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CVE-2026-115922
Published:October 26, 2026
Updated:October 28, 2026
Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. Prior to 1.22.0, _unpack_2bit() and _unpack_4bit() resize unpacked arrays according to attacker-controlled TensorProto.dims without verifying that raw_data or int32_data encodes the declared number of elements. Materializing an untrusted UINT2, INT2, UINT4, INT4, or FLOAT4E2M1 tensor through onnx.numpy_helper.to_array() or onnx.reference.ReferenceEvaluator can therefore expand a small packed payload into a disproportionately large allocation and exhaust memory. This issue is fixed in version 1.22.0.
Affected Packages
onnx (CONDA):
Affected version(s) >=1.18.0 <1.22.0
Fix Suggestion:
Update to version 1.22.0
https://github.com/onnx/onnx.git (GITHUB):
Affected version(s) >=v1.18.0 <v1.22.0
Fix Suggestion:
Update to version v1.22.0
onnx (PYTHON):
Affected version(s) >=1.18.0 <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)
Memory Allocation with Excessive Size Value
EPSS
Base Score:
0.13