CVE-2026-115920
Published:October 26, 2026
Updated:October 28, 2026
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.
Affected Packages
onnx (CONDA):
Affected version(s) >=1.3.0 <1.22.0Fix Suggestion:
Update to version 1.22.0https://github.com/onnx/onnx.git (GITHUB):
Affected version(s) >=v1.2.1 <v1.22.0Fix Suggestion:
Update to version v1.22.0onnx (PYTHON):
Affected version(s) >=1.2.1 <1.22.0Fix Suggestion:
Update to version 1.22.0Related Resources (4)
Do you need more information?
Contact UsCVSS v4
Base Score:
6.9
Attack Vector
LOCAL
Attack Complexity
LOW
Attack Requirements
NONE
Privileges Required
NONE
User Interaction
NONE
Vulnerable System Confidentiality
NONE
Vulnerable System Integrity
NONE
Vulnerable System Availability
HIGH
Subsequent System Confidentiality
NONE
Subsequent System Integrity
NONE
Subsequent System Availability
NONE
CVSS v3
Base Score:
6.2
Attack Vector
LOCAL
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED
Confidentiality
NONE
Integrity
NONE
Availability
HIGH
Weakness Type (CWE)
Out-of-bounds Read
EPSS
Base Score:
0.18