CVE-2026-34445 (GCVE-0-2026-34445)

Vulnerability from cvelistv5 – Published: 2026-04-01 17:30 – Updated: 2026-04-01 18:00
VLAI?
Title
ONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings.
Summary
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.
Severity ?
8.6 (High)
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
CWE
  • CWE-20 - Improper Input Validation
  • CWE-400 - Uncontrolled Resource Consumption
  • CWE-915 - Improperly Controlled Modification of Dynamically-Determined Object Attributes
Assigner
References
Impacted products
Vendor Product Version
onnx onnx Affected: < 1.21.0
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  • Seen: The vulnerability was mentioned, discussed, or observed by the user.
  • Confirmed: The vulnerability has been validated from an analyst's perspective.
  • Published Proof of Concept: A public proof of concept is available for this vulnerability.
  • Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
  • Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
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  • Not confirmed: The user expressed doubt about the validity of the vulnerability.
  • Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.



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