Which versions of jd-mlops are malicious?

The following PyPI versions of jd-mlops are flagged malicious: 0.1, 99.99.99. Treat any of these as compromised.

How do I remediate jd-mlops if I installed it?

jd-mlops 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 jd-mlops — how do I know if it already compromised me?

If jd-mlops 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 jd-mlops part of a known attack campaign?

Yes — jd-mlops is associated with the RLMA-2025-03621, GENERIC-standard-pypi-install-pentest, RLUA-2026-00440 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 jd-mlops 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 jd-mlops (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging jd-mlops across your stack and pipelines.

Malicious package

jd-mlopsPyPI

Malicious code in jd-mlops (PyPI) Remove it immediately and rotate any exposed credentials.

MAL-2025-6528

Immediate action

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

pip uninstall jd-mlops

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

2 flagged

0.199.99.99

Indicators of compromise (SHA-256)

9a0de724ce87ad60094b5710f08786f55eda20a8caf7712772e4326816fb102e

18ddbbdf19fa08f5ef1f3bff65d4a8954581dd63e21096b9ed584a79772ee39c

27e0c1b0bb778a762b23a541daa571391b073db56f64e90af5a403dffe5bbff3

0f50883ca04eaf09354a2c15a90a2ca77ad246c0ecef232ed43388098e465756

6a92e5f7445cbcc22fac4a05561357b07258e068ad7eb7ee0102adf85d98be07

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 jd-mlops (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging jd-mlops across your stack and pipelines.
If you installed it — respond
jd-mlops 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 jd-mlops 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 jd-mlops 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. jd-mlops on PyPI has been identified as a malicious package (versions 0.1, 99.99.99 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

RLMA-2025-03621GENERIC-standard-pypi-install-pentestRLUA-2026-00440

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193)
ReversingLabs · finder

Detect & block this

O3 blocks jd-mlops-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