CVE-2026-8597: Amazon SageMaker Python SDK · Improper Validation of Integrity Check Value
Affects Amazon SageMaker Python SDKSource CVE Database V5
Not known to be exploited · CVSS 7.2 High : upgrade to 3.8.0 or 2.257.2 soon.
Data as of 30 Oct 2026, 11:52 UTC
- EPSS
- 0.5% chance of exploitation in 30 days – higher than 43% of CVEsExploit Prediction Scoring System: the likelihood attackers will use this flaw soon.
- Patch
- Available – fixed in 3.8.0, 2.257.2
CVSS:3.1/AV:N/AC:L/PR:H/UI:N/S:U/C:H/I:H/A:HExploitation evidence
Disclosed: evidence found.
CVE published 14 May 2026
Detectable: no evidence on record.
No public nuclei template indexed
Weaponized: no evidence on record.
No public exploit code indexed in Metasploit or Exploit-DB
Exploited in the wildExploited: no evidence on record.
Not in CISA KEV and no source reports exploitation
Observed by OffSeq MirageSeen by Mirage: no evidence on record.
No attack traffic recorded by OffSeq Mirage sensors
A missing step is not evidence of safety. Sources: cve.org (opens in a new tab), the Metasploit, Exploit-DB and nuclei-templates index as of 30 Oct 2026.
What to do
Upgrade sagemaker to 3.8.0 or 2.257.2.
Affected software
| Product | Affected | Fixed in |
|---|---|---|
| AWSAmazon SageMaker Python SDK | Affected
| Fixed in– |
PyPIsagemakerpkg:pypi/sagemakerOther threats | Affected
| Fixed in
|
Check your own hosts for these packages with threat-finder (opens in a new tab), our free open-source scanner.
AI-suggested
AWS recommends upgrading the Amazon SageMaker Python SDK to version v2.257.2 or v3.8.0 or later. Additionally, any Triton models previously created with ModelBuilder using affected SDK versions should be rebuilt using the updated SDK to ensure the vulnerability is fully mitigated. Since this is a cloud service, AWS manages the underlying infrastructure, but customers must update their SDK and models accordingly. Patch status is confirmed as available via vendor advisory: https://aws.amazon.com/security/security-bulletins/2026-031-aws/
Description
Missing integrity verification in the Triton inference handler in Amazon SageMaker Python SDK v2 before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to achieve code execution in inference containers via replacement of model artifacts in S3 with a specially crafted pickle payload that is deserialized without verification. This issue requires a remote authenticated actor with S3 write access to the model artifact path. To remediate this issue, we recommend upgrading to Amazon SageMaker Python SDK v2.257.2 or v3.8.0 and rebuild any Triton models previously created with ModelBuilder using the updated SDK.
References
- github.com/aws/sagemaker-python-sdk/releases/tag/v2.257.2 (opens in a new tab)
- github.com/aws/sagemaker-python-sdk/releases/tag/v3.8.0 (opens in a new tab)
- aws.amazon.com/security/security-bulletins/2026-031-aws/ (opens in a new tab)
- github.com/aws/sagemaker-python-sdk/security/advisories/GHSA-rq6v-x3j8-7qgf (opens in a new tab)