ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute

[ Description ]Official 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.

[ Fixes ]Fixes and patches

• onnx 1.22.0Fixed version · GitHub Advisories · pip package onnx: upgrade to 1.22.0 or later (affected >= 1.4.0, <= 1.21.0)

[ Packages ]Affected open-source packages

• onnx pipAffected >= 1.4.0, <= 1.21.0 · fixed in 1.22.0 · GHSA-m4pr-6v3c-6fgr

[ References ]References

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