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CVE-2019-6446: Numpy Deserialization of Untrusted Data

May 24, 2022 (updated October 8, 2024)

** 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.

References

  • access.redhat.com/errata/RHSA-2019:3335
  • access.redhat.com/errata/RHSA-2019:3704
  • bugzilla.suse.com/show_bug.cgi?id=1122208
  • github.com/advisories/GHSA-9fq2-x9r6-wfmf
  • github.com/numpy/numpy
  • github.com/numpy/numpy/issues/12759
  • github.com/numpy/numpy/pull/12889
  • github.com/pypa/advisory-database/tree/main/vulns/numpy/PYSEC-2019-108.yaml
  • lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4
  • lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4
  • nvd.nist.gov/vuln/detail/CVE-2019-6446
  • web.archive.org/web/20210124234613/https://www.securityfocus.com/bid/106670

Code Behaviors & Features

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Affected versions

All versions up to 1.16.0

Solution

Unfortunately, there is no solution available yet.

Impact 9.8 CRITICAL

CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

Learn more about CVSS

Weakness

  • CWE-502: Deserialization of Untrusted Data

Source file

pypi/numpy/CVE-2019-6446.yml

Spotted a mistake? Edit the file on GitLab.

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