An AI security team that maps, tests, validates, and reports.
ScanRub combines an automated scanner with research mined from real disclosures - and an AI validation gate so you only see findings that matter.
Point the scanner at a domain. It maps the attack surface and runs a multi-stage pipeline - picking tools, chasing leads, and narrating progress in real time.
Subdomain enumeration, live-host probing, technology fingerprinting, and URL discovery feed the scanner a complete picture before it tests.
A planner orders 25 security tools by the detected stack and prior findings, so the highest-value checks run first.
Every finding passes an LLM validation step that reclassifies severity and filters false positives before it reaches your report.
A transparent quality score tells you how thorough a scan was - coverage, depth, and confidence at a glance.
Each finding ships with proof, affected location, impact, and remediation - ready to paste into a ticket or report.
Detection strategies are derived from thousands of disclosed reports, so checks reflect how bugs are actually found in the wild.
From SSRF and IDOR to request smuggling and race conditions, mapped to CWE and OWASP.
The scanner connects related issues into exploit chains that show real, demonstrable impact.
Track findings over time and compare scans to see what changed between releases.
Run recurring scans and get notified the moment something new and serious appears.
Gate pull requests on new vulnerabilities - wire ScanRub into your pipeline with an API key and block the merge before a regression ships.
Tenancy isolation and clear authorization requirements keep testing in scope.
See it find real bugs
Run a scan in the live demo, or explore the research behind the detections.