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Malicious package

mlflow-uiPyPI

mlflow-ui is a confirmed malicious PyPI package (MAL-2026-10779) that steals credentials and exfiltrates sensitive data (malicious versions 2.7.1, 2.7.2, 2.7.3). Do not install it — remove it immediately and rotate any exposed credentials.

Malicious code in mlflow-ui (PyPI)

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

The package impersonates the MLflow project (author 'MLflow Community' [email protected], homepage https://github.com/mlflow/mlflow) but provides no MLflow UI functionality. Both setup.py (install time) and mlflow_ui/init.py (import time) execute payload_core.py, which collects hostname, platform, the full process environment (dict(os.environ)), /etc/hosts, /etc/resolv.conf, /proc/self/cgroup, /proc/1/cmdline, directory listings of /, /app, /opt, /srv, /home, /tmp, and the output of id, ps aux, and ip addr, along with internal-network probe results. The data is base64-encoded and POSTed to https://webhook.site/9510ba0a-29f7-4ce6-afe7-632c92cf0f41/piprecon over TLS with verification disabled (ssl.create_unverified_context()). The same module fetches a second-stage Python payload from https://webhook.site/a9f5802b-c77e-4226-99dd-bc89d7dc8cca/s2.py and passes the bytes to compile()+exec() with subprocess and os bound in globals, yielding arbitrary remote code execution on the installer's host at both install and import time. Bulk environment scraping captures AWS*, GH_TOKEN, npm/PyPI tokens, database URLs, and any other CI/build secrets present.

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
77ab1bbfc9287ae255dbdbd3284995c4955261b11b78b6d25fb6521b69ec7469
b7192c53fc1e0b62e2c373a8a6beabfeb3777cae3aacfe23ca374eab1c2839a7

Detection & response playbook

Credential / info stealer
  1. 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.

  2. 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.

  3. 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.

  4. 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-uiIN-MAL-2026-010890IN-MAL-2026-010889

References

Credits

  • Amazon Inspector · finder
  • 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.

Explore

mlflow-ui (PyPI) malicious package — MAL-2026-10779 | O3 Security