Which versions of matlibplot are malicious?

The following PyPI versions of matlibplot are flagged malicious: 0.3. Treat any of these as compromised.

How do I remediate matlibplot if I installed it?

matlibplot is built to steal secrets, so assume every credential the build or runtime could read is compromised. Remove it from your project and lockfile, then rotate ALL exposed secrets — npm/registry tokens, cloud keys, CI/CD secrets, SSH keys, and any .env values — from a known-clean machine. Audit logs for unauthorized use of those credentials.

I already installed matlibplot — how do I know if it already compromised me?

If matlibplot was installed, its post-install payload may already have run. Removing the package does not undo that — check outbound connections and credential use from the install window onward.

Is matlibplot part of a known attack campaign?

Yes — matlibplot is associated with the RLMA-2024-11085, GENERIC-standard-pypi-install-pentest, RLUA-2026-00499 campaign. Packages in the same campaign often share infrastructure and payloads, so check whether any related packages are also in your dependency tree.

How do I find matlibplot across my projects, lockfiles, and CI pipelines?

Search your lockfiles and build artifacts for matlibplot (version 0.3).

Malicious package

matlibplotPyPI

Advisory published Jul 26, 2024Updated Mar 19, 2026

matlibplot is a confirmed malicious PyPI package (MAL-2024-11630) that steals credentials and exfiltrates sensitive data (malicious version 0.3). Do not install it — remove it immediately and rotate any exposed credentials.

Malicious code in matlibplot (PyPI)

MAL-2024-11630

Immediate action

Remove the package, then rotate any secrets the build/runtime could reach.

pip uninstall matlibplot

What this malware does

Installing the package or importing the module exfiltrates basic information about the host, and the package has no other purpose.

Category: PROBABLY_PENTEST - Packages looking like typical pentest packages, but also anything that looks like testing, exploring pre-prepared kits, research & co, with clearly low-harm possibilities.

Campaign: GENERIC-standard-pypi-install-pentest

Reasons (based on the campaign):

The package contains code to exfiltrate basic data from the system, like IP or username. It has a limited risk.
The package overrides the install command in setup.py to execute malicious code during installation.

Malicious versions

1 flagged

0.3

Indicators of compromise (SHA-256)

9f0477f858af87764b6e9c7486403bbfc93331b47027f3616f37c2390c2f74c8

7651107d5574ccec82e018bafbcd461fc8ba9ea402bcc3cb8ce035927be9fce8

b675638019d08df47348aa16973f4b46c50ffad23b83f5a125b19d30fd90825a

88aefb022ab10a434b1af4343b9b06e460653d280c7db578970f4786d5688278

799dd41ef0b7f9f7a91cdd927db4ebd53813af5751b1e147aa3626be8a2db017

Detection & response playbook

Credential / info stealer

Find it
Search your lockfiles and build artifacts for matlibplot (version 0.3).
If you installed it — respond
matlibplot is built to steal secrets, so assume every credential the build or runtime could read is compromised. Remove it from your project and lockfile, then rotate ALL exposed secrets — npm/registry tokens, cloud keys, CI/CD secrets, SSH keys, and any .env values — from a known-clean machine. Audit logs for unauthorized use of those credentials.
Did it already run?
If matlibplot was installed, its post-install payload may already have run. Removing the package does not undo that — check outbound connections and credential use from the install window onward.

Frequently asked questions

No. matlibplot on PyPI has been identified as a malicious package (version 0.3 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

RLMA-2024-11085GENERIC-standard-pypi-install-pentestRLUA-2026-00499

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193)
ReversingLabs · finder

Detect & block this

O3 blocks matlibplot-class packages before install and in CI — and if it already ran, its runtime egress monitoring catches the credential exfiltration and severs the channel.

Malware detection Runtime egress monitoring

Explore

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