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  <DocumentTitle xml:lang="en">CVE-2021-29533</DocumentTitle>
  <DocumentType>SUSE CVE</DocumentType>
  <DocumentPublisher Type="Vendor">
    <ContactDetails>security@suse.de</ContactDetails>
    <IssuingAuthority>SUSE Security Team</IssuingAuthority>
  </DocumentPublisher>
  <DocumentTracking>
    <Identification>
      <ID>SUSE CVE-2021-29533</ID>
    </Identification>
    <Status>Interim</Status>
    <Version>1</Version>
    <RevisionHistory>
      <Revision>
        <Number>7</Number>
        <Date>2025-02-17T00:43:57Z</Date>
        <Description>current</Description>
      </Revision>
    </RevisionHistory>
    <InitialReleaseDate>2021-05-30T14:49:38Z</InitialReleaseDate>
    <CurrentReleaseDate>2025-02-17T00:43:57Z</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-2021-29533</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 trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. 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>
  <ProductTree xmlns="http://docs.oasis-open.org/csaf/ns/csaf-cvrf/v1.2/prod"/>
  <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 trigger a denial of service via a `CHECK` failure by passing an empty image to `tf.raw_ops.DrawBoundingBoxes`. This is because the implementation(https://github.com/tensorflow/tensorflow/blob/ea34a18dc3f5c8d80a40ccca1404f343b5d55f91/tensorflow/core/kernels/image/draw_bounding_box_op.cc#L148-L165) uses `CHECK_*` assertions instead of `OP_REQUIRES` to validate user controlled inputs. Whereas `OP_REQUIRES` allows returning an error condition back to the user, the `CHECK_*` macros result in a crash if the condition is false, similar to `assert`. In this case, `height` is 0 from the `images` input. This results in `max_box_row_clamp` being negative and the assertion being falsified, followed by aborting program execution. 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-2021-29533</CVE>
    <ProductStatuses/>
    <Threats>
      <Threat Type="Impact">
        <Description>important</Description>
      </Threat>
    </Threats>
    <CVSSScoreSets>
      <ScoreSetV2>
        <BaseScoreV2>2.1</BaseScoreV2>
        <VectorV2>AV:L/AC:L/Au:N/C:N/I:N/A:P</VectorV2>
      </ScoreSetV2>
      <ScoreSetV3>
        <BaseScoreV3>5.5</BaseScoreV3>
        <VectorV3>CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H</VectorV3>
      </ScoreSetV3>
    </CVSSScoreSets>
  </Vulnerability>
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