CVE-2026-8597 — sagemaker
CVE-2026-8597 is a CWE-354 vulnerability in sagemaker. A fix is available for sagemaker — see the affected versions and patch details below.
Missing integrity verification in Triton inference handler in Amazon SageMaker Python SDK
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-2026-8597.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
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
Amazon SageMaker Python SDK is an open-source library for training and deploying machine learning models on Amazon SageMaker. An issue exists where, under certain circumstances, the Triton inference handler deserializes model artifacts without performing integrity verification, allowing specially crafted pickle payloads to execute arbitrary code.
Impact
When using ModelBuilder with the Triton inference server, the Triton handler did not perform integrity verification before deserializing model artifacts. A remote authenticated actor with S3 write access to the model artifact path could replace model files with a crafted payload that would execute automatically on the next container lifecycle event, achieving code execution with the SageMaker execution role's IAM permissions.
Impacted versions: >= v2.199.0 AND <= v2.257.1, >= v3.0.0 AND <= v3.7.1
Patches
This issue has been addressed in Amazon SageMaker Python SDK v2.257.2 and v3.8.0. The Triton inference handler now performs integrity verification before deserializing model artifacts. AWS recommend upgrading to the latest version and rebuilding any Triton models previously created with ModelBuilder using the updated SDK. Ensure any forked or derivative code is patched to incorporate the new fixes.
Workarounds
If upgrading is not immediately possible, users should restrict S3 write access to model artifact paths to only trusted principals and monitor for unintended modifications to files in model artifact S3 locations.
References
If there any questions or comments about this advisory, contact AWS Security via 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 | ≥ 2.199.0&&< 2.257.2 | 2.257.2pip install --upgrade 'sagemaker==2.257.2' |
| 🐍PyPI | sagemaker | ≥ 3.0.0&&< 3.8.0 | 3.8.0pip install --upgrade 'sagemaker==3.8.0' |
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 2.257.2 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-8597 is resolved across your whole dependency graph.
Workarounds
Do not deserialise data from untrusted sources: where the format allows it, restrict deserialisation to an explicit allowlist of expected types, and prefer a data-only format (JSON, Protobuf) over one that can reconstruct arbitrary objects until you can upgrade.
Frequently Asked Questions
Is CVE-2026-8597 in your dependencies?
Find it across PyPI, including transitive dependencies.