CVE-2026-28500 PUBLISHED

ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack

Assigner: GitHub_M
Reserved: 27.02.2026 Published: 18.03.2026 Updated: 18.03.2026

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

CVSS Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CVSS Score: 8.6

Product Status

Vendor onnx
Product onnx
Versions
  • Version <= 1.20.1 is affected

References

Problem Types

  • CWE-345: Insufficient Verification of Data Authenticity CWE
  • CWE-494: Download of Code Without Integrity Check CWE
  • CWE-693: Protection Mechanism Failure CWE