CVE-2026-28500 - Vulnerability Analysis

Overview

Open Neural Network Exchange (ONNX) <= 1.20.1 contains a security control bypass caused by improper logic in repository trust verification in onnx.hub.load(), letting attackers perform zero-interaction supply-chain attacks and exfiltrate sensitive files when loading models with silent=True.

Severity & Score

Impact

Attackers can silently exfiltrate sensitive files from victim machines during model loading, leading to data theft and supply-chain compromise.

Mitigation

No patched versions available; monitor for updates and avoid using silent=True with untrusted models.

References

• https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md
• https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m

Social Media Activity(1 post)

/r/netsec

@_r_netsec

Mar 21, 2026

ONNX Hub silent=True suppresses all trust verification, enabling supply chain attacks on ML model loading (CVE-2026-28500, CVSS 9.1, no patch available) https://raxe.ai/labs/advisories/RAXE-2026-039

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Related Resources

• Vulnerability Intelligence Dashboard
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