CVE-2026-34445
Last modified
CVE-2026-34445 is a high-severity vulnerability rated 8.6/10 on the CVSS scale. Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. EPSS estimates a 0.29% chance of exploitation in the next 30 days.
Description
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to version 1.21.0, the ExternalDataInfo class in ONNX was using Python’s setattr() function to load metadata (like file paths or data lengths) directly from an ONNX model file. It didn’t check if the "keys" in the file were valid. Due to this, an attacker could craft a malicious model that overwrites internal object properties. This issue has been patched in version 1.21.0.
Metrics
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
Weakness Enumeration
Affected Software
| Vendor | Product | Versions |
|---|---|---|
| Linuxfoundation | Onnx | < 1.21.0 |
References
- https://github.com/onnx/onnx/pull/7751Issue Tracking, Patch
- https://github.com/onnx/onnx/security/advisories/GHSA-538c-55jv-c5g9Patch, Vendor Advisory
Timeline
- Published
- Last Modified
- Status
- Analyzed
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How Strix Helps
- How Strix found a critical auth bypass in etcdStrix autonomously discovered a critical authentication bypass in etcd, later designated CVE-2026-33413.
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