Bug 2560984 (CVE-2026-115921)

Summary: CVE-2026-115921 onnx: onnx: Denial of Service via improper attribute validation in Scan shape inference
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
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Priority: medium    
Version: unspecifiedKeywords: Security
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OS: Linux   
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A flaw was found in Open Neural Network Exchange (ONNX). When performing shape inference on a machine learning model, the Scan operator does not safely validate the required num_scan_inputs attribute. An attacker can exploit this issue by supplying an untrusted model that omits this attribute or provides a negative value, triggering an invalid memory access or excessive memory allocation. This flaw causes the application to terminate unexpectedly, resulting in a Denial of Service (DoS).
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Description OSIDB Bzimport 2026-10-26 17:46:29 UTC 
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.