Which versions of tensorflowlitex are malicious?

The following PyPI versions of tensorflowlitex are flagged malicious: 0.1.7. Treat any of these as compromised.

How do I remediate tensorflowlitex if I installed it?

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

If tensorflowlitex 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 tensorflowlitex part of a known attack campaign?

Yes — tensorflowlitex is associated with the 2025-04-tensorflowlitex 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 tensorflowlitex 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 tensorflowlitex (version 0.1.7). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging tensorflowlitex across your stack and pipelines.

Malicious package

tensorflowlitexPyPI

Malicious code in tensorflowlitex (PyPI) Remove it immediately and rotate any exposed credentials.

MAL-2025-191890

Immediate action

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

pip uninstall tensorflowlitex

What this malware does

Importing the module (init.py) starts downloading and executing a remote exectuable, which has been identified by any.run and tria.ge as a malicious infostealer

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

Campaign: 2025-04-tensorflowlitex

Reasons (based on the campaign):

Downloads and executes a remote executable.
exfiltration-browser-data
infostealer
malware
typosquatting

Malicious versions

1 flagged

0.1.7

Indicators of compromise (SHA-256)

1f8c546b796531a1fcf06e705691909563fce6128815b2d4a8f9333c1cb967fd

c4b20463291f0bcc715ff6daffb6b2cc258096921b2aaf2a0b9bf96947b49b46

40762c570ef9125e0eb16acd8ede71c1c50493437fd459ddffd584aab1bcba26

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 tensorflowlitex (version 0.1.7). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging tensorflowlitex across your stack and pipelines.
If you installed it — respond
tensorflowlitex 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 tensorflowlitex 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 tensorflowlitex 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. tensorflowlitex on PyPI has been identified as a malicious package (version 0.1.7 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

2025-04-tensorflowlitex

References

Credits

Kamil Mańkowski (kam193)

Detect & block this

O3 blocks tensorflowlitex-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