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  <DocumentTitle xml:lang="en">CVE-2022-21737</DocumentTitle>
  <DocumentType>SUSE CVE</DocumentType>
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    <Identification>
      <ID>SUSE CVE-2022-21737</ID>
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    <Status>Interim</Status>
    <Version>1</Version>
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        <Number>6</Number>
        <Date>2025-02-16T03:13:16Z</Date>
        <Description>current</Description>
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    <InitialReleaseDate>2022-02-05T02:43:32Z</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-2022-21737</Note>
    <Note Title="Mitre CVE Description" Type="Description" Ordinal="2" xml:lang="en">Tensorflow is an Open Source Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, 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 Machine Learning Framework. The implementation of `*Bincount` operations allows malicious users to cause denial of service by passing in arguments which would trigger a `CHECK`-fail. There are several conditions that the input arguments must satisfy. Some are not caught during shape inference and others are not caught during kernel implementation. This results in `CHECK` failures later when the output tensors get allocated. The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.</Note>
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