SecNN/AiScan-N

AiScan-N 来了！这是一款基于人工智能驱动的Ai自动化网络安全（运维）工具，专注于网络安全评估、漏洞扫描、运维、应急响应、渗透测试自动化，Ai大模型工具集【CLI Agent】 ，Ai驱动的安全检测技术，提升安全测试（运维）效率，专为企业和个人用户打造，尤其适合初学者（小白）快速上手使用，让你轻松迈入智能安全攻防时代！适用场景 ：如（红队演练、CTF比赛、Web应用渗透测试、内网横向移动、密码破解与暴力攻击、流量分析与威胁检测、APT攻击模拟、漏洞赏金挑战等场景）🎥演示视频（文章中）：https://mp.weixin.qq.com/s/7lsUdbrxkDy4P5pZhEWv7Q

What it solves

AiScan-N is an AI-powered automation tool for cybersecurity operations, designed to streamline network security assessments, vulnerability scanning, penetration testing, and emergency response. It aims to reduce the reliance on high-cost security experts and lower the barrier to entry for beginners by automating complex security tasks that typically require deep manual experience.

How it works

The project operates as a CLI Agent that integrates with various Large Language Models (LLMs)—including cloud-based, third-party, or locally deployed models—to execute security workflows. It uses a Model Context Protocol (MCP) to extend AI capabilities, allowing the LLM to interact with the local system, remote hosts via SSH, and specialized security tools (like nmap, fscan, and sqlmap). The system includes a workspace with session management, long-term memory for preferences, and a skills center where users can define standardized procedures for the AI to follow.

Who it’s for

It is designed for cybersecurity professionals, red teamers, CTF competitors, and beginners who want to automate security audits, APK reverse engineering, and network asset mapping.

Highlights

  • Automated Penetration Testing: AI-driven identification of vulnerabilities and simulation of attacks to generate security reports.
  • MCP Integration: Built-in support for Android/iOS control, SSH remote management, and integration with tools like BurpSuite and IDA Pro.
  • Asset Mapping: Comprehensive subdomain collection, fingerprinting, and CDN/origin server detection.
  • Mobile Analysis: One-click APK unpacking, static analysis, and traffic capturing for Android apps.
  • Traffic Analysis: AI-assisted analysis of PCAP/PCAPNG files to identify malicious traffic patterns.
  • Multi-Model Support: Compatible with various LLMs, including local offline models for air-gapped environments.

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