anti-bot-engine
Signal-based bot detection layer using behavioral fingerprinting and adaptive challenges.
Purpose
Bot detection is often reduced to IP blocking or CAPTCHAs. anti-bot-engine takes a different approach: collect behavioral signals during normal interaction and use them to score requests without interrupting real users.
The system issues adaptive challenges only when signals cross a threshold, keeping friction low for humans and cost high for automation.
Tech Stack
Language
Runtime
Focus
Project Timeline
Research into behavioral fingerprinting techniques began.
Basic signal collection and scoring logic implemented.
Replaced synchronous checks with an async challenge pipeline.
Repository made public with core fingerprinting module.
Active. Fingerprinting and challenge system are functional.
ML scoring model, edge middleware integration, dashboard.
Current Progress
GitHub
Repository metadata placeholders for future API integration.
2026-06-18
2026-07-20
Prototype
public
github.com/d3f4lt0/anti-bot-engine
README
TypeScript
Signal-based bot detection layer using behavioral fingerprinting and adaptive challenges.