MediumVulnerability

CVE-2026-1778: Amazon SageMaker Python SDK TLS certificate verification disabled

Source: NVD(opens in a new tab)
Identifier: CVE-2026-1778
Published: February 2, 2026
Record updated: October 9, 2026

Affected: sagemaker >= 3.0, < 3.1.1, fixed in 3.1.1, released December 11, 2025, 54 days before disclosure
sagemaker < 2.256.0, fixed in 2.256.0, released January 8, 2026, 26 days before disclosure
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.3%

Summary

CVE-2026-1778 affects the Amazon SageMaker Python SDK before v3.1.1 or v2.256.0. When a Triton Python model is imported, the SDK disables TLS certificate verification for HTTPS connections the service makes, so requests with invalid and self-signed certificates succeed. The issue is classified as CWE-295 (Improper Certificate Validation) with a CVSS 4.0 score of 8.2 (HIGH) from the CNA AMZN, and NVD had not yet provided an assessment.

Mitigation

Fixed in v3.1.1 and v2.256.0 of the Amazon SageMaker Python SDK.

Details

Scores and exploitation

CVSS score: 5.9(medium)
Patch available: Yes
EPSS: 0.3%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-295

Affected

Packages: sagemaker@>= 3.0, < 3.1.1 (fixed: 3.1.1)
sagemaker@< 2.256.0 (fixed: 2.256.0)
Vendors: Amazon

Classification

Attack type: Other
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Integrity
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2026-1778

First tracked: February 15, 2026 at 08:45 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 90% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

sagemakerPyPIReaches an LLM package through dependencies · 3 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

Related items