Which versions of nebulix-ai are malicious?

The following PyPI versions of nebulix-ai are flagged malicious: 1.0.0, 1.0.3. Treat any of these as compromised.

How do I remediate nebulix-ai if I installed it?

nebulix-ai 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 nebulix-ai — how do I know if it already compromised me?

If nebulix-ai 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 nebulix-ai part of a known attack campaign?

Yes — nebulix-ai is associated with the IN-MAL-2026-003277, IN-MAL-2026-003278 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 nebulix-ai 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 nebulix-ai (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging nebulix-ai across your stack and pipelines.

Malicious package

nebulix-aiPyPI

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

MAL-2026-4758

Immediate action

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

pip uninstall nebulix-ai

What this malware does

The package's documented NebulixEngine.chat() API hardcodes two Firebase Realtime Database URLs owned by the author (fcmm-48870-default-rtdb.firebaseio.com and tappu-76693-default-rtdb.firebaseio.com) as the destination for caller-supplied data. On engine instantiation the user-provided auth_token is sent to the author's auth database; during chat(), session['history'] (last 50 user queries), user_name, and custom_knowledge are written via requests.put to the author's database keyed by the user's token (nebulix/engine.py lines 33-38 and 472). Any developer integrating this library silently exfiltrates their end users' chat content, names, and custom knowledge entries to the author's Firebase project. The behavior is not disclosed in README or package metadata, and the destination is not configurable — it is the canonical silent-relay shape, where normal use of the advertised API leaks caller data to a hardcoded third-party endpoint. Two embedded Firebase Web API keys are public-by-design identifiers (not credentials) and are noted only as corroborating context that the author's database is the relay target.

Malicious versions

2 flagged

1.0.01.0.3

Indicators of compromise (SHA-256)

7bc662c864e83242155c49a3177a62c71655266294880723d71664e112250cc0

93ea83117b0ae362a2b55ad581d69b3600c81b78d2e90c19bb1ea9eea2266a4c

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 nebulix-ai (2 malicious versions). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging nebulix-ai across your stack and pipelines.
If you installed it — respond
nebulix-ai 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 nebulix-ai 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 nebulix-ai 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. nebulix-ai on PyPI has been identified as a malicious package (versions 1.0.0, 1.0.3 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

IN-MAL-2026-003277IN-MAL-2026-003278

References

Credits

Amazon Inspector · finder

Detect & block this

O3 blocks nebulix-ai-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