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  <DocumentTitle xml:lang="en">CVE-2022-36012</DocumentTitle>
  <DocumentType>SUSE CVE</DocumentType>
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    <ContactDetails>security@suse.de</ContactDetails>
    <IssuingAuthority>SUSE Security Team</IssuingAuthority>
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    <Identification>
      <ID>SUSE CVE-2022-36012</ID>
    </Identification>
    <Status>Interim</Status>
    <Version>1</Version>
    <RevisionHistory>
      <Revision>
        <Number>5</Number>
        <Date>2025-02-16T02:57:25Z</Date>
        <Description>current</Description>
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    <InitialReleaseDate>2022-09-19T23:35:40Z</InitialReleaseDate>
    <CurrentReleaseDate>2025-02-16T02:57:25Z</CurrentReleaseDate>
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      <Date>2020-12-27T01:00:00Z</Date>
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    <Note Title="CVE" Type="Summary" Ordinal="1" xml:lang="en">CVE-2022-36012</Note>
    <Note Title="Mitre CVE Description" Type="Description" Ordinal="2" xml:lang="en">TensorFlow is an open source platform for machine learning. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</Note>
    <Note Title="Terms of Use" Type="Legal Disclaimer" Ordinal="4" xml:lang="en">The CVRF data is provided by SUSE under the Creative Commons License 4.0 with Attribution (CC-BY-4.0).</Note>
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      <Description>SUSE Security Ratings</Description>
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      <Note Title="Vulnerability Description" Type="General" Ordinal="1" xml:lang="en">TensorFlow is an open source platform for machine learning. When `mlir::tfg::ConvertGenericFunctionToFunctionDef` is given empty function attributes, it crashes. We have patched the issue in GitHub commit ad069af92392efee1418c48ff561fd3070a03d7b. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.</Note>
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