CVE-2026-28500
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.
Predictions
Heuristic predictions, AS-IS, for prioritization only.
Mitigations
No mitigations published for this CVE yet.
The vendor-content worker queues fetches as references arrive (check back in a few minutes). Or — if you've already worked around this in production — publish your fix to the community-verified tier.
✚ Propose a mitigation on Community → Mitigations published via the community go through AI scoring + 2 human reviewers + 7-day silent objection window before landing here withsource_tier=community-verified.
OS impact
Debian Affected 5 releases
| Version | Status | Fixed in |
|---|---|---|
| trixie | Affected | — |
| sid | Affected | — |
| forky | Affected | — |
| bullseye | Affected | — |
| bookworm | Affected | — |
References
Community-verified mitigations for this CVE will appear above when contributors publish them.
Verify integrity in audit chain (admin only). AS-IS.