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  <title>Most recent entries from all</title>
  <updated>2026-09-28T18:39:22.359640+00:00</updated>
  <author>
    <name>Vulnerability-Lookup</name>
    <email>info@circl.lu</email>
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  <entry>
    <id>https://vulnerability.circl.lu/vuln/cve-2019-6446</id>
    <title>CVE-2019-6446</title>
    <updated>2026-09-28T18:39:22.383913+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml">
        <p>An issue was discovered in NumPy before 1.16.3. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources.</p>
      </div>
    </content>
    <link href="https://vulnerability.circl.lu/vuln/cve-2019-6446"/>
  </entry>
  <entry>
    <id>https://vulnerability.circl.lu/vuln/ghsa-9fq2-x9r6-wfmf</id>
    <title>GHSA-9fq2-x9r6-wfmf — Numpy Deserialization of Untrusted Data</title>
    <updated>2026-09-28T18:39:22.384047+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: numpy</p>
<p>** DISPUTED **  An issue was discovered in NumPy 1.16.2 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is  a behavior that might have legitimate applications in (for example) loading serialized Python object arrays from trusted and authenticated sources.</p></div>
    </content>
    <link href="https://vulnerability.circl.lu/vuln/ghsa-9fq2-x9r6-wfmf"/>
  </entry>
  <entry>
    <id>https://vulnerability.circl.lu/vuln/pysec-2019-108</id>
    <title>PYSEC-2019-108</title>
    <updated>2026-09-28T18:39:22.384106+00:00</updated>
    <content type="xhtml">
      <div xmlns="http://www.w3.org/1999/xhtml"><p><strong>Affected:</strong> PyPI: numpy</p>
<p>** DISPUTED **   An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickle Python module unsafely, which allows remote attackers to execute arbitrary code via a crafted serialized object, as demonstrated by a numpy.load call. NOTE: third parties dispute this issue because it is  a behavior that might have legitimate applications in (for example)  loading serialized Python object arrays from trusted and authenticated  sources.</p></div>
    </content>
    <link href="https://vulnerability.circl.lu/vuln/pysec-2019-108"/>
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