Which versions of tronapipy are malicious?

The following PyPI versions of tronapipy are flagged malicious: 0.0.1. Treat any of these as compromised.

How do I remediate tronapipy if I installed it?

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

If tronapipy was installed, its post-install payload may already have run. Removing the package does not undo that — check outbound connections and credential use from the install window onward.

Is tronapipy part of a known attack campaign?

Yes — tronapipy is associated with the RLMA-2025-03705, 2025-04-tronix, RLUA-2026-00839 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 tronapipy across my projects, lockfiles, and CI pipelines?

Search your lockfiles and build artifacts for tronapipy (version 0.0.1).

Part of a larger attack: 2025-04-tronix published 67 malicious packages. See the full campaign →

Malicious package

tronapipyPyPI

Advisory published Apr 28, 2025Updated Mar 19, 2026

tronapipy is a confirmed malicious PyPI package (MAL-2025-6606) that steals credentials and exfiltrates sensitive data (malicious version 0.0.1). Do not install it — remove it immediately and rotate any exposed credentials.

Malicious code in tronapipy (PyPI)

MAL-2025-6606

Immediate action

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

pip uninstall tronapipy

What this malware does

Package appears to be designed for private key exfiltration, but no known usage. The name appears to be related to the cryptocurrency TRX (Tron / Tronix). Some packages additionally clone the readme of other, legit libraries. The similar packages are repeating uploaded to PyPI

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

Campaign: 2025-04-tronix

Reasons (based on the campaign):

exfiltration-generic
crypto-related

Malicious versions

1 flagged

0.0.1

Indicators of compromise (SHA-256)

fa081dbc288e7484e0e0425b26ae874faab190a8bf1ed163d0cb6e4de0f18fb2

c78fe33c5b694a492a295abdfc5224c6977a846cf5ec1e8f1265dafab0758ea8

f708be2fc70e3c2c9dc79ee1706944cb73f9604b496c4171a5971f5c6e0091fe

62107d205608f1909664d5bd1804f61f96c42faf7199a3e208f46de2c6fdadba

8928b5e3b147f92d29ce0e802a448cb955626faa2fc5ec5d3e6adae4cdbdc5ff

Detection & response playbook

Credential / info stealer

Find it
Search your lockfiles and build artifacts for tronapipy (version 0.0.1).
If you installed it — respond
tronapipy 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 tronapipy was installed, its post-install payload may already have run. Removing the package does not undo that — check outbound connections and credential use from the install window onward.

Frequently asked questions

No. tronapipy on PyPI has been identified as a malicious package (version 0.0.1 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

RLMA-2025-037052025-04-tronixRLUA-2026-00839

References

Credits

Kamil Mańkowski (kam193)
ReversingLabs · finder

Detect & block this

O3 blocks tronapipy-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

All malware advisories How O3 detects malware Vulnerability database