Vulnerability 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.
CVSS Score
MEDIUM
Related Weaknesses (CWE)
References
- https://github.com/onnx/onnx/commit/2ec288908952eea9dcf48d4b197915e1f72c6abf
- https://github.com/onnx/onnx/pull/7997
- https://github.com/onnx/onnx/releases/tag/v1.22.0
- https://github.com/onnx/onnx/security/advisories/GHSA-6pwm-x34p-fvj2
FAQ
What is CVE-2026-115920?
CVE-2026-115920 is a vulnerability with a CVSS score of 6.2 (MEDIUM). 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 di...
How severe is CVE-2026-115920?
CVE-2026-115920 has been rated MEDIUM with a CVSS base score of 6.2/10. Review the CVSS metrics above for detailed severity breakdown.
Is there a patch for CVE-2026-115920?
Check the references section above for vendor advisories and patch information. Review vendor security bulletins for remediation guidance.