Which versions of ml-fdbk-shared are malicious?

The following PyPI versions of ml-fdbk-shared are flagged malicious: 1.0.0, 2.3.1. Treat any of these as compromised.

How do I remediate ml-fdbk-shared if I installed it?

ml-fdbk-shared 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 ml-fdbk-shared — how do I know if it already compromised me?

If ml-fdbk-shared 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 ml-fdbk-shared part of a known attack campaign?

Yes — ml-fdbk-shared is associated with the 2026-07-ml-shared 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 ml-fdbk-shared 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 ml-fdbk-shared (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging ml-fdbk-shared across your stack and pipelines.

Malicious package

ml-fdbk-sharedPyPI

ml-fdbk-shared is a confirmed malicious PyPI package (MAL-2026-11200) that steals credentials and exfiltrates sensitive data (malicious versions 1.0.0, 2.3.1). Do not install it — remove it immediately and rotate any exposed credentials.

Malicious code in ml-fdbk-shared (PyPI)

MAL-2026-11200

Immediate action

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

pip uninstall ml-fdbk-shared

What this malware does

During installation, package exfiltrates basic info and all environmental variables.

Category: MALICIOUS - The campaign has clearly malicious intent, like infostealers.

Campaign: 2026-07-ml-shared

Reasons (based on the campaign):

exfiltration-env-variables
The package contains code to exfiltrate basic data from the system, like IP or username. It has a limited risk.

Malicious versions

2 flagged

1.0.02.3.1

Indicators of compromise (SHA-256)

2f2313f59d10884a764cb2e2dbfe3aa8ae97545c995785f65ca1e856b4a29b8c

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 ml-fdbk-shared (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging ml-fdbk-shared across your stack and pipelines.
If you installed it — respond
ml-fdbk-shared 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 ml-fdbk-shared 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 ml-fdbk-shared 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. ml-fdbk-shared on PyPI has been identified as a malicious package (versions 1.0.0, 2.3.1 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

2026-07-ml-shared

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193) · reporter

Detect & block this

O3 blocks ml-fdbk-shared-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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