> ## Content Index > Fetch the complete content index at: https://darkwebinformer.com/llms.txt > Use this file to discover other available public pages before exploring further. # GhostEyes: Next-Gen Reconnaissance Toolkit for Red Teams & Pentesters - URL: https://darkwebinformer.com/ghosteyes-next-gen-reconnaissance-toolkit-for-red-teams-pentesters/ - Published: 2025-08-02T16:25:47.000Z - Updated: 2025-09-04T22:20:45.000Z - Author: Dark Web Informer - Tags: Tools --- **GitHub:** --- **GhostEyes** is an asynchronous-first, modular offensive reconnaissance toolkit built for penetration testers, red team operators, and security researchers. It combines network and web recon capabilities with streamlined report generation — all within a modern, clean codebase. --- ## What’s New in v2.1.0 - Fixed `asyncio.run()` nesting issues (no more runtime conflicts) - Colorized CLI output, quiet mode, and customizable output paths - `--examples` flag for quick onboarding - Clean structure, ready for future v3 enhancements (plugin system, structured logs, etc.) --- ## Key Features ### Network Reconnaissance - ARP subnet scanning - VLAN discovery and sampling - Layer 2 traceroute - DHCP traffic monitoring - Real-time device tracking ### Web Reconnaissance - Subdomain brute-force - Directory brute-force - Technology stack detection ### Reporting - Generate reports in TXT, JSON, HTML, and CSV formats - Supports multiple output types from previous scans ### CLI User Experience - Support for `--version`, `--examples`, `--quiet`, `--output` - Colorized terminal output - Single `asyncio.run()` ensures compatibility with async workflows --- ## Installation bashCopyEdit`git clone` https://github.com/6lackRaven/GhostEyes.git `cd` GhostEyes pip install -r requirements.txt > Python 3.10 or higher is recommended. --- ## Quick Start bashCopyEdit`# Show help` python ghosteyes.py -h `# Show version` python ghosteyes.py --version `# View example usage` python ghosteyes.py --examples --- ## Command Overview ### `net` — Network Reconnaissance bashCopyEditpython ghosteyes.py net -i \[--scan CIDR | --vlan | --track | --trace IP | --dhcp\] \[--duration N\] \[--output FILE\] | Option | Description | | ---------------- | ------------------------------------------- | | \-i, --interface | Specify network interface (default: eth0) | | \-s, --scan | ARP scan a subnet (e.g., 192.168.1.0/24) | | \-v, --vlan | Discover VLANs | | \-t, --track | Track live devices | | \-r, --trace | Layer 2 traceroute to a target IP | | \-d, --dhcp | Capture DHCP traffic | | \--duration | Duration (seconds) for vlan, track, or dhcp | | \--output | Output file path (default: scan\_net.json) | **Examples:** bashCopyEdit`# ARP scan` python ghosteyes.py net -i eth0 --scan 192.168.1.0/24 --output my\_scan.json `# VLAN discovery` python ghosteyes.py net -i eth0 --vlan --duration 120 `# Device tracking` python ghosteyes.py net -i wlan0 --track --duration 60 --quiet --- ### `web` — Web Reconnaissance bashCopyEditpython ghosteyes.py web -u https://example.com \[OPTIONS\] | Option | Description | | ----------------- | ------------------------------------------ | | \-u, --url | Target URL (required) | | \-s, --subdomains | Subdomain brute-force wordlist | | \-b, --bruteforce | Directory brute-force wordlist | | \-T, --tech | Detect web technology stack | | \-w, --workers | Number of concurrent workers (default: 50) | | \--output | Output file (default: scan\_web.json) | **Examples:** bashCopyEdit`# Subdomain scan with tech detection` python ghosteyes.py web -u https://example.com -s subdomains.txt -T `# Directory brute-force` python ghosteyes.py web -u https://example.com -b dirs.txt --quiet --- ### `report` — Generate Recon Reports bashCopyEditpython ghosteyes.py report -f scan\_net.json -t html json | Option | Description | | ----------- | -------------------------------------------- | | \-f, --file | Input file path (must be a JSON scan result) | | \-t, --type | Output format(s): txt, json, html, csv, all | **Examples:** bashCopyEdit`# Generate HTML and JSON reports` python ghosteyes.py report -f scan\_net.json -t html json `# Generate all report formats` python ghosteyes.py report -f scan\_web.json -t all --- ## Output Files | Scan Type | Default Output File | | --------- | ------------------- | | Network | scan\_net.json | | Web | scan\_web.json | Use `--output` to customize the filename and path. --- ## Roadmap Toward v3 Planned enhancements include: - Plugin-based architecture - Structured logging (JSON with log levels) - Config file support via `.toml` or `.yaml` - Improved concurrency with timeouts and cancellation - Packaging via PyPI (`pip install ghosteyes`) - Self-contained binaries and REST API/Web UI interface Details available in `CHANGELOG.md`. --- ## Legal Notice GhostEyes is provided strictly for ethical security research and authorized testing. By using this tool, you agree to: - Only scan targets you own or are explicitly authorized to test - Comply with local and international laws (e.g., CFAA, GDPR) - Accept full responsibility for any actions performed The authors disclaim liability for misuse or damage caused by this tool. --- ## License Released under the [MIT License](https://github.com/6lackRaven/GhostEyes/blob/main/LICENSE). --- ## Contact - **Author:** 6lackRaven - **Email:** harleystanislas.raven@gmail.com - **Telegram:** @Thereal6lackRaven - **Facebook:** Harley Stanislas --- ## Contributing Interested in contributing? 1. Fork the repository 2. Create a feature branch: `git checkout -b feature/my-feature` 3. Write clean, tested code 4. Submit a pull request with a clear description Follow the existing code style and maintain respectful collaboration.