Bug 2560979 (CVE-2026-115919)

Summary: CVE-2026-115919 onnx: onnx: Denial of Service via out-of-bounds read in shape inference
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
Status: NEW --- QA Contact:
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Priority: medium    
Version: unspecifiedKeywords: Security
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OS: Linux   
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A flaw was found in ONNX. This vulnerability allows an attacker to cause a Denial of Service (DoS) by providing a specially crafted machine learning model with malformed neural network nodes. During the shape inference process, the application attempts to read memory outside the intended boundaries without validating input dimensions, leading to an application crash.
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Description OSIDB Bzimport 2026-10-26 17:42:46 UTC 
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.