ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank

影響: pip:onnx >= 1.2.1, <= 1.21.0 → 1.22.0

ONNX ConvTranspose shape inference performed an out-of-bounds read when the weight tensor had fewer than three dimensions and the model did not provide a kernel_shape attribute. The inference function derived an empty effective_kernel_shape vector from the undersized weight tensor, then indexed that vector once for each spatial dimension of the input tensor. A crafted model passed onnx.checker.check_model() and caused SIGSEGV when passed to onnx.shape_inference.infer_shapes(). Technical details…

Read on GitHub Advisory Database

On 10/29/2026, 06:16 AM, GitHub Advisory Database published "ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank" (type: Advisory). Severity is "Medium" (medium). Related technologies: Python. CVE: CVE-2026-115920.