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CVE-2026-115921
Published:October 26, 2026
Updated:October 29, 2026
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.4.0 until 1.22.0, ScanInferenceFunction, ScanInferenceFunction_opset8, and ScanInferenceFunction_opset9 do not safely validate the required num_scan_inputs attribute. A missing attribute is dereferenced as a null pointer, while a negative value is converted to size_t and can reach an exceptional oversized allocation path. An untrusted model can therefore terminate or disrupt shape inference, including a negative-value model that can pass onnx.checker.check_model(). This issue is fixed in version 1.22.0.
Affected Packages
onnx (CONDA):
Affected version(s) >=1.4.1 <1.22.0
Fix Suggestion:
Update to version 1.22.0
https://github.com/onnx/onnx.git (GITHUB):
Affected version(s) >=v1.4.0 <v1.22.0
Fix Suggestion:
Update to version v1.22.0
onnx (PYTHON):
Affected version(s) >=1.4.0 <1.22.0
Fix Suggestion:
Update to version 1.22.0
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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)
NULL Pointer Dereference
Signed to Unsigned Conversion Error
EPSS
Base Score:
0.13