ipcrawler 192.168.1.1 -o ./scan

Features

• AI-Powered Parsing - Converts any tool output to structured JSON (OpenAI, Groq, Anthropic, Ollama)
• Concurrent Execution - Tokio-based async with automatic pre-scan and dependency handling
• Template System - Add tools via YAML without code changes
• Multiple Formats - Terminal, HTML, Markdown, and JSON reports
• Smart Consistency - Multi-pass parsing with union merge strategy

[!NOTE] LLMs are used solely to parse raw tool outputs into structured data. They do not provide security analysis, opinions, or recommendations—only data transformation from unstructured to structured format.

Installation

# Quick install
curl -fsSL https://raw.githubusercontent.com/neur0map/ipcrawler/main/install.sh | bash

# Build from source
git clone https://github.com/neur0map/ipcrawler.git
cd ipcrawler
cargo build --release
sudo mv target/release/ipcrawler /usr/local/bin/

Quick Start

# 1. Configure LLM provider (one-time)
ipcrawler setup

# 2. Run scan
ipcrawler example.com -o ./scan

# 3. View results
open ./scan/report.html

Usage

# Basic scan
ipcrawler <target> -o <output_dir>

# Specific ports
ipcrawler <target> -p 22,80,443 -o <output>

# Custom wordlist
ipcrawler <target> -w big -o <output>

# With sudo (privileged templates)
sudo ipcrawler <target> -o <output>

# List available templates
ipcrawler list

Configuration

Get an API key from Groq (recommended), OpenAI, Anthropic, or install Ollama for local models.

# Interactive setup
ipcrawler setup

# Or set environment variables
export LLM_PROVIDER="groq"
export LLM_API_KEY="your-key"

Documentation

• Usage Guide - Detailed commands, options, and examples
• Configuration - LLM setup and advanced configuration
• Template Guide - Creating custom tool templates
• Development - Building and contributing
• Architecture - System design and internals
• Contributing - Contribution guidelines

License

MIT License - see LICENSE for details

Built with Rust • Powered by AI