AI Model Identity Fingerprint
Overview
A structured multi-stage protocol to determine an AI model's true identity by cross-referencing self-reported claims against knowledge boundary probes, capability tests, behavioral analysis, and self-consistency analysis. Produces a standardized identification report with confidence scoring.
This protocol incorporates techniques from recent academic research (2024-2026) on LLM fingerprinting, including behavioral patterns, timing analysis, and stati
[Description truncada. Veja o README completo no GitHub.]