owl234/arl-next
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Modern Asset Mapping and Vulnerability Monitoring Platform (ARL-Next). Reconstructing the classic ARL architecture, focusing on enterprise asset association, asynchronous decoupling concurrent scheduling, integration with native MCP protocols, and containerized out-of-the-box deployment.
Overview
Modern Attack Surface Reconnaissance & Asset Intelligence Platform ⚡ Rapid deployment guide • 💡 Architecture evolution comparison • ✨ Core features • 🤖 MCP configuration guide • 📜 Changelog • 📄 Open source protocol It is an asset mapping platform based on the classic open-source project ARL (Asset Reconnaissance Lighthouse), undergoing architectural reconstruction and continuous evolution. To address engineering bottlenecks such as task queue blockage, long-term memory growth, and outdated historical dependencies in large-scale scanning scenarios, the system implements microservice splitting and asynchronous task decoupling, comprehensively upgrades the modern runtime foundation and mapping toolchain, and integrates standard protocols to support automated asset pivot and AI collaborative scheduling. * 🤖 : Built-in standardized Python MCP service, supporting external agent integration and task assignment and export of 13D asset dashboard data. (👉 MCP Configuration Guide) * ⚙️ : Microservice splitting and independent task queue distribution, combined with batch data repository optimization, ensuring smooth operation of high-throughput scanning. * 🌐 : Supports automated association between enterprise equity relationships and full-type ICP (websites/apps/mini programs/quick applications) to build multi-level asset topologies. * 🔍 : Based on Nmap 7.95 LTS stable version; Built-in native Python sensitive credential and information flow extraction engine. * 🛡️ : Continuously synchronizes authoritative CVE vulnerability intelligence, monitors GitHub associated code and credential leaks, supports atomic update deduplication mechanism. * ⚡ : Integrates container health activation, ready polling, and automatic restart mechanisms, supporting smooth online upgrades in the management backend. * 📦 : Provides Alibaba Cloud domestic image source precompilation and build products to avoid image pulls and dependency installation failures caused by cross-border network fluctuations. *: Real-time monitoring of host physical memory and swap levels, system resource load, scanning task lifecycle, multi-dimensional risk dashboard, and panoramic operation log flow. * : Supports enterprise ICP filing (website/mobile app/WeChat mini-program/Kuai app) penetration and company equity penetration, with one-click association and synchronized multi-dimensional detection tasks. * : Deeply integrated with Nuclei, a pool of 100+ dedicated PoC plugin for vulnerabilities, and nearly 10,000 web fingerprint libraries (8,800+), supporting full lifecycle issuance and tracking. *: Real-time tracking of the latest global CVE vulnerabilities, automated monitoring of GitHub sensitive code and credential leaks.
Overview (machine translated)
English | Chinese Simplified
ARL-Next
Modern Asset Mapping and Vulnerability Monitoring Platform
Modern Attack Surface Reconnaissance & Asset Intelligence Platform
Enterprise asset linkage · Asynchronous decoupled scheduling · Native MCP protocol integration · Containerized unboxing deployment
🚀 Quick Start (5 minutes) • ⚡ Rapid Deployment Guide • 💡 Architecture Evolution Comparison • ✨ Core Features • 🔌 API Integration Guide • 🤖 MCP Configuration Guide • 📜 Update Log • 💬 Discussion and Exchange • 📄 Open source protocol
💡 What is ARL-Next?
ARL-Next is an asset mapping platform based on the classic open-source project ARL (Asset Exploration Lighthouse), which undergoes architectural reconstruction and continuous evolution. To address engineering bottlenecks such as task queue blocking, long-term memory growth, and outdated historical dependencies in large-scale scanning scenarios, the system implements microservice splitting and asynchronous task decoupling, comprehensively upgrades the modern runtime environment and mapping toolchain, and integrates the Model Context Protocol (MCP) standard protocol, supporting automated asset pivoting and AI collaborative analysis.
💡 Comparison of Architectural Evolution and Technical Solution Benchmarks
| Evaluation Dimensions | ARL Original Architecture and Implementation | ARL-Next Refactoring Solution |
|---|---|---|
| Concurrency and Scheduling Architecture | Task execution shares a single Celery queue; complex tasks with high concurrency are prone to queue blocking and temporary dead | Splitting OSINT and screenshots into independent microservices, introducing separate queues and batch warehousing, significantly reducing queue blocking and concurrency bottlenecks |
| Automated Protocol Integration | No standardized external scheduling interface, only supports manual interaction via web console | Supports native MCP Server, providing the capability to perform multidimensional asset profiling via standard protocols |
| Enterprise Asset Topology | Unaffiliated Enterprises and All-Type Digital Asset Drilling Links | Deep Asset Group Integration: Supports corporate equity association and multi-type ICP searches (websites / apps / mini programs / quick apps), building multi-level group topology and exposure surface profiles |
| Container Building and Deployment | Outdated dependencies and lack of image acceleration make build pulls vulnerable to external network fluctuations | Multi-stage container construction and Alibaba Cloud domestic image source precompilation Improve build speed and deployment stability |
| Underlying Technology Stack Baseline | Python 3.6 / Vue 2 / MongoDB 3.x / Nmap 7.70 | Python 3.13 / Vue 3.5 / MongoDB 7.0 / Nmap 7.95 Stable Version Modern runtime baseline alignment |
This page was translated automatically. Technical details may differ from the original.
Install
docker run --rm -v $(pwd):/host crpi-laul1izptqrf0tkf.cn-beijing.personal.cr.aliyuncs.com/owl234-arl-prod/arl-web:latest bash -c "cp /code/start-prod.sh /host/start-prod.sh && cp /code/docker-compose.prod.yml /host/docker-compose.prod.yml && mkdir -p /host/updater && cp -r /code/updater/. /host/updater/ 2>/dev/null || true; mkdir -p /host/tools && cp -r /code/tools/. /host/tools/ 2>/dev/null || true; mkdir -p /host/frontend && cp /code/frontend/default.conf.prod /host/frontend/default.conf.prod 2>/dev/null || true; cp /code/version.txt /host/version.txt 2>/dev/null || true; cp /code/CHANGELOG.md /host/CHANGELOG.md 2>/dev/null || true; cp /code/CHANGELOG_en.md /host/CHANGELOG_en.md 2>/dev/null || true" && \