Is CVE-2026-115921 exploited in the wild?

No. Junglewise Threat Intelligence has no report of CVE-2026-115921 being exploited in the wild.

How severe is CVE-2026-115921?

Medium severity, with a CVSS score of 6.2, published 26 October 2026.

Which products and versions are affected?

ONNX 1.4.0 to 1.21.x; onnx (PyPI) >= 1.4.0, <= 1.21.0, ECOSYSTEM:introduced=1.4.0,fixed=1.22.0.

Is there a fix for CVE-2026-115921?

Yes. onnx (PyPI): upgrade to 1.22.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

How is CVE-2026-115921 attacked?

It is attacked over the network, in a software library.

Am I affected by CVE-2026-115921?

Check whether you run ONNX or onnx (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

CVE-2026-115921: ONNX null pointer dereference in shape inference

Q: Is there a fix for CVE-2026-115921?

Yes. onnx (PyPI): upgrade to 1.22.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.

Q: How is CVE-2026-115921 attacked?

It is attacked over the network, in a software library.

Q: Am I affected by CVE-2026-115921?

Check whether you run ONNX or onnx (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

CVE-2026-115921 · Severity: medium · CVSS 6.2 · Published 2026-10-26

Open Neural Network Exchange (ONNX) is a machine learning framework used to standardize model formats across different platforms. Versions 1.4.0 through 1.21.x fail to properly validate the num_scan_inputs attribute in shape inference functions, allowing untrusted models to trigger null pointer dereferences or excessive memory allocation. An attacker can exploit this by crafting a malicious model file that crashes the inference process or disrupts shape inference operations.

Technologies: ONNX, onnx (PyPI). Vendors: ONNX, PyPI.

Quick answers

Is CVE-2026-115921 exploited in the wild?: No. Junglewise Threat Intelligence has no report of CVE-2026-115921 being exploited in the wild.
How severe is CVE-2026-115921?: Medium severity, with a CVSS score of 6.2, published 26 October 2026.
Which products and versions are affected?: ONNX 1.4.0 to 1.21.x; onnx (PyPI) >= 1.4.0, <= 1.21.0, ECOSYSTEM:introduced=1.4.0,fixed=1.22.0.
Is there a fix for CVE-2026-115921?: Yes. onnx (PyPI): upgrade to 1.22.0 or later. Junglewise finds every place you run it, drafts the upgrade and applies it once you approve.
How is CVE-2026-115921 attacked?: It is attacked over the network, in a software library.
Am I affected by CVE-2026-115921?: Check whether you run ONNX or onnx (PyPI) at an affected version. Junglewise does that check for you around the clock: connect your code, cloud and domains, and it matches new vulnerabilities like this one against what you actually run and tells you when one reaches you.

How to fix

onnx (PyPI): upgrade to 1.22.0 or later
```
pip install "onnx>=1.22.0"
```

Technical details

ScanInferenceFunction and related shape inference functions in ONNX lack proper validation of the num_scan_inputs attribute. A missing attribute causes null pointer dereference, while a negative value is cast to size_t and can trigger oversized memory allocation. Untrusted models can pass onnx.checker.check_model() validation yet cause denial of service through shape inference disruption or process termination.

Affected products

ONNX ONNX 1.4.0 to 1.21.x

Identifiers

CVE-2026-115921
GHSA-m4pr-6v3c-6fgr

Timeline

2026-05-07: patched: Fix merged as PR #7916 to onnx:main
2026-10-26: advisory

References

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