v1.0

The ultimate search engine reconnaissance tool for ethical hackers and security researchers. Uncover hidden vulnerabilities with advanced dorking techniques.

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Cyber Reconnaissance

Multi-Engine Support

Query across Google, Bing, DuckDuckGo, Yahoo, Baidu, and Yandex simultaneously for comprehensive results with automated request rotation.

Smart Dork Categories

Pre-built dork categories for filetypes, login pages, config files, vulnerabilities, and subdomains with customizable templates.

Advanced Output

Export results in JSON, CSV, or plain text formats with detailed metadata for easy integration with other security tools.

Terminal Demo

Terminal
$ python ezdorker.py example.com -e google bing -c filetype login -v -o results.json [+] EZDorker v1.0 - Cyber Reconnaissance Tool [+] Initializing with 4 threads... [+] Target: example.com [+] Engines: google, bing [+] Dork categories: filetype, login [+] Generated 12 dork queries [+] Starting reconnaissance... [1/12] Executing: site:example.com filetype:pdf [+] GOOGLE: Found 3 results (0.8s) [+] BING: Found 2 results (1.1s) [2/12] Executing: site:example.com inurl:login [+] GOOGLE: Found admin panel at /admin/login (0.6s) [+] BING: Found 1 result (0.9s) [+] Scan completed in 28.4 seconds [+] Results saved to: results.json [+] 42 unique endpoints discovered

Installation

Requirements

System
• Python 3.6+ (recommended 3.9+) • pip package manager • 256MB RAM minimum • Internet connection

Quick Install

Bash
# Clone the repository git clone https://github.com/alastorapps/ezdorker-tool.git cd ezdorker # Install dependencies pip install -r requirements.txt # Or install manually pip install requests beautifulsoup4 colorama

Docker Install

Bash
# Pull the Docker image docker pull alastorapps/ezdorker-tool:latest # Run with basic parameters docker run -it --rm alastorapps/ezdorker-tool example.com

Usage

Basic Command

Bash
python ezdorker.py example.com

Advanced Options

Option Description Example
-o OUTPUT Save results to file (JSON/CSV/TXT) -o results.json
-e ENGINES Search engines (space-separated) -e google bing yandex
-c CATEGORIES Dork categories to use -c filetype login
-t THREADS Number of threads (default: 4) -t 8
-d DELAY Delay between requests (seconds) -d 3
-b Open dorks in browser -b
-v Verbose output mode -v

Full Example

Bash
# Comprehensive scan with all options python ezdorker.py example.com \ -o results.csv \ -e google bing duckduckgo \ -c filetype login config vulnerabilities \ -t 6 \ -d 2 \ -v \ -b

Supported Engines

Engine Status Features Rate Limit
Google Full Support Advanced operators, pagination Strict
Bing Full Support API-like results, fast Moderate
DuckDuckGo Full Support Privacy focused, no JS Lenient
Yahoo Full Support Bing-powered, alternative Moderate
Baidu Basic Support Chinese results Strict
Yandex Basic Support Russian results Moderate

FAQ

How do I avoid getting blocked by search engines?
  • Use the -d flag to increase delay between requests (recommended 3-5 seconds)
  • Rotate between different search engines using -e google bing duckduckgo
  • Limit the number of threads with -t 2 for more stealth
  • Consider using residential proxies if doing extensive scanning
What's the best output format for analysis?

For most use cases, JSON (-o results.json) is recommended because:

  • Preserves all metadata (engine source, dork used, timestamps)
  • Easily parsable by other tools (jq, Python scripts, etc.)
  • Supports nested structures for complex data

For quick review, CSV is good for spreadsheet analysis, and TXT is most human-readable.

Can I add custom dork patterns?

Yes! Edit the DORKS dictionary in the script to add your own patterns:

Python
DORKS = { "custom": [ "site:{target} ext:php intext:'admin'", "site:{target} intitle:'index of' password", # Add your custom dorks here ], # ... existing categories }

Then use with -c custom parameter.