🤖 AI-Based Network Reconnaissance Tool

Project Overview

This project bridges the gap between complex command-line network scanners and intuitive, natural language interfaces. Designed specifically for Network Security Administrators, the tool eliminates the steep learning curve associated with advanced Nmap flags by allowing users to request reconnaissance tasks in plain English.

The system automatically translates these requests into optimized Nmap commands, executes the scan, and then utilizes an AI language model to interpret the raw XML output into a prioritized, actionable security report.

Technical Implementation

The platform is built on Next.js, leveraging its serverless functions to securely communicate with the backend scanning engine. The core translation layer uses the OpenAI GPT-4 API to parse user intent into precise `nmap` syntax, ensuring safety constraints are met before execution.

The actual scanning occurs in an isolated Node.js environment using the `node-nmap` abstraction layer. Once the scan completes, the raw output is fed back into the LLM context window with a specialized system prompt that forces the AI to act as a seasoned penetration tester—highlighting critical open ports, identifying outdated service versions, and cross-referencing known CVEs.

Key Features / Findings

• Natural Language to Nmap translation engine with safety guardrails.
• Automated AI-driven analysis of scan results, prioritizing critical vulnerabilities.
• Real-time streaming of scan progress via WebSockets for long-running comprehensive scans.
• Exportable executive summaries and detailed technical findings.
• Built-in rate limiting and strict target validation to prevent abuse.