CVE-2026-115919

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. 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.

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/92e541266af5dd38cfa48aeb92206f4268a066cd
https://github.com/onnx/onnx/pull/7879
https://github.com/onnx/onnx/releases/tag/v1.22.0
https://github.com/onnx/onnx/security/advisories/GHSA-48m4-24cq-37qf