GHSA-rjrp-m2jw-pv9c is a high-severity (CVSS 7.2) CWE-319 vulnerability in sagemaker. A fix is available for sagemaker — see the affected versions and patch details below.
SageMaker Python SDK has Exposed HMAC
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 GHSA-rjrp-m2jw-pv9c.
EPSS Exploitation Probability
EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.
How urgent is this, really
GHSA-rjrp-m2jw-pv9c plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.
Where this sits among everything scored
Of 377,166 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.
Real-World Exposure
sagemaker🐍sagemakerReal-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
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | sagemaker | ≥ 3.0&&< 3.2.0 | 3.2.0pip install --upgrade 'sagemaker==3.2.0' |
| 🐍PyPI | sagemaker | all versions | 2.256.0pip install --upgrade 'sagemaker==2.256.0' |
Detection & mitigation playbook
Open-source dependencyDetect
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 GHSA-rjrp-m2jw-pv9c 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.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-rjrp-m2jw-pv9c can be triaged on real exposure rather than presence alone.
Tailored to GHSA-rjrp-m2jw-pv9c. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-rjrp-m2jw-pv9c in your dependencies?
O3 Security finds GHSA-rjrp-m2jw-pv9c across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.