False positives don’t just waste time - they erode trust, delay remediation, and bury real issues under a pile of noise.
That’s why we’ve built and integrated the Machine Learning classifier - a purpose-trained machine learning model - directly into our Website Scanner and URL Fuzzer.
Instead of relying on brittle RegEx logic, the ML Classifier analyzes every HTML response during a scan and automatically sorts it into one of four smart categories:
📌 HIT – High-value targets like login pages, exposed secrets, and backups
📌 MISS – Confirmed dead ends, even when status codes are misleading
📌 PARTIAL HIT – Ambiguous but interesting results (like firewall pages or redirects)
📌 INCONCLUSIVE – Requires browser-based rendering for confirmation
This means you can quickly focus on what matters, reduce triage time, and get clearer, cleaner results.