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Fencer Vulns
high 8.6

CVE-2026-34445 json

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

published 2026-04-01 7 mo ago modified 2026-09-10 1 mo ago also EUVD-2026-17985 , GHSA-538c-55jv-c5g9 , PYSEC-2026-2240

cvss
8.6
version 3.1, CNA
cisa kev
Not listed
not in CISA's catalog
epss
0.3%
EPSS 0.3% chance of exploitation in 30 days, percentile 21%
public exploits
0
none known

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.

Patch / fix

  • pypi onnx 1.21.0
  • linuxfoundation onnx 1.21.0
  • onnx onnx 1.21.0
  • pytorch Azure Linux 3.0 2.2.2-14

azure linux advisories AZL-81989

Azure Linux vulnerability data, Copyright (c) Microsoft Corporation, from https://github.com/microsoft/AzureLinuxVulnerabilityData via OSV, under the MIT licence; changed: normalised to fixed package versions per release. MIT

Vendor advisories

What the vendors themselves say about their products: affected, fixed or not affected, and what to do.

red hat product security vex CVE-2026-34445 updated cvss 7.3

ONNX: ONNX: Denial of Service and potential information disclosure via malicious model metadata

  • Red Hat OpenShift AI (RHOAI) rhoai/odh-openvino-model-server-rhel9
    affected: no fix available
  • Red Hat OpenShift AI 2.25 rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 1787292256, rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 1787652771, rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 1788185436, rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 1788185848, rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 1788185899, rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 1788301844, +8 more
    fixed: vendor fix RHSA-2026:65126
  • Red Hat OpenShift AI 3.3 rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9 1789651383, rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9 1789651379, rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9 1789651387, rhoai/odh-workbench-jupyter-pytorch-rocm-py312-rhel9 1789651385, rhoai/odh-workbench-jupyter-trustyai-cpu-py312-rhel9 1790260954, rhoai/odh-pipeline-runtime-datascience-cpu-py312-rhel9 1790345193, +8 more
    fixed: vendor fix RHSA-2026:73987
  • Red Hat OpenShift AI 2.25 rhoai/odh-rhel9-operator 1788331391, rhoai/odh-vllm-cpu-rhel9 1786712073, rhoai/odh-dashboard-rhel9 1788312226, rhoai/odh-modelmesh-rhel9 1788319539, rhoai/odh-operator-bundle 1788332816, rhoai/odh-vllm-cuda-rhel9 1786710989, +57 more Red Hat OpenShift AI 3.3 rhoai/odh-cli-rhel9 1790070206, rhoai/rhai-cli-rhel9 1790070206, rhoai/odh-mlflow-rhel9 1789653606, rhoai/odh-trainer-rhel9 1790136369, rhoai/odh-maas-api-rhel9 1790131842, rhoai/odh-mlserver-rhel9 1789121365, +63 more
    not affected: vulnerable code not present

Red Hat CSAF VEX © Red Hat, Inc., from https://security.access.redhat.com/data/csaf/v2/vex/; changed: reduced to product statuses and remediations. CC BY 4.0 · csaf

CISA SSVC

Exploitation
none
Automatable
yes
Technical impact
partial
Assessed
7 mo ago

Exploit prediction

0.29% chance of exploitation in the next 30 days, higher than 21% of all scored CVEs (FIRST EPSS, 2026-11-08).

CVSS scores

assigned by version score vector
CNA 3.1 8.6 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
GitHub 3.1 8.6 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H
OSV 3.1 8.6 CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:L/A:H

Affected packages

ecosystem package affected fixed in
pypi onnx
<1.21.0
1.21.0

Affected products

  • onnx onnx

Classification

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

References

Sources

Fencer Vulns keeps one entry per vulnerability: the CVE id wins, then GHSA, and records that alias each other are merged, except that two CVEs always keep separate entries. The same data is available as JSON.

CPEs and fixed versions use Anchore's correction of NVD's data: Added CPE configurations because not yet analyzed by NVD.