Vulnerabilities in pkg:pypi/numpy

Q: What is CVE-2019-6446?

CVE-2019-6446 is a security vulnerability in Numpy involving Numpy Deserialization of Untrusted Data under CWE-502: Deserialization of Untrusted Data.

Q: Which Numpy versions are affected?

Affected versions include releases prior to 1.16.3 across affected packages: numpy.

Q: What version fixes CVE-2019-6446?

Upgrading to 1.16.3 (or the latest patched release for your respective branch) resolves the vulnerability.

Q: Is numpy affected?

Yes, numpy is affected in releases prior to 1.16.3. Upgrade your dependency to 1.16.3 or later.

Q: What is the CVSS score of CVE-2019-6446?

CVE-2019-6446 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.

Q: What CWE is associated with CVE-2019-6446?

CVE-2019-6446 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).

Q: How can I check PyPI dependencies for CVE-2019-6446?

Run the dependency tree command: 'pip show numpy'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

PACKAGE

Advisory Identifier: GHSA-9fq2-x9r6-wfmf

Advisory Summary

CVE-2019-6446 is a CRITICAL (CVSS 9.8) numpy deserialization of untrusted data vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Numpy libraries in the PyPI ecosystem. The issue involves numpy deserialization of untrusted data. Remediation is available by upgrading affected packages to version 1.16.3.

8 Known Advisory Record(s)

Package Vulnerability Intelligence

pkg:pypi/numpy

8 Known Advisory Record(s)

Vulnerability advisories affecting package pkg:pypi/numpy. Select an advisory below to view technical details or fixes.

Advisory ID	CVE / NVD	Severity	Summary
GHSA-9fq2-x9r6-wfmf	CVE-2019-6446	CRITICAL	Numpy Deserialization of Untrusted Data
GHSA-cw6w-4rcx-xphc	CVE-2014-1858	HIGH	Arbitrary file write in NumPy
GHSA-2fc2-6r4j-p65h	CVE-2014-1859	HIGH	Numpy arbitrary file write via symlink attack
GHSA-6p56-wp2h-9hxr	CVE-2021-33430	MODERATE	NumPy Buffer Overflow (Disputed)
GHSA-5545-2q6w-2gh6	CVE-2021-41495	HIGH	NumPy NULL Pointer Dereference
GHSA-fpfv-jqm9-f5jm	CVE-2021-34141	MODERATE	Incorrect Comparison in NumPy
GHSA-f7c7-j99h-c22f	CVE-2021-41496	MODERATE	Buffer Copy without Checking Size of Input in NumPy
GHSA-frgw-fgh6-9g52	CVE-2017-12852	HIGH	Numpy missing input validation

CVE-2019-6446 at a Glance

CVE Identifier CVE-2019-6446

GHSA Identifier GHSA-9fq2-x9r6-wfmf

Severity CRITICAL

CVSS v3.1 Base Score 9.8

CWE Classification CWE-502: Deserialization of Untrusted Data

Affected Product Numpy

Package Ecosystem PyPI

Published Date 2022-05-24

Last Updated 2026-07-06

Security Impact

CVSS: 9.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)

Attack Complexity Low (AC:L)

Privileges Required None (PR:N)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality High (C:H)

Integrity High (I:H)

Availability High (A:H)

How to Fix CVE-2019-6446

To remediate this vulnerability, upgrade all affected Numpy dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

numpy fixed: 1.16.3

pip install numpy>=1.16.3

Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release:

pip show numpy

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2019-6446, inspect your installed packages using pip:

pip show numpy

Analyze the terminal output to locate any version of Numpy in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 1.16.3), your application is affected.

Note: The pip show numpy command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Numpy, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

** 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.

CVE-2019-6446 Affected Numpy Versions

1 component(s)

Fixed Versions:

1.16.3

Product / Package	Ecosystem	Affected Versions	Fixed Version
numpy pypi/numpy	PyPI	< 1.16.3	1.16.3

References

NVD — CVE-2019-6446 NVD

https://nvd.nist.gov/vuln/detail/CVE-2019-6446

Numpy Source Repository REPOSITORY

https://github.com/numpy/numpy/issues/12759

Numpy Source Repository REPOSITORY

https://github.com/numpy/numpy/pull/12889

Numpy Source Repository REPOSITORY

https://github.com/numpy/numpy/pull/13359

Security Fix Commit FIX COMMIT

https://github.com/numpy/numpy/commit/89b688732b37616c9d26623f81aaee1703c30ffb

access.redhat.com/errata/rhsa-2019:33... WEB

https://access.redhat.com/errata/RHSA-2019:3335

access.redhat.com/errata/rhsa-2019:37... WEB

https://access.redhat.com/errata/RHSA-2019:3704

bugzilla.suse.com/show_bug.cgi WEB

https://bugzilla.suse.com/show_bug.cgi?id=1122208

GitHub Advisory / Wiki ADVISORY

https://github.com/advisories/GHSA-9fq2-x9r6-wfmf

Numpy Source Repository REPOSITORY

https://github.com/numpy/numpy

Numpy Source Repository REPOSITORY

https://github.com/pypa/advisory-database/tree/main/vulns/numpy/PYSEC-2019-108.yaml

lists.fedoraproject.org/archives/list/packa... WEB

https://lists.fedoraproject.org/archives/list/package-announce%40lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4

lists.fedoraproject.org/archives/list/packa... WEB

https://lists.fedoraproject.org/archives/list/package-announce@lists.fedoraproject.org/message/7ZZAYIQNUUYXGMKHSPEEXS4TRYFOUYE4

Numpy Security Information SECURITY

https://web.archive.org/web/20210124234613/https://www.securityfocus.com/bid/106670

Numpy Security Information SECURITY

http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00091.html

Numpy Security Information SECURITY

http://lists.opensuse.org/opensuse-security-announce/2019-09/msg00092.html

Numpy Security Information SECURITY

http://lists.opensuse.org/opensuse-security-announce/2019-10/msg00015.html

Numpy Security Information SECURITY

http://www.securityfocus.com/bid/106670

Frequently Asked Questions

What is CVE-2019-6446?

CVE-2019-6446 is a security vulnerability in Numpy involving Numpy Deserialization of Untrusted Data under CWE-502: Deserialization of Untrusted Data.

Which Numpy versions are affected?

Affected versions include releases prior to 1.16.3 across affected packages: numpy.

What version fixes CVE-2019-6446?

Upgrading to 1.16.3 (or the latest patched release for your respective branch) resolves the vulnerability.

Is numpy affected?

Yes, numpy is affected in releases prior to 1.16.3. Upgrade your dependency to 1.16.3 or later.

What is the CVSS score of CVE-2019-6446?

CVE-2019-6446 has a CVSS v3.1 base score of 9.8 (CRITICAL) with vector string CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H.

What CWE is associated with CVE-2019-6446?

CVE-2019-6446 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).

How can I check PyPI dependencies for CVE-2019-6446?

Run the dependency tree command: 'pip show numpy'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.

Machine-readable OSV JSON OSV v1.5 Schema

Normalized schema output

View Raw JSON

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  "id" : "GHSA-9fq2-x9r6-wfmf",
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  "published" : "2022-05-24T22:00:57Z",
  "aliases" : [ "CVE-2019-6446" ],
  "summary" : "Numpy Deserialization of Untrusted Data",
  "details" : "** 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.",
  "severity" : [ {
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    "url" : "https://access.redhat.com/errata/RHSA-2019:3335"
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}

CVSS V3

9.8 CRITICAL

Attack Vector Network (AV:N)

Attack Complexity Low (AC:L)

Privileges Required None (PR:N)

User Interaction None (UI:N)

Scope Unchanged (S:U)

Confidentiality High (C:H)

Integrity High (I:H)

Availability High (A:H)

Vector String

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

Advisory Metadata

Source ID: GHSA-9fq2-x9r6-wfmf
Schema Version: 1.4.0
Published: 2022-05-24 22:00
Last Modified: 2026-07-06 15:24
Database Record File: advisories/github-reviewed/2022/05/GHSA-9fq2-x9r6-wfmf/GHSA-9fq2-x9r6-wfmf.json