ARL-Next
A modern attack-surface reconnaissance and asset-intelligence platform, rebuilt from the classic ARL project with an async microservice architecture and a native Model Context Protocol server for AI-assisted analysis.
ARL-Next re-architects the original ARL (Asset Reconnaissance Lighthouse) project to fix engineering bottlenecks in large-scale scanning: task-queue blocking, growing memory use during long runs, and outdated dependencies. It splits OSINT collection and screenshotting into independent microservices with separated light and heavy task queues and batched database writes, and upgrades the stack to Python 3.13, Vue 3.5, MongoDB 7.0 and Nmap 7.95.
It groups enterprise assets across multi-level organizational structures, correlating websites, apps, mini-programs and quick apps into a unified exposure map, and integrates Nuclei with more than 100 vulnerability proof-of-concept plugins and an 8,800-entry web fingerprint library. A native MCP server, built on the Python standard library, exposes thirteen dimensions of asset data for automated retrieval and AI-assisted analysis, and it continuously syncs CVE intelligence and monitors GitHub for leaked code and credentials.