CVE-2026-28500 (GCVE-0-2026-28500)

Vulnerability from cvelistv5 – Published: 2026-03-18 01:15 – Updated: 2026-03-18 14:08
VLAI?
Title
ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack
Summary
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.
Severity ?
8.6 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
CWE
  • CWE-345 - Insufficient Verification of Data Authenticity
  • CWE-494 - Download of Code Without Integrity Check
  • CWE-693 - Protection Mechanism Failure
Assigner
References
Impacted products
Vendor Product Version
onnx onnx Affected: <= 1.20.1
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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
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  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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