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National Vulnerability Database

National Vulnerability Database

NVD

National Vulnerability Database
  1. Vulnerabilities

CVE-2026-28500 Detail

Description

Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. In versions up to and including 1.20.1, a security control bypass exists in onnx.hub.load() due to improper logic in the repository trust verification mechanism. While the function is designed to warn users when loading models from non-official sources, the use of the silent=True parameter completely suppresses all security warnings and confirmation prompts. This vulnerability transforms a standard model-loading function into a vector for Zero-Interaction Supply-Chain Attacks. When chained with file-system vulnerabilities, an attacker can silently exfiltrate sensitive files (SSH keys, cloud credentials) from the victim's machine the moment the model is loaded. As of time of publication, no known patched versions are available.


Metrics

 
NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 4.0 Severity and Vector Strings:

NIST CVSS score
NIST: NVD
N/A
NVD assessment not yet provided.

References to Advisories, Solutions, and Tools

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URL Source(s) Tag(s)
https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md CISA-ADP, GitHub, Inc. Patch 
https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m GitHub, Inc. Vendor Advisory 

Weakness Enumeration

CWE-ID CWE Name Source
CWE-345 Insufficient Verification of Data Authenticity GitHub, Inc.  
CWE-494 Download of Code Without Integrity Check GitHub, Inc.  
CWE-693 Protection Mechanism Failure GitHub, Inc.  

Known Affected Software Configurations Switch to CPE 2.2

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Change History

3 change records found show changes

Quick Info

CVE Dictionary Entry:
CVE-2026-28500
NVD Published Date:
03/17/2026
NVD Last Modified:
03/18/2026
Source:
GitHub, Inc.