Some requests never reach the model
gate.ts short-circuits allowlisted paths/IPs and cryptographically verified clients. Their zero-risk records are local policy outcomes, not model confidence measurements.
Inspect the supporting source ↗A Node/Python HTTP request gate combining local allowlists and verification with optional TypeSafe questions about bot behavior, attacks, spoofing, traffic category and risk.
traffic-guard progressively evaluates requests against TypeSafe System One using Noul (`is_bot`, `is_attack`, `is_spoofed`), Choice (`traffic_type`), and Score (`risk_level`).
Adds structured choices or scores to the workflow; performance and cost benefits have not been independently verified.
Pinned gate and policy code reviewed. Short-circuit allow decisions are local outcomes; configured API-outage behavior can differ, and some missing-answer fields receive defaults. No WAF, throughput or bot-detection benchmark was reproduced here.
Combine deterministic request screening and a model-based HTTP traffic assessment.
Material analysed:
gate.ts short-circuits allowlisted paths/IPs and cryptographically verified clients. Their zero-risk records are local policy outcomes, not model confidence measurements.
Inspect the supporting source ↗The gate exposes allow/block fallback options and assigns low-risk defaults for some missing answer fields. A deployment must test these paths explicitly instead of treating every returned assessment as a full model result.
Inspect the supporting source ↗Useful for studying staged request gates. Put rate limits and protocol validation ahead of probabilistic screening, and choose an outage policy that matches the application's risk.
Trace gate.ts's short-circuits, answer defaults and fallback catch, then compare policy.ts for good-bot and honeypot branches using synthetic HTTP metadata.