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  <updated>2026-10-06T08:09:13.912405+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>csirt@opendfir.org</email>
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  <entry>
    <id>https://cve.radiocsirt.org/vuln/cve-2026-63632</id>
    <title>CVE-2026-63632 — ONNX: Heap-Buffer-Overflow READ in Gemm Version Converter Adapter via Undersized Input Shape</title>
    <updated>2026-10-06T08:09:13.913624+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> onnx</p>
<p>Open Neural Network Exchange (ONNX) is an open standard for machine learning interoperability. From 1.3.0 until 1.22.0, onnx.version_converter.convert_version() can perform an out-of-bounds read in Gemm_7_6::adapt_gemm_7_6() in onnx/version_converter/adapters/gemm_7_6.h when a Gemm node has input tensors with fewer than two dimensions because B_shape[1], A_shape[0], or A_shape[1] is accessed without a rank check, potentially causing a process crash during an opset 7 to 6 downgrade. This issue is fixed in version 1.22.0.</p></div>
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    <link href="https://cve.radiocsirt.org/vuln/cve-2026-63632"/>
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