Which versions of mlflow-ui are malicious?

The following PyPI versions of mlflow-ui are flagged malicious: 2.7.1, 2.7.2, 2.7.3. Treat any of these as compromised.

How do I remediate mlflow-ui if I installed it?

mlflow-ui 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 mlflow-ui — how do I know if it already compromised me?

If mlflow-ui 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 mlflow-ui part of a known attack campaign?

Yes — mlflow-ui is associated with the 2026-07-mlflow-ui 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 mlflow-ui 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 mlflow-ui (3 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging mlflow-ui across your stack and pipelines.

Malicious package

mlflow-uiPyPI

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

MAL-2026-10779

Immediate action

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

pip uninstall mlflow-ui

What this malware does

During installation, the package first collects local information, environment variables, and probes connections to typically expected services like databanks. Results are exfiltrated and then, the next stage code is downloaded and executed. It then continues exfiltrating data by looking for credentials to databases, exfiltrating SQLite databases and bruteforcing&exfiltrating other databases reachable from the running environment.

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

Campaign: 2026-07-mlflow-ui

Reasons (based on the campaign):

files-exfiltration
exfiltration-env-variables
dependency-confusion
Downloads and executes a remote malicious script.
exfiltration-credentials
network-scan
exfiltration-cloud-tokens

Malicious versions

3 flagged

2.7.12.7.22.7.3

Indicators of compromise (SHA-256)

efedaf471fdd5b95baee95d9bd0d330c8ce0f5da06b5cdf89458fd4ea7a38015

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 mlflow-ui (3 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging mlflow-ui across your stack and pipelines.
If you installed it — respond
mlflow-ui 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 mlflow-ui 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 mlflow-ui 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. mlflow-ui on PyPI has been identified as a malicious package (versions 2.7.1, 2.7.2, 2.7.3 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

2026-07-mlflow-ui

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193) · reporter

Detect & block this

O3 blocks mlflow-ui-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