Ghostprint

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.

Depersonalize your LLM usage. Introduce noise. Prevent fingerprinting.

Install as OpenClaw Plugin

bash

git clone https://github.com/alarawms/ghostprint ~/.openclaw/extensions/ghostprint
openclaw plugins enable ghostprint
openclaw gateway restart

Usage

Once installed, these agent tools are available in any session:

• ghostprint_fire — fire a noise round immediately
• ghostprint_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)

bash

cp config.example.yaml config.yaml
# edit config.yaml with your API keys
python3 ghostprint.py --run-once
python3 ghostprint.py --install-cron

Cost

< $0.35/month at 3× daily across Anthropic + Z.ai.

Source

https://github.com/alarawms/ghostprint