This is a self-contained tool for detecting third-party AI API model substitution by analyzing the statistical fingerprint of random number generation. The backend is a Python proxy server (http.server) that forwards requests to OpenAI/Anthropic endpoints, handles GitHub baseline retrieval with caching, and provides an auto-update mechanism. The frontend is a single HTML file with embedded JavaScript (no bundler) that handles all user interaction: calibration of official models, testing of unknown channels, quick one-click verification against pre-downloaded baselines, and multi-channel comparison. The tool uses cosine similarity and Jensen-Shannon divergence to compare distributions, with special handling for model-specific parameters (max_tokens vs max_completion_tokens). The code is functional and well-organized for a single-developer tool, but lacks modularity (everything in one HTML file, backend in one script) and has no test suite. The baseline data files are precomputed artifacts, not part of a live data pipeline.