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  <DocumentTitle xml:lang="en">CVE-2021-41202</DocumentTitle>
  <DocumentType>SUSE CVE</DocumentType>
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    <IssuingAuthority>SUSE Security Team</IssuingAuthority>
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    <Identification>
      <ID>SUSE CVE-2021-41202</ID>
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    <Status>Interim</Status>
    <Version>1</Version>
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        <Number>4</Number>
        <Date>2025-02-17T00:26:59Z</Date>
        <Description>current</Description>
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    <InitialReleaseDate>2021-11-09T02:08:26Z</InitialReleaseDate>
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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-2021-41202</Note>
    <Note Title="Mitre CVE Description" Type="Description" Ordinal="2" xml:lang="en">TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.</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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      <Note Title="Vulnerability Description" Type="General" Ordinal="1" xml:lang="en">TensorFlow is an open source platform for machine learning. In affected versions while calculating the size of the output within the `tf.range` kernel, there is a conditional statement of type `int64 = condition ? int64 : double`. Due to C++ implicit conversion rules, both branches of the condition will be cast to `double` and the result would be truncated before the assignment. This result in overflows. The fix will be included in TensorFlow 2.7.0. We will also cherrypick this commit on TensorFlow 2.6.1, TensorFlow 2.5.2, and TensorFlow 2.4.4, as these are also affected and still in supported range.</Note>
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