Mend.io Vulnerability Database
The largest open source vulnerability database
What is a Vulnerability ID?
New vulnerability? Tell us about it!
CVE-2026-115919
Published:October 26, 2026
Updated:October 29, 2026
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, RNNShapeInference_opset1_to_6() processes malformed RNN and LSTM nodes from opsets 1 through 6 and GRU nodes from opsets 3 through 6 without verifying that the first input has rank three. The function accesses dim(0) and dim(1) on an undersized protobuf shape, which can read outside the intended repeated field and terminate an application when onnx.shape_inference.infer_shapes() processes an untrusted model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.
Affected Packages
onnx (CONDA):
Affected version(s) >=1.3.0 <1.22.0
Fix Suggestion:
Update to version 1.22.0
https://github.com/onnx/onnx.git (GITHUB):
Affected version(s) >=v1.2.1 <v1.22.0
Fix Suggestion:
Update to version v1.22.0
onnx (PYTHON):
Affected version(s) >=1.2.1 <1.22.0
Fix Suggestion:
Update to version 1.22.0
Do you need more information?
Contact Us
CVSS 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