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  <DocumentTitle xml:lang="en">CVE-2021-29566</DocumentTitle>
  <DocumentType>SUSE CVE</DocumentType>
  <DocumentPublisher Type="Vendor">
    <ContactDetails>security@suse.de</ContactDetails>
    <IssuingAuthority>SUSE Security Team</IssuingAuthority>
  </DocumentPublisher>
  <DocumentTracking>
    <Identification>
      <ID>SUSE CVE-2021-29566</ID>
    </Identification>
    <Status>Interim</Status>
    <Version>1</Version>
    <RevisionHistory>
      <Revision>
        <Number>4</Number>
        <Date>2022-10-26T23:52:48Z</Date>
        <Description>current</Description>
      </Revision>
    </RevisionHistory>
    <InitialReleaseDate>2021-05-30T14:49:48Z</InitialReleaseDate>
    <CurrentReleaseDate>2022-10-26T23:52:48Z</CurrentReleaseDate>
    <Generator>
      <Engine>cve-database/bin/generate-cvrf-cve.pl</Engine>
      <Date>2020-12-27T01:00:00Z</Date>
    </Generator>
  </DocumentTracking>
  <DocumentNotes>
    <Note Title="CVE" Type="Summary" Ordinal="1" xml:lang="en">CVE-2021-29566</Note>
    <Note Title="Mitre CVE Description" Type="Description" Ordinal="2" xml:lang="en">TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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>
  </DocumentNotes>
  <DocumentReferences>
    <Reference Type="Self">
      <URL>https://www.suse.com/support/security/rating/</URL>
      <Description>SUSE Security Ratings</Description>
    </Reference>
  </DocumentReferences>
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  <Vulnerability xmlns="http://docs.oasis-open.org/csaf/ns/csaf-cvrf/v1.2/vuln" Ordinal="1">
    <Notes>
      <Note Title="Vulnerability Description" Type="General" Ordinal="1" xml:lang="en">TensorFlow is an end-to-end open source platform for machine learning. An attacker can write outside the bounds of heap allocated arrays by passing invalid arguments to `tf.raw_ops.Dilation2DBackpropInput`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/afd954e65f15aea4d438d0a219136fc4a63a573d/tensorflow/core/kernels/dilation_ops.cc#L321-L322) does not validate before writing to the output array. The values for `h_out` and `w_out` are guaranteed to be in range for `out_backprop` (as they are loop indices bounded by the size of the array). However, there are no similar guarantees relating `h_in_max`/`w_in_max` and `in_backprop`. The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, as these are also affected and still in supported range.</Note>
    </Notes>
    <CVE>CVE-2021-29566</CVE>
    <ProductStatuses/>
    <Threats>
      <Threat Type="Impact">
        <Description>important</Description>
      </Threat>
    </Threats>
    <CVSSScoreSets>
      <ScoreSetV2>
        <BaseScoreV2>4.6</BaseScoreV2>
        <VectorV2>AV:L/AC:L/Au:N/C:P/I:P/A:P</VectorV2>
      </ScoreSetV2>
      <ScoreSetV3>
        <BaseScoreV3>7.8</BaseScoreV3>
        <VectorV3>CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H</VectorV3>
      </ScoreSetV3>
    </CVSSScoreSets>
  </Vulnerability>
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