risks: In multi-tenant, shared S3 bucket, a disclosed HMAC key could act as a pivot point to perform inappropriate actions against other users' remote function workloads. This could leverage the IAM permissions, shared S3 buckets, or VPC resources to compromise adjacent services or data.\n\n### Impacted versions\n\n- SageMaker Python SDK v3 < v3.2.0\n- SageMaker Python SDK v2 < v2.256.0\n\n### Patches\nThis issue has been addressed in SageMaker Python SDK version [v3.2.0](https://github.com/aws/sagemaker-python-sdk/tree/22d30f577a6139431a1fb9154b7b88a0e2a1ace6) and [v2.256.0](https://github.com/aws/sagemaker-python-sdk/tree/a140cfcd12abfee10254cb4dea3bb10758e4321c). Upgrading to the latest version immediately and ensuring any forked or derivative code is patched to incorporate the new fixes is recommended.\n\n### Workarounds\nCustomers using self-signed certificates for internal model downloads should add their private Certificate Authority (CA) certificate to the container image rather than relying on the SDK’s previous insecure configuration. This opt-in approach maintains security while accommodating internal trusted domains.\n\n### Resources\nIf there are any questions or comments about this advisory, contact AWS Security via the [vulnerability reporting page](https://aws.amazon.com/security/vulnerability-reporting) or directly via email to [aws-security@amazon.com](mailto:aws-security@amazon.com). Please do not create a public GitHub issue.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:H"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:H/VI:H/VA:H/SC:N/SI:N/SA:N"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "sagemaker"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "3.0"
      }, {
        "fixed" : "3.2.0"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "sagemaker"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.256.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/aws/sagemaker-python-sdk/security/advisories/GHSA-rjrp-m2jw-pv9c"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2026-1777"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/aws/sagemaker-python-sdk/commit/708c7b2f4135ecaec55973d098f3dbe98b657933"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/aws/sagemaker-python-sdk/commit/fb0d789db4fd5fecde5509963939369f4c7ce63b"
  }, {
    "type" : "WEB",
    "url" : "https://aws.amazon.com/security/security-bulletins/2026-004-AWS"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/aws/sagemaker-python-sdk"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/aws/sagemaker-python-sdk/releases/tag/v2.256.0"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/aws/sagemaker-python-sdk/releases/tag/v3.2.0"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-201", "CWE-295", "CWE-319" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-02-02T23:33:32Z",
    "nvd_published_at" : "2026-02-02T23:16:04Z"
  }
}