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cpe:2.3:a:amazon_sagemaker_python_sdk:aws:*:*:*:*:*:*:*:*
part: a version: * update: *
| Vendor | Amazon Sagemaker Python Sdk (1d745020-53f5-5d90-a77a-c948734b48fd) |
|---|---|
| Product | Aws (2ed9b980-54a4-5f87-bc76-d2623af717ce) |
| Edition | * |
| Language | * |
| Software edition | * |
| Target software | * |
| Target hardware | * |
| Other | * |
| Notes | Imported from gcve-enriched-dumps CVE data |
PURL mappings
| PURL | Source | Last updated |
|---|---|---|
| No PURL mappings for this CPE yet. | ||
Vulnerability references
| Identifier | cpeApplicability | Submitted | db.gcve.eu details | Rationale |
|---|---|---|---|---|
CVE:CVE-2026-8597 |
vulnerable | 2026-06-08 08:08:58.475849 |
Missing integrity verification in Triton inference handler in Amazon SageMaker Python SDK
HIGH (7.2)
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.
Published: 2026-05-14T19:37:02.187Z
Updated: 2026-05-16T03:56:23.152Z |
Imported from gcve-enriched-dumps CVE data |
CVE:CVE-2026-8596 |
vulnerable | 2026-06-08 08:08:58.475428 |
Cleartext storage of HMAC signing key in Amazon SageMaker Python SDK ModelBuilder/Serve path
HIGH (7.2)
Cleartext storage of sensitive information in the ModelBuilder/Serve component in Amazon SageMaker Python SDK before v2.257.2 and v3 before v3.8.0 might allow a remote authenticated actor to extract the HMAC signing key from SageMaker API responses and forge valid integrity signatures for specially crafted model artifacts, achieving code execution in inference containers. This issue requires a remote authenticated actor with permissions to call SageMaker describe APIs and 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 models previously created with ModelBuilder using the updated SDK.
Published: 2026-05-14T19:35:51.421Z
Updated: 2026-05-16T03:56:21.927Z |
Imported from gcve-enriched-dumps CVE data |
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