ONNX: Malicious ONNX models can crash servers by exploiting unprotected object settings. (onnx onnx)

CVE-2026-34445
HIGH 8.6

At a glance

Source
NVD
EPSS
EPSS 0.29 % · percentile 22 ()
State
PUBLISHED
Published
Updated
Assigner
GitHub_M
NVD status
Analyzed

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.

Weaknesses (CWE)

  • CWE-20 — Improper Input Validation
  • CWE-400 — Uncontrolled Resource Consumption
  • CWE-915 — Improperly Controlled Modification of Dynamically-Determined Object Attributes

References

Scores

VersionScoreVectorScored by
CVSS 3.1HIGH 8.6CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:HGitHub_M
CVSS 3.1HIGH 8.6CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:HNVD · security-advisories@github.com (Secondary)

Advisories

European references

CERT-FR advisories

Affected configurations (NVD CPE)

Affected products

ProductVersions
onnx · onnxaffected < 1.21.0

Sources

SourceLicence
CVE List (CVEProject cvelistV5)CVE Program Terms of Use
EPSS (FIRST.org)FIRST — attribution requested
ENISA EUVDENISA — reproduction authorised, source acknowledged
CERT-FR (ANSSI)Licence Ouverte / Etalab 2.0
NVD (NIST) via fkie-cad/nvd-json-data-feedsPublic domain — this product uses data from the NVD API but is not endorsed or certified by the NVD