owl234/ARL-Next

🚀 自动化资产侦察与漏洞监控平台 (ARL-Next)。重构自经典 ARL，全面升级 Puppeteer + Nuclei 引擎，打通「天眼查/ICP ➔ 资产发现 ➔ 漏洞扫描 ➔ 威胁情报追踪」安全闭环。支持 Docker 极简部署，AI 二开友好。

310 ★44 forksPythonUpdated 5d ago

What you need to know

An AI-native, Docker-based asset reconnaissance and vulnerability monitoring platform (a modern rewrite of ARL / Asset Reconnaissance Lighthouse) with a built-in MCP server so AI agents can directly schedule and query asset discovery, Web fingerprinting, Nuclei scanning, and threat-intel monitoring.

Install

One-command deploy for China servers (recommended): pull arl-web image from Aliyun mirror, extract start-prod.sh/docker-compose.prod.yml, run bash start-prod.sh
git clone --depth 1 https://github.com/owl234/ARL-Next.git && bash start-prod.sh (needs GitHub network access)
Dev: git clone && bash start-dev.sh (Docker backend + Vite frontend hot reload)

Usage

  • •Access https://<server-IP>:5173 - default credentials: Basic Auth admin/arl_next, business panel admin/arlpass (double-layer authentication)
  • •AI agents connect via the built-in MCP server to orchestrate asset scheduling and retrieval (MCP config guide in mcp-server/README.md)
  • •Use the Web dashboard for asset scoping, task lifecycle, custom PoC management, global fingerprint search, and threat-intel radar (CVE + GitHub code-leak monitoring)
  • •Enterprise asset discovery via ICP registration and TianYanCha (天眼查) integrations; alerts via Telegram

Key features

  • ✓Built-in MCP server for AI agents to directly control asset scheduling and retrieval
  • ✓High-performance architecture: heavy tasks (screenshots, OSINT) isolated into microservices (Puppeteer Node.js container, OSINT container) to prevent task deadlock
  • ✓Upgraded Chromium and Nuclei engines; MongoDB 7.0 with bulk_write and composite unique indexes for large asset tables
  • ✓Threat-intel radar tracking latest CVEs and GitHub code leaks; fingerprint engine with Aho-Corasick matching and memory cache
  • ✓China-market optimized: Aliyun prebuilt images to bypass GFW, one-click hot updates from the Web UI, Autoheal self-healing containers, Basic Auth protection

Best for

Chinese-market security teams and SRC researchers needing an AI-agent-controllable asset reconnaissance and vulnerability monitoring platform.

Caveats

  • ⚠For authorized enterprise security building, SRC vulnerability hunting, and academic research only; unauthorized probing is illegal (Chinese law)
  • ⚠Default credentials are public (admin/arl_next, admin/arlpass) - change them for production
  • ⚠Optimized for China deployments (Aliyun images); GitHub clone path requires reliable GitHub access
  • ⚠Documentation is primarily in Chinese
Platforms: Linux (Ubuntu/Debian) · DockerClients: AI agents via MCP
Documentation ↗

Reviewed 2026-08-07

Topics

asmattack-surface-managementbugbountycvedockerdocker-composeflaskfofainfosecmcpmodel-context-protocolnucleiosintreconnaissanceredteamsecurity-toolsthreat-intelligencevue3vulnerability-scanner
View on GitHub ↗
Stars
310★
Forks
44
Language
Python
License
—
Created
2026-04-30
Last push
2026-08-02