GitHub Advisoryadvisory · PyPI
GHSA-hqmj-h5c6-369m ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack
HIGH
Official page ↗
- Aliases
- CVE-2026-28500
- Ecosystem
- PyPI
- Packages
- onnx
- Severity
- High
- CVSS vector
- CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:N/A:N
- Weaknesses
- CWE-345, CWE-494, CWE-693
- Reviewed
- 2026-03-16
Affected packages
• PyPI onnx: < 1.21.0rc1 → fixed in 1.21.0rc1
Description
What's the issue
Passing `silent=True` to `onnx.hub.load()` kills all trust warnings and user prompts. This means a model can be downloaded from any unverified GitHub repo with zero user awareness.
```python
if not _verify_repo_ref(repo) and not silent:
# completely skipped when silent=True
print("The model repo... is not trusted")
if input().lower() != "y":
return None
```
On top of that, the SHA256 integrity check is useless here — it validates against a manifest that lives in the same repo the attacker controls, so the hash will always match.
Impact
Any pipeline using `hub.load()` with `silent=True` and an external repo string is silently loading whatever the repo owner ships. If that model executes arbitrary code on load, the attacker has access to the machine.
Resolved by removing the feature
References
• Write-up
Related
Alias · CVE (1)
- CVE-2026-28500 Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. vulnerability
References
- https://github.com/onnx/onnx/security/advisories/GHSA-hqmj-h5c6-369m web
- https://nvd.nist.gov/vuln/detail/CVE-2026-28500 advisory
- https://github.com/ZeroXJacks/CVEs/blob/main/2026/CVE-2026-28500.md web
- https://github.com/onnx/onnx package
- https://github.com/pypa/advisory-database/tree/main/vulns/onnx/PYSEC-2026-103.yaml web