Three detection layers that disagree usefully, and why they combine by max, not sum

Features get you a vector per window. Turning that into a decision is where the design choices are. This system scores every window three independent ways and takes the strongest single case. Each layer covers a failure mode of the others. Layer 1: guardrails Deterministic thresholds, no baseline of any kind: // Honeytoken hit — highest-confidence signal. Immediate revoke. if ( fv . honeytoken_hits > 0 ) add ( 100 , ' honeytoken_hits ' , ' … ' ); // High miss ratio — guessing IDs that mostly do…