What’s Vulnerable › Vulnerabilities

CVE-2026-115921: ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute

• Severity: medium (CVSS 6.2 v3.1)
• Exploited in the wild: not listed in CISA KEV
• EPSS: 0.1% probability of exploitation in the next 30 days
• Public exploit or detection template: none known
• Published: 2026-10-26 · updated 2026-10-31
• Weakness: CWE-195

Description

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.

Affected products

• onnx: from 1.4.0, < 1.22.0

References

• https://github.com/onnx/onnx/commit/dd6bc92ea39fd2274fd671f0734b0b8b558356f5
• https://github.com/onnx/onnx/pull/7916
• https://github.com/onnx/onnx/releases/tag/v1.22.0
• https://github.com/onnx/onnx/security/advisories/GHSA-m4pr-6v3c-6fgr

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