CVE-2019-6446: An issue was discovered in NumPy before 1.16.3

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CRITICAL 9.8REMOTEUPGRADEMITIGATE

CVE-2019-6446 is a critical-severity flaw (CVSS 9.8) affecting numpy, fedora. Below: why it ranks where it does, which versions are affected, what to do, and the exact commands.

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.

Why this priority

Critical severity
EPSS top 2%: very likely to be exploited
Public exploit reference
Remotely exploitable, no login, no user action

A fixed release or distro patch exists.

Risk facts

CVSS score	9.8 (Critical)
Attack vector	Network (remote)
Attack complexity	Low
Privileges needed	None
User interaction	None
EPSS exploit chance	27.3% (top 2%)
CISA exploited list	No
Weakness	CWE-502
Published	2019-01-16
Last modified	2026-06-17

Publisher (CNA): MITRE · Vendor: fedoraproject · numpy

Last updated 2026-06-17 · Sources: CVE Program, NVD, CISA KEV, EPSS and vendor advisories · How we score

Am I affected?

Timeline

2019-01-16 05:29 UTCPublished CVE record published
2026-06-17 02:39 UTCUpdated Record last modified

numpy numpy UPGRADE

Affected: <= 1.16.0

Fixed in: newer than 1.16.0

Safe to downgrade to: no unaffected older release

1. Check installed version

apt-cache policy numpy || rpm -q numpy || numpy --version

2. UPGRADE to newer than 1.16.0 (Debian / Ubuntu)

sudo apt update && sudo apt install --only-upgrade numpy

2. UPGRADE (RHEL / Amazon Linux / Fedora)

sudo dnf upgrade numpy

Note

Distros often backport fixes without changing the version number. Confirm with the distro advisory or changelog.

fedoraproject fedora MITIGATE

Affected: 30

Fixed in: no fixed release known

Safe to downgrade to: a release before 30

Check your OS release

cat /etc/os-release; uname -r

Debian / Ubuntu

sudo apt update && sudo apt full-upgrade

RHEL / Amazon Linux / Fedora

sudo dnf upgrade --refresh

Windows

Install the latest cumulative update from Windows Update

If no patch exists yet

OS downgrades are not safe. Apply the vendor mitigation from the advisory and restrict exposure.

Exact fixes by distribution

A distro patch exists: prefer upgrading over downgrading.

Python (pip) · numpy · FIXED · 1.16.3 · vulnerable: < 1.16.3 · source

pip install --upgrade "numpy>=1.16.3" pip show numpy

Fedora 46 · libopenmpt · FIXED · 0.8.10-2.fc46 · FEDORA-2026-a9998621be · source

sudo dnf upgrade --advisory=FEDORA-2026-a9998621be

RHEL 8 · numpy · FIXED · numpy-1.14.3-9.el8

sudo dnf upgrade --advisory=RHSA-2019:3704 rpm -q numpy

RHEL 6 · numpy · DEFERRED

RHEL 7 · numpy · DEFERRED

Public exploits and detection

Public code exists for this CVE. Treat unpatched systems as at risk, and only run PoCs in a lab.

GitHub PoC: RayScri/CVE-2019-6446 (3 stars)

Verify at the official source NVD · CVE Program · Report a problem with this page
Scores and fixes here are computed automatically from those and other public sources. Confirm with the vendor advisory before changing production systems.

Quick answers

How do I fix CVE-2019-6446?

numpy: upgrade to newer than 1.16.0; fedora: mitigate or apply the listed mitigation. Exact commands for each OS are on this page.

Is CVE-2019-6446 being exploited?

CVE-2019-6446 is not on the CISA Known Exploited Vulnerabilities list at the time of the last update. Check again, as this can change.

What does CVE-2019-6446 affect?

CVE-2019-6446 affects numpy, fedora. Severity is critical (CVSS 9.8). 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 di

How urgent is CVE-2019-6446?

Priority 69/100. Critical severity; EPSS top 2%: very likely to be exploited; Public exploit reference; Remotely exploitable, no login, no user action

Software pages

Python vulnerabilities · Pandas and NumPy vulnerabilities

Related CVEs

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References

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