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  <id>https://vulnerability.circl.lu/sightings/feed</id>
  <title>Most recent sightings.</title>
  <updated>2026-06-21T19:59:30.553196+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>info@circl.lu</email>
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  <subtitle>Contains only the most 10 recent sightings.</subtitle>
  <entry>
    <id>https://vulnerability.circl.lu/sighting/12d80560-d659-4392-b66d-431de31da7ec/export</id>
    <title>12d80560-d659-4392-b66d-431de31da7ec</title>
    <updated>2026-06-21T19:59:30.953489+00:00</updated>
    <author>
      <name>Automation user</name>
      <uri>https://vulnerability.circl.lu/user/automation</uri>
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    <content>{"uuid": "12d80560-d659-4392-b66d-431de31da7ec", "vulnerability_lookup_origin": "1a89b78e-f703-45f3-bb86-59eb712668bd", "author": "9f56dd64-161d-43a6-b9c3-555944290a09", "vulnerability": "CVE-2022-29212", "type": "seen", "source": "https://t.me/cibsecurity/43132", "content": "\u203c CVE-2022-29212 \u203c\n\nTensorFlow is an open source platform for machine learning. Prior to versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4, certain TFLite models that were created using TFLite model converter would crash when loaded in the TFLite interpreter. The culprit is that during quantization the scale of values could be greater than 1 but code was always assuming sub-unit scaling. Thus, since code was calling `QuantizeMultiplierSmallerThanOneExp`, the `TFLITE_CHECK_LT` assertion would trigger and abort the process. Versions 2.9.0, 2.8.1, 2.7.2, and 2.6.4 contain a patch for this issue.\n\n\ud83d\udcd6 Read\n\nvia \"National Vulnerability Database\".", "creation_timestamp": "2022-05-21T07:44:55.000000Z"}</content>
    <link href="https://vulnerability.circl.lu/sighting/12d80560-d659-4392-b66d-431de31da7ec/export"/>
    <published>2022-05-21T07:44:55+00:00</published>
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