CVE-2026-115921
mediumOpen Neural Network Exchange (ONNX) is an open standard for machine learning interoperability.
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.
CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H Affected products
Not reported by the source (unknown — not "none").
Weakness classification (CWE)
Source: NVD / CISA. “NVD-CWE-Other” and “NVD-CWE-noinfo” mean NVD could not assign a specific weakness.
Mitigation & advisories
No vendor advisory or patch reference tagged by NVD. Check the references below.
References
- https://github.com/onnx/onnx/commit/dd6bc92ea39fd2274fd671f0734b0b8b558356f5 security-advisories@github.com
- https://github.com/onnx/onnx/pull/7916 security-advisories@github.com
- https://github.com/onnx/onnx/releases/tag/v1.22.0 security-advisories@github.com
- https://github.com/onnx/onnx/security/advisories/GHSA-m4pr-6v3c-6fgr security-advisories@github.com