CVE-2026-28500

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

State
Published
Severity
8.6 High
Published
Mar 18, 2026
Updated
Jul 15, 2026
Reserved
Feb 27, 2026

Read the record on cve.org

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.

Scores

CVSSScoreVectorSource
3.18.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:NGitHub_M
3.18.6 HighCVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:Nredhat-SADP

Weaknesses

  • CWE-345 Insufficient Verification of Data Authenticity
  • CWE-494 Download of Code Without Integrity Check
  • CWE-693 Protection Mechanism Failure
  • CWE-829 Inclusion of Functionality from Untrusted Control Sphere

Affected Products

ProductVersions
onnxonnx
  • <= 1.20.1Affected

References

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