Which versions of causal-canvas are malicious?

The following PyPI versions of causal-canvas are flagged malicious: 99.0.0. Treat any of these as compromised.

How do I remediate causal-canvas if I installed it?

causal-canvas 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 causal-canvas — how do I know if it already compromised me?

If causal-canvas 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 causal-canvas part of a known attack campaign?

Yes — causal-canvas is associated with the GENERIC-standard-pypi-install-pentest, GENERIC-hackerone-bugbounty 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 causal-canvas 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 causal-canvas (version 99.0.0). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging causal-canvas across your stack and pipelines.

Malicious package

causal-canvasPyPI

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

MAL-2026-1294

Immediate action

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

pip uninstall causal-canvas

What this malware does

Installing the package or importing the module exfiltrates basic information about the host, and the package has no other purpose.

Category: PROBABLY_PENTEST - Packages looking like typical pentest packages, but also anything that looks like testing, exploring pre-prepared kits, research & co, with clearly low-harm possibilities.

Campaign: GENERIC-standard-pypi-install-pentest

Reasons (based on the campaign):

The package contains code to exfiltrate basic data from the system, like IP or username. It has a limited risk.
The package overrides the install command in setup.py to execute malicious code during installation.

The OpenSSF Package Analysis project identified 'causal-canvas' @ 99.0.0 (pypi) as malicious.

It is considered malicious because:

The package communicates with a domain associated with malicious activity.

Malicious versions

1 flagged

99.0.0

Indicators of compromise (SHA-256)

29d40dc740a5e270e319661e2e5c80d03b4bc01a7a306e930f82ace29699520e

ecab11884e9f4226d493a759dd7039ee4669a904d1834041fb73c81502fe4f27

a973113293bb5a543ff2dce4b700a2274baab554d942e85de5c7657a809c85da

6de677ccf6f8af6c953f615c1f5955785338aced92e082ba5593409409ee45f9

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 causal-canvas (version 99.0.0). O3 Security's supply-chain scanner checks every dependency against known-malicious package intelligence at install time and in CI, flagging causal-canvas across your stack and pipelines.
If you installed it — respond
causal-canvas 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 causal-canvas 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 causal-canvas 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. causal-canvas on PyPI has been identified as a malicious package (version 99.0.0 flagged). It should be removed immediately — do not install or keep it in your dependency tree.

Campaign

GENERIC-standard-pypi-install-pentestGENERIC-hackerone-bugbounty

References

bad-packages.kam193.eu

Credits

Kamil Mańkowski (kam193) · reporter
OpenSSF: Package Analysis · finder

Detect & block this

O3 blocks causal-canvas-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