CVE-2026-115920
ONNX: Out-of-bounds read in ConvTranspose shape inference via undersized weight rank
- State
- Published
- Severity
- 6.2 Medium
- Published
- Oct 26, 2026
- Updated
- Oct 26, 2026
- Reserved
- Oct 23, 2026
Description
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.2.1 until 1.22.0, ConvTranspose shape inference processes a weight tensor with fewer than three dimensions without a kernel_shape attribute by deriving an empty effective_kernel_shape and indexing it for the input's spatial dimensions. The flaw affects convTransposeShapeInference_opset11() and the current inference path, and an untrusted model that can pass onnx.checker.check_model() can crash onnx.shape_inference.infer_shapes(), causing denial of service without demonstrated confidentiality or integrity impact. This issue is fixed in version 1.22.0.
Scores
| CVSS | Score | Vector | Source |
|---|---|---|---|
| 3.1 | 6.2 Medium | CVSS:3.1/AV:L/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H | GitHub_M |
Weaknesses
- CWE-125 Out-of-bounds Read
Affected Products
| Product | Versions |
|---|---|
onnxonnx |
|
References
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