Vulnerabilities
Misconfiguration
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CVE Vulnerabilities

CVE-2019-6446

Deserialization of Untrusted Data

Published: Jan 16, 2019 | Modified: Jul 21, 2025
CVSS 3.x
9.8
CRITICAL
Source:
NVD
CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
CVSS 2.x
7.5 HIGH
AV:N/AC:L/Au:N/C:P/I:P/A:P
RedHat/V2
RedHat/V3
8.8 MODERATE
CVSS:3.0/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Ubuntu
LOW
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Additional information
NVDhttps://nvd.nist.gov/vuln/detail/CVE-2019-6446
CWEhttps://cwe.mitre.org/data/definitions/502.html

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.

Weakness

The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.

Affected Software

NameVendorStart VersionEnd Version
NumpyNumpy*1.16.0 (including)
Red Hat Enterprise Linux 8RedHatpython27:2.7-8010020190903182548.51c94b97*
Red Hat Enterprise Linux 8RedHatnumpy-1:1.14.3-9.el8*
Python-numpyUbuntubionic*
Python-numpyUbuntucosmic*
Python-numpyUbuntudisco*
Python-numpyUbuntueoan*
Python-numpyUbuntutrusty*
Python-numpyUbuntuxenial*

Potential Mitigations

  • Make fields transient to protect them from deserialization.
  • An attempt to serialize and then deserialize a class containing transient fields will result in NULLs where the transient data should be. This is an excellent way to prevent time, environment-based, or sensitive variables from being carried over and used improperly.

References

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