CVE-2026-115921 json
ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute
published 2026-10-26 13 d ago modified 2026-10-31 9 d ago also GHSA-m4pr-6v3c-6fgr , EUVD-2026-110046
- cvss
- 6.2
- version 3.1, CNA
- cisa kev
- Not listed
- not in CISA's catalog
- epss
- 0.1%
- EPSS 0.1% chance of exploitation in 30 days, percentile 2%
- public exploits
- 0
- none known
Summary
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.4.0 until 1.22.0, ScanInferenceFunction, ScanInferenceFunction_opset8, and ScanInferenceFunction_opset9 do not safely validate the required num_scan_inputs attribute. A missing attribute is dereferenced as a null pointer, while a negative value is converted to size_t and can reach an exceptional oversized allocation path. An untrusted model can therefore terminate or disrupt shape inference, including a negative-value model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.
Patch / fix
- pypi onnx 1.22.0
- github.com/onnx/onnx@dd6bc92 commit
- github.com/onnx/onnx#7916 pull request
- github.com/onnx/onnx/releases/tag/v1.22.0 release
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-2026-115921 updated cvss 6.2
onnx: onnx: Denial of Service via improper attribute validation in Scan shape inference
-
Red Hat OpenShift AI (RHOAI) rhoai/odh-mlserver-rhel9, rhoai/odh-mlserver-cuda-rhel9, rhoai/odh-openvino-model-server-rhel9, rhoai/odh-pipeline-runtime-pytorch-cuda-py312-rhel9, rhoai/odh-pipeline-runtime-pytorch-rocm-py312-rhel9, rhoai/odh-workbench-jupyter-pytorch-cuda-py312-rhel9, +11 moreaffected: no fix available “Fix deferred”
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
- no
- Technical impact
- partial
- Assessed
- 9 d ago
Exploit prediction
0.13% chance of exploitation in the next 30 days, higher than 2% of all scored CVEs (FIRST EPSS, 2026-11-08).
CVSS scores
| assigned by | version | score | vector |
|---|---|---|---|
| CNA | 3.1 | 6.2 | CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
| GitHub | 3.1 | 6.2 | CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H |
Affected packages
| ecosystem | package | affected | fixed in |
|---|---|---|---|
| pypi | onnx | >=1.4.0, <1.22.0 |
1.22.0 |
Affected products
- onnx onnx
Classification
References
-
github.com
/onnx/onnx/pull/7916
web
-
github.com
/onnx/onnx/commit/dd6bc92ea39fd2274fd671f0734b0b8b558356f5
web
-
github.com
/onnx/onnx/security/advisories/GHSA-m4pr-6v3c-6fgr
web
-
github.com
/onnx/onnx/releases/tag/v1.22.0
web
-
nvd.nist.gov
/vuln/detail/CVE-2026-115921
advisory
-
github.com
/onnx/onnx
package
Sources
- CVE List CVE-2026-115921
- GitHub Advisory GHSA-m4pr-6v3c-6fgr
- NVD CVE-2026-115921
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