CVE-2026-115920

Published: Ott 26, 2026 Last Modified: Ott 26, 2026
ExploitDB:
Other exploit source:
Google Dorks:
MEDIUM 6,2
Attack Vector: local
Attack Complexity: low
Privileges Required: none
User Interaction: none
Scope: unchanged
Confidentiality: none
Integrity: none
Availability: high

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.

125

Out-of-bounds Read

Draft
Common Consequences
Security Scopes Affected:
Confidentiality Availability Other
Potential Impacts:
Read Memory Bypass Protection Mechanism Dos: Crash, Exit, Or Restart Varies By Context
Applicable Platforms
Languages: Memory-Unsafe, C, C++
Technologies: ICS/OT
View CWE Details
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