🕵️ Abdal Web Intelligence Analyzer

🎤 README Translation

• English
• فارسی

Abdal Web Intelligence Analyzer is a powerful and stealthy CLI-based tool for analyzing websites protected by modern WAF/CDN solutions such as ArvanCloud, Cloudflare, Akamai, and others.
It leverages a real headless browser to simulate real-user behavior, bypass JS-based protections, and analyze both static and dynamic assets.

📊 Technical Capabilities

Feature	Description
Static Extraction	Images, CSS, JS, Fonts from full DOM
Dynamic Detection	API endpoints via fetch, axios, jQuery, forms
Load Time Analysis	Based on performance.timing from real browser
CDN Detection	Analyzes headers from real HTTP responses using a headless browser
WAF Detection	Detects redirects, JS challenges, ArvanCloud security layers
Protocol Scan	Checks support for HTTP/2, HTTP/3, and QUIC (via ALPN)
Rate Suggestion	Calculates safe RPS (Requests/sec) based on CPU, RAM, Disk, OS

🚀 Features

• ✅ Bypasses advanced WAF protections (e.g., ArvanCloud, Cloudflare, etc.)
• 🧠 Real browser rendering using undetected_chromedriver and selenium-wire
• 🌐 Detects active CDN providers by analyzing real HTTP response headers
• 🔍 Scans for:
  • Static Assets (Images, CSS, JS, Fonts)
  • Dynamic Endpoints (AJAX, APIs, Forms, Hidden routes)
• ⏱️ Measures full page load time using window.performance.timing
• ⚡ Estimates recommended RPS (requests per second) based on system specs
• 📡 Detects HTTP/2, HTTP/3, and QUIC protocol support
• 🛡️ Identifies JavaScript-based WAF protection (e.g., ArvanCloud challenges)
• ⚙️ Supports both Linux and Windows
• 🖥️ Lightweight & fast CLI-based interface, no GUI required

📋 Prerequisites

Before running the analyzer, make sure you have the following installed:

pip install beautifulsoup4
pip install httpx
pip install colorama
pip install undetected-chromedriver
python -m ensurepip --upgrade
python -m pip install setuptools

🔍 How It Works

The analyzer uses a stealth headless browser (based on undetected_chromedriver) to simulate a real user visiting a website. It performs the following steps:

1. Browser Launch: Starts a headless Chromium instance with bot detection disabled.
2. WAF Detection: If a known WAF page (like ArvanCloud's JS challenge) is detected, it waits until the JS challenge passes and the page reloads.
3. Page Load Time Measurement: Uses window.performance.timing to measure the real page load time from the browser's perspective.
4. Content Extraction:
   • Extracts static assets: images, CSS files, JavaScript files, and fonts.
   • Detects dynamic endpoints using patterns such as fetch(), axios, XMLHttpRequest, forms, and query URLs.
5. Resource Counting: Totals static and dynamic requests found in the DOM.
6. Performance Estimation: Based on optional CPU, RAM, Disk, and OS input, calculates an estimated optimal RPS (requests per second) the server can handle for static/dynamic content.

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🐳 Docker Installation & Usage

You can run the Abdal Web Intelligence Analyzer instantly using Docker, without needing to install Python dependencies.

📥 Pull the Docker Image

docker pull ebrasha/abdal-web-intelligence-analyzer

docker run -it  ebrasha/abdal-web-intelligence-analyzer

🛠️ Usage

▶️ If you are using Windows:

Simply run the run.bat file by double-clicking it or executing it via terminal:

run.bat

1. Run the script:

python abdal-web-intelligence-analyzer.py

2. Enter the website URL when prompted (include http:// or https://)

3. Optionally provide your server specifications:

   • Number of CPU cores
   • RAM in GB
   • Disk type (HDD/SSD/NVMe)
   • OS type (Linux/Windows)

4. The analyzer will display:

   • Page load time
   • Number of static assets (images, CSS, JS, fonts)
   • Number of dynamic requests detected
   • Recommended RPS for both static and dynamic content

📊 Output Example

🔍 Analyzing: https://example.com
=====================================
⏱️ Page Load Time: 2.45 seconds
📸 Images: 12
🎨 CSS Files: 5
📜 JS Files: 8
🔠 Fonts: 3
⚙️ Dynamic Requests Detected: 15
-------------------------------------
📊 Total Static Requests: 28
📊 Total Dynamic Requests: 15

⚙️ Suggested Static Requests/second: 25
⚙️ Suggested Dynamic Requests/second: 12

🐛 Reporting Issues

If you encounter any issues or have configuration problems, please reach out via email at Prof.Shafiei@Gmail.com. You can also report issues on GitLab or GitHub.

❤️ Donation

If you find this project helpful and would like to support further development, please consider making a donation:

• Donate Here

🤵 Programmer

Handcrafted with Passion by Ebrahim Shafiei (EbraSha)

• E-Mail: Prof.Shafiei@Gmail.com
• Telegram: @ProfShafiei

📜 License

This project is licensed under the GPLv2 or later License.