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    <lastBuildDate>Tue, 27 Oct 2026 17:45:36 +0000</lastBuildDate>
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      <title>CVE-2026-115921 — ONNX: Null Pointer Dereference in ScanInferenceFunction Due to Missing Required Attribute</title>
      <link>https://db.gcve.eu/vuln/cve-2026-115921</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; onnx&lt;/p&gt;
&lt;p&gt;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; onnx&lt;/p&gt;
&lt;p&gt;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.&lt;/p&gt;</content:encoded>
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