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Automated reconnaissance tool with AI report generation. Subdomain enumeration, endpoint crawling, and vulnerability pattern detection.

Project description

HB-Recon

PyPI version PyPI - Downloads Python License Stars

Automated reconnaissance workflow with AI-ready report generation.

Perfect for bug bounty hunters, pentesters, and security researchers.


⚠️ Important Notice

HB-Recon is a workflow automation tool — it orchestrates external security tools and generates structured reports.

What it does:

  • ✅ Automates reconnaissance workflows
  • ✅ Chains multiple tools together
  • ✅ Generates AI-ready JSON reports
  • ✅ Organizes scan results

What it does NOT do:

  • ❌ Include built-in scanning capabilities
  • ❌ Auto-install required tools
  • ❌ Work without dependencies

Features

Subdomain Enumeration — subfinder integration
Live Host Detection — httpx for alive checks
Technology Stack Scan — WhatWeb detection
Endpoint Crawling — Katana deep crawl (depth 3)
Vulnerability Patterns — gf pattern matching (XSS, SQLi, IDOR)
AI Report Generation — Structured JSON with risk scoring


Prerequisites

System Requirements

  • OS: Linux / WSL (Windows Subsystem for Linux)
  • Python: 3.8+
  • Go: 1.19+ (for tool installation)

Required External Tools

You MUST install these tools before using hb-recon:

Tool Purpose Installation
subfinder Subdomain enumeration go install -v github.com/projectdiscovery/subfinder/v2/cmd/subfinder@latest
httpx HTTP probe go install -v github.com/projectdiscovery/httpx/cmd/httpx@latest
katana Web crawler go install -v github.com/projectdiscovery/katana/cmd/katana@latest
gf Pattern matcher go install github.com/tomnomnom/gf@latest
whatweb Tech detection sudo apt install whatweb (Debian/Ubuntu)

Quick Install (All Tools)

# Install Go tools
go install -v github.com/projectdiscovery/subfinder/v2/cmd/subfinder@latest
go install -v github.com/projectdiscovery/httpx/cmd/httpx@latest
go install -v github.com/projectdiscovery/katana/cmd/katana@latest
go install github.com/tomnomnom/gf@latest

# Install WhatWeb
sudo apt install whatweb

# Verify installations
subfinder -version
httpx -version
katana -version
gf -h
whatweb --version

Installation

Option 1: PyPI (Recommended)

pip install hb-recon

Option 2: From Source

git clone https://github.com/infohlaingbwar/hb-recon.git
cd hb-recon
pip install -e .

Usage

Interactive Mode

python -m hb_recon

Example:

=======================================================
  Auto Recon -> AI Ready
=======================================================

[>] Domain: example.com

[+] Subfinder + Httpx
[v] Done (5.2s)

[*] WhatWeb + Katana (parallel)...
[+] Katana (crawl)
[v] Done (12.4s)

[+] gf (XSS/SQLi/IDOR patterns)
[v] Done (1.8s)

[√] Total: 19.4s

Output Structure

recon_example.com/
├── subdomains.txt      # All discovered subdomains
├── alive.txt           # Live hosts (200, 301, 403)
├── urls.txt            # Crawled endpoints (depth 3)
├── xss.txt             # XSS-prone endpoints
├── sqli.txt            # SQLi-prone endpoints
├── idor.txt            # IDOR-prone endpoints
├── tech_stack.txt      # Technology detection
└── ai_report.json      # AI-ready structured report

AI Report Format

The tool generates ai_report.json with structured data perfect for AI analysis:

{
  "target": "example.com",
  "timestamp": "2026-06-20T13:45:00",
  "summary": {
    "subdomains": 15,
    "alive_hosts": 8,
    "endpoints": 324,
    "technologies": 12,
    "high_risk": 3,
    "medium_risk": 7,
    "low_risk": 15
  },
  "endpoints": [
    {
      "url": "https://admin.example.com/api/users?id=123",
      "category": "idor",
      "risk": "high",
      "params": ["id"]
    }
  ],
  "tech_stack": {
    "server": "nginx/1.18.0",
    "frameworks": ["React", "Node.js"],
    "cms": "WordPress 6.2"
  }
}

Use with AI:

# After scan
cat recon_example.com/ai_report.json | pbcopy
# Paste into ChatGPT/Claude: "Analyze this recon data for vulnerabilities"

Workflow Logic

Input: Domain
    ↓
1. Subdomain Enumeration (subfinder)
    → hackertarget, waybackarchive sources
    ↓
2. Live Detection (httpx)
    → Filter 200, 301, 403 status codes
    ↓
3. Parallel Execution:
    ├─→ Tech Stack (WhatWeb)
    └─→ Endpoint Crawl (Katana depth=3)
    ↓
4. Pattern Detection (gf)
    ├─→ XSS patterns
    ├─→ SQLi patterns
    └─→ IDOR patterns
    ↓
5. AI Report Generation
    → Risk scoring
    → Category grouping
    → JSON export

Example Workflow

# 1. Install hb-recon
pip install hb-recon

# 2. Run scan
python -m hb_recon
# Enter: bugcrowd.com

# 3. Wait 30-60 seconds

# 4. Check results
cd recon_bugcrowd.com
cat ai_report.json

# 5. Analyze with AI
# Copy ai_report.json content to ChatGPT/Claude

Security Notice

⚠️ Only use on authorized targets.

This tool is for:

  • Bug bounty programs (with scope)
  • Authorized penetration testing
  • Your own infrastructure

Unauthorized scanning is illegal and violates:

  • Computer Fraud and Abuse Act (CFAA)
  • Most countries' cybercrime laws
  • Bug bounty program rules

You are responsible for your actions.


Troubleshooting

"Command not found" errors

Problem: Tool binaries not in PATH

Solution:

# Add Go bin to PATH (add to ~/.bashrc or ~/.zshrc)
export PATH="$HOME/go/bin:$PATH"

# Reload shell
source ~/.bashrc

"Platform Error" on Windows

Problem: hb-recon requires Linux/WSL

Solution:

# Use WSL (Windows Subsystem for Linux)
wsl -d kali-linux
pip install hb-recon
python -m hb_recon

Network timeouts

Problem: Slow/unstable connection

Solution:

# Increase timeout in cli.py
# Default: timeout=300 (5 minutes)

Contributing

Contributions welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Submit a pull request

License

MIT License - See LICENSE


Author

Hlaing Bwar


Made with ❤️ for the bug bounty community

Disclaimer: This tool is for educational and authorized testing only. Misuse may result in legal consequences.

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