Which versions of habitmf are malicious?

The following PyPI versions of habitmf are flagged malicious: 99.7. Treat any of these as compromised.

How do I remediate habitmf if I installed it?

habitmf 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 habitmf — how do I know if it already compromised me?

If habitmf was ever installed, its post-install/runtime payload may have already executed. O3's L7 egress monitoring and runtime eBPF sensors detect the credential exfiltration or command-and-control callback after install and block the malicious outbound channel, so you catch and contain the actual compromise — not just the presence of the package.

Is habitmf part of a known attack campaign?

Yes — habitmf is associated with the 2024-11-byted-dast 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 habitmf across my projects, lockfiles, and CI pipelines?

Scan your lockfiles (package-lock.json, pnpm-lock.yaml, yarn.lock, requirements.txt, poetry.lock, etc.) and build artifacts for habitmf (version 99.7). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging habitmf across your stack and pipelines.

Malicious package

habitmfPyPI

Malicious code in habitmf (PyPI) Remove it immediately and rotate any exposed credentials.

MAL-2024-10416

Immediate action

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

pip uninstall habitmf

What this malware does

A campaign of probably pentest packages flooding PYPI. Installing the package or importing the module triggers reporting basic info like hostname, path and the username to the package author. There is no other purpose of the package.

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: 2024-11-byted-dast

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.
typosquatting
dependency-confusion

The OpenSSF Package Analysis project identified 'habitmf' @ 99.7 (pypi) as malicious.

It is considered malicious because:

The package communicates with a domain associated with malicious activity.

Malicious versions

1 flagged

99.7

Indicators of compromise (SHA-256)

eb9394908f6f8771c056f2934475dbb2b4c48c7dd4d3d58b0512cdb0d18ab9ae

25c1d7f30482a6186ab9a0de8b0a7fe3487e86201266fef1c7de62060498fa45

d09f18707694764b32bb61823442ab1a1162ee3bc38eb29849dcdbbe8a326271

54e8aea9c43d091dcd73d2907fcc29d8f6f8fe7b47c20e27dd1ef337c017f9e4

Detection & response playbook

Credential / info stealer

Find it
Scan your lockfiles (package-lock.json, pnpm-lock.yaml, yarn.lock, requirements.txt, poetry.lock, etc.) and build artifacts for habitmf (version 99.7). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging habitmf across your stack and pipelines.
If you installed it — respond
habitmf 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 habitmf was ever installed, its post-install/runtime payload may have already executed. O3's L7 egress monitoring and runtime eBPF sensors detect the credential exfiltration or command-and-control callback after install and block the malicious outbound channel, so you catch and contain the actual compromise — not just the presence of the package.
How O3 protects you
O3 blocks habitmf before install through its supply-chain scanner, and if it has already run, detects and severs the exfiltration or C2 callback at runtime through L7 egress monitoring and eBPF.

Frequently asked questions

No. habitmf on PyPI has been identified as a malicious package (version 99.7 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

2024-11-byted-dast

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193)
OpenSSF: Package Analysis · finder

Detect & block this

O3 blocks habitmf-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