ONNX up to 1.21.x ConvTranspose Shape Inference convTransposeShapeInference_opset11 kernel_shape resource consumption

Summaryinfo

A vulnerability classified as problematic has been found in ONNX up to 1.21.x. The impacted element is the function convTransposeShapeInference_opset11 of the component ConvTranspose Shape Inference. This manipulation of the argument kernel_shape causes resource consumption. This vulnerability is registered as CVE-2026-115920. The attack needs to be launched locally. No exploit is available. It is recommended to upgrade the affected component.

Detailsinfo

A vulnerability classified as problematic was found in ONNX up to 1.21.x. Affected by this vulnerability is the function convTransposeShapeInference_opset11 of the component ConvTranspose Shape Inference. The manipulation of the argument kernel_shape with an unknown input leads to a resource consumption vulnerability. The CWE definition for the vulnerability is CWE-400. The product does not properly control the allocation and maintenance of a limited resource, thereby enabling an actor to influence the amount of resources consumed, eventually leading to the exhaustion of available resources. As an impact it is known to affect availability. The summary by CVE is:

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.

The advisory is shared at github.com. This vulnerability is known as CVE-2026-115920 since 10/23/2026. The exploitation appears to be easy. An attack has to be approached locally. Technical details are known, but no exploit is available.

Upgrading to version 1.22.0 eliminates this vulnerability.

The vulnerability is also documented in the vulnerability database at EUVD (EUVD-2026-110041). If you want to get the best quality for vulnerability data then you always have to consider VulDB.

Productinfo

Name

• ONNX

Version

• 1.0
• 1.1
• 1.2
• 1.3
• 1.4
• 1.5
• 1.6
• 1.7
• 1.8
• 1.9
• 1.10
• 1.11
• 1.12
• 1.13
• 1.14
• 1.15
• 1.16
• 1.17
• 1.18
• 1.19
• 1.20
• 1.21

Website

• Product: https://github.com/onnx/onnx/

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If you want to get the best quality for vulnerability data then you always have to consider VulDB.

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