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Vulnerability record · CVE-2026-28500 · published 18 March 2026

CVE-2026-28500: Linuxfoundation onnx insufficient verification of data authenticity vulnerability

Linuxfoundation · Onnx

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.

9.1 CVSS 3.1 Critical EPSS 0.31% · top 78.4% CWE-345 · Insufficient verification of data authenticityCWE-494 · Download of code without integrity check
9.1CVSS 3.1 base score
0.31%EPSS exploitation probability, 30 days
NoNot in CISA KEV
1Affected product versions listed by NVD
7References
15 Jul 2026Last modified by NVD

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.

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:N

Affected products

1 vulnerable configurations from NVD's CPE data, grouped by vendor and product.

References

LinkTags
https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md Patch
https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m Vendor Advisory
https://access.redhat.com/errata/RHSA-2026:24977
https://access.redhat.com/security/cve/CVE-2026-28500
https://bugzilla.redhat.com/show_bug.cgi?id=2448518
https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md Patch
https://security.access.redhat.com/data/csaf/v2/vex/2026/cve-2026-28500.json

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Related vulnerabilities

Same products first, then exploited flaws of the same weakness class.

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Source: NIST National Vulnerability Database (record CVE-2026-28500), CISA KEV, FIRST EPSS (scores of 2026-09-26). This page is refreshed as NVD updates the record.