CVE-2026-28500 — onnx
HIGHCVE-2026-28500 is a high-severity (CVSS 8.6) CWE-345 vulnerability in onnx. A fix is available for onnx — see the affected versions and patch details below.
ONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain Attack
Exploitation Status
Proof-of-concept exploit code exists
- CISA’s SSVC triage found public proof-of-concept exploit code for this CVE, though no confirmed active exploitation.
- CISA assesses this as automatable — exploitation doesn’t require manual, per-target effort, which raises the odds of mass scanning and opportunistic attacks.
Exploitation and automatability from CISA’s SSVC triage for CVE-2026-28500.
EPSS Exploitation Probability
Probability of exploitation in the next 30 days, from FIRST.org EPSS.
How urgent is this, really
Where this sits among everything scored
Real-World Exposure
onnxReal-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.
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.
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
Affected Packages
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | onnx | all versions | 1.21.0rc1pip install --upgrade 'onnx==1.21.0rc1' |
Affected Products
onnxlinuxfoundationDetection & mitigation playbook
Open-source dependencyDetect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for onnx, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update onnx to 1.21.0rc1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-28500 is resolved across your whole dependency graph.
Workarounds
If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.
Fixing This On Your OS
If you run this on a Linux distribution, patch through your package manager against the distro's own security advisory below — it tracks the exact backported fix for your release, which can ship on a different timeline (and sometimes a different severity) than the upstream project.
Mitigation for this issue is either not available or the currently available options do not meet the Red Hat Product Security criteria comprising ease of use and deployment, applicability to widespread installation base or stability.Source: Red Hat security advisory for CVE-2026-28500 (CC BY 4.0)
| Product | Fixed in | Advisory |
|---|---|---|
| Red Hat OpenShift AI 2.25 | rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1780078312 | RHSA-2026:24977 |
| Red Hat OpenShift AI 3.3 | rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9:1790345193 | RHSA-2026:73987 |
Frequently Asked Questions
Is CVE-2026-28500 in your dependencies?
Find it across PyPI, including transitive dependencies.