Bug 2448518 (CVE-2026-28500)

Summary: CVE-2026-28500 onnx: ONNX: Untrusted Model Repository Warnings Suppressed
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security DevOps Team <prodsec-dev>
Status: NEW --- QA Contact:
Severity: high Docs Contact:
Priority: high    
Version: unspecifiedCC: jkoehler, lphiri
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A flaw was found in Open Neural Network Exchange (ONNX), an open standard for machine learning interoperability. A security control bypass exists in the `onnx.hub.load()` function due to improper logic in its repository trust verification. An attacker can exploit this by providing a malicious model, which, when loaded with the `silent=True` parameter, suppresses all security warnings. This vulnerability transforms a standard model-loading function into a vector for Zero-Interaction Supply-Chain Attacks.
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oVirt Team: --- RHEL 7.3 requirements from Atomic Host:
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Bug Depends On: 2448796, 2448797    
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Description OSIDB Bzimport 2026-03-18 02:02:00 UTC 
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.