High-fidelity vulnerability scanner fusing agentic AI with native speed, modularity, and precision.
Deterministic, multi-phase scanning with active and passive modules. Content discovery, browser spidering, SPA crawling, SAST, and audit — all in one pipeline.
AI agents autonomously plan attacks, select modules, generate custom payloads, and triage results. Powered by Claude, Codex, Gemini, or OpenCode.
Core engine written in Go. Configurable worker pools with per-host rate limiting and hybrid in-memory/disk/Redis queues.
Agents write custom checks on the fly via an embedded JS engine. Discover and load sessions during scans with session-aware HTTP APIs and multi-step auth flows.
Feed targets via URLs, OpenAPI specs, Postman collections, Burp exports, cURL commands, or live proxy traffic.
Run native scans with strategy presets, or let AI agents autonomously discover endpoints and orchestrate attacks.
Get findings with full request/response evidence, confidence scoring, and exportable HTML reports.
XSS (reflected, DOM, SSR), SQLi, NoSQL, SSTI, command injection, XXE, prototype pollution
CSRF, IDOR, authorization bypass, mass assignment, HTTP method tampering
GraphQL introspection, SSRF, open redirect, request smuggling, JWT flaws, race conditions
Spring Boot, Django, Laravel, Rails, Express, Next.js, Nuxt, ASP.NET, Flask, FastAPI
Firebase, cloud storage takeover, default credentials, web cache poisoning, CORS misconfiguration
Agents continuously learn from scan results, refining detection strategies and adapting to new attack surfaces
Scanner modules — active and passive
Native scan phases
Agentic scan phases
Frameworks with dedicated scanners
Agent learning capacity — always evolving
GitHub Actions, GitLab CI, Jenkins
Import/export Burp XML traffic
REST API with Swagger UI and traffic ingestion
Auto-ingest API specifications
Claude, Codex, Gemini, OpenCode, Cursor via Agent SDK
Managed scanning infrastructure, team collaboration, and continuous monitoring — all without self-hosting.