Описание
Numpy Deserialization of Untrusted Data
** 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.
Ссылки
- https://nvd.nist.gov/vuln/detail/CVE-2019-6446
- https://github.com/numpy/numpy/issues/12759
- https://github.com/numpy/numpy/pull/12889
- https://access.redhat.com/errata/RHSA-2019:3335
- https://access.redhat.com/errata/RHSA-2019:3704
- https://bugzilla.suse.com/show_bug.cgi?id=1122208
- https://github.com/pypa/advisory-database/tree/main/vulns/numpy/PYSEC-2019-108.yaml
- https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4
- https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4
- https://web.archive.org/web/20210124234613/https://www.securityfocus.com/bid/106670
- http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00091.html
- http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00092.html
- http://lists.opensuse.org/opensuse-security-announce/2019-10/msg00015.html
Пакеты
numpy
<= 1.16.0
Отсутствует
EPSS
9.3 Critical
CVSS4
9.8 Critical
CVSS3
CVE ID
Дефекты
Связанные уязвимости
** 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.
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
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
An issue was discovered in NumPy 1.16.0 and earlier. It uses the pickl ...
EPSS
9.3 Critical
CVSS4
9.8 Critical
CVSS3