Developer Needed — Automated Regression Test Harness for Fraud Detection Engine
Publicada el 2026-07-23
Descripción de la oferta
Project Overview We have an in-house fraud/risk detection system that scores signals like proxy usage, VPN usage, device fingerprint risk, bot probability, and location spoofing (similar to tools like Fingerprint/Seon). We need an automated test harness that validates our detection engine against known-labeled test cases, so we catch regressions every time we update our rules or models. What This Is NOT This is not live evasion testing against production. All test data is pre-labeled, synthetic, and sourced from public reference data (known proxy/VPN IP ranges, published emulator fingerprint signatures, etc.). No real user data, no production access required. Scope of Work Build a fixture library of labeled test cases across categories: proxy, vpn, device_risk, location_spoofing, bot, and clean (control cases expected to score low) Build a test runner that feeds each fixture to our detection API and compares actual output against expected output Track both false negatives (missed risk) and false positives (over-flagged clean cases) separately Integrate into our CI pipeline so it runs automatically on every PR/deploy Output a clear pass/fail summary report per category Requirements Experience building automated test suites / CI pipelines Comfortable working with JSON fixtures and REST APIs Familiarity with fraud/risk detection concepts is a plus, not required Clean, documented, maintainable code (this becomes a long-term internal QA tool) Deliverables Fixture library (JSON, ~15-20 cases per category to start, extensible) Test runner + CI integration Summary report format (pass/fail, false positive vs false negative breakdown) Short doc on how to add new fixtures going forward
Skills
Fuente original: freelancer