- name
- ghostprint
- description
- LLM fingerprint noise injector. Sends behaviorally realistic randomized queries to Anthropic, Z.ai, and any OpenAI-compatible provider on a schedule to depersonalize your usage profile and prevent behavioral fingerprinting. Available as a native OpenClaw plugin (no extra config — reuses your existing provider keys) and a standalone Python script.
- version
- 3.0.0
Ghostprint
Depersonalize your LLM usage. Introduce noise. Prevent fingerprinting.
Install as OpenClaw Plugin
git clone https://github.com/alarawms/ghostprint ~/.openclaw/extensions/ghostprint
openclaw plugins enable ghostprint
openclaw gateway restartUsage
Once installed, these agent tools are available in any session:
ghostprint_fire— fire a noise round immediatelyghostprint_stats— show run history and stats
The background scheduler fires automatically every ~2 hours (Poisson-distributed).
How it works
- 6 personas with stable domain preferences and multi-turn rates
- 300+ topics across 12 domains (cooking, health, science, DIY, tech, finance, language, travel, psychology, history, lifestyle)
- Contextual follow-ups — multi-turn sessions use topic-paired follow-ups
- Poisson timing — exponentially distributed inter-arrival times
- Activity weights — suppressed during sleep hours, lighter on weekends
- Metadata-only logs — never logs topic text or reply content
- No config needed — reuses your existing OpenClaw provider credentials
Standalone (no OpenClaw)
cp config.example.yaml config.yaml
# edit config.yaml with your API keys
python3 ghostprint.py --run-once
python3 ghostprint.py --install-cronCost
< $0.35/month at 3× daily across Anthropic + Z.ai.
Source
https://github.com/alarawms/ghostprint