How severe is CVE-2026-1777?

No CVSS score has been assigned to CVE-2026-1777 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by CVE-2026-1777?

CVE-2026-1777 affects the following packages: sagemaker (PyPI), sagemaker (PyPI). Ecosystems affected: PyPI.

How do I fix CVE-2026-1777?

Update sagemaker to 3.2.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-1777 is resolved across your whole dependency graph.

How do I detect CVE-2026-1777 in my PyPI dependencies?

Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for sagemaker, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

How do I mitigate CVE-2026-1777 if there is no patch (or I can't update yet)?

If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Is CVE-2026-1777 actively exploited in the wild?

No public exploit code has been indexed for CVE-2026-1777 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for CVE-2026-1777?

CVE-2026-1777 has an EPSS (Exploit Prediction Scoring System) score of 0.5%, placing it in the 44th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is CVE-2026-1777?

CVE-2026-1777 is classified as CWE-319 (CWE-319). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was CVE-2026-1777 published, and has it been updated?

CVE-2026-1777 was published on February 2, 2026 and was last updated on October 28, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

Not in CISA KEV

CVE-2026-1777 — sagemaker

Fix: aws/sagemaker-python-sdk@708c7b2

CVE-2026-1777 is a CWE-319 vulnerability in sagemaker. A fix is available for sagemaker — see the affected versions and patch details below.

Cleartext transmission of sensitive materials in aws/sagemaker-python-sdk

Also known asGHSA-rjrp-m2jw-pv9cPYSEC-2026-1888

Published

Feb 2, 2026

Updated

Oct 28, 2026

Affected

2 pkgs

Patched

2 / 2

Exploits

None indexed

Exploitation data as of Nov 3, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

A successful exploit gives an attacker total control of the affected component, not partial access.
CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-1777.

EPSS Exploitation Probability

via FIRST.org ↗

0.5%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs44th percentile — riskier than 44% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

2 pkgs affected

🐍sagemaker🐍sagemaker

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

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 and v2.256.0. 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 or directly via email to [email protected]. Please do not create a public GitHub issue.

Affected Packages

2 total 2 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`sagemaker`	≥ 3.0&&< 3.2.0	3.2.0`pip install --upgrade 'sagemaker==3.2.0'`
🐍PyPI	`sagemaker`	all versions	2.256.0`pip install --upgrade 'sagemaker==2.256.0'`

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for sagemaker, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update sagemaker to 3.2.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-1777 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

Frequently Asked Questions

### 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

O3 Security · Impact-Aware SCA

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