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    <title>Most recent entries from all</title>
    <link>https://db.gcve.eu</link>
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      <title>CVE-2019-6446</title>
      <link>https://db.gcve.eu/vuln/cve-2019-6446</link>
      <description>&lt;p&gt;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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://db.gcve.eu/vuln/cve-2019-6446</guid>
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    <item>
      <title>GHSA-9fq2-x9r6-wfmf — Numpy Deserialization of Untrusted Data</title>
      <link>https://db.gcve.eu/vuln/ghsa-9fq2-x9r6-wfmf</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: numpy&lt;/p&gt;
&lt;p&gt;** 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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: numpy&lt;/p&gt;
&lt;p&gt;** 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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://db.gcve.eu/vuln/ghsa-9fq2-x9r6-wfmf</guid>
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    <item>
      <title>PYSEC-2019-108</title>
      <link>https://db.gcve.eu/vuln/pysec-2019-108</link>
      <description>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: numpy&lt;/p&gt;
&lt;p&gt;** 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.&lt;/p&gt;</description>
      <content:encoded>&lt;p&gt;&lt;strong&gt;Affected:&lt;/strong&gt; PyPI: numpy&lt;/p&gt;
&lt;p&gt;** 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.&lt;/p&gt;</content:encoded>
      <guid isPermaLink="false">https://db.gcve.eu/vuln/pysec-2019-108</guid>
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