CVE-2026-34445: high-severity vulnerability in onnx
ONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings.
Published
E-mail alert when it lands in KEV, gets a public PoC or its score goes up.
21Vexday Risk Score
No sign of exploitation. No public exploitation artifact known so far.
ssvc Trackcvss 8.6epss 0.3%
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.
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
Affected products
onnx · onnxRelated CVEs — onnx
In the same product, most dangerous first.
CVE-2024-27318HIGHCVE-2024-27318EPSS 1.2%CVE-2026-27489HIGHONNX: Path Traversal via SymlinkEPSS 0.6%CVE-2024-27319MEDIUMCVE-2024-27319EPSS 0.6%CVE-2026-28500HIGHONNX Untrusted Model Repository Warnings Suppressed by silent=True in onnx.hub.load() — Silent Supply-Chain AttackEPSS 0.3%CVE-2026-34447MEDIUMONNX: External Data Symlink TraversalEPSS 0.3%CVE-2026-44512MEDIUMONNX: Null Pointer Dereference in Upsample Version Converter Adapter (Zero Inputs)EPSS 0.2%