In the world of offensive security, Reconnaissance is King. You can have the most advanced exploit for a specific vulnerability, but if you never find the page where that vulnerability exists, your exploit is useless.

Many beginners in Bug Bounty and Penetration Testing make a critical mistake: they stick to the homepage and manually click a few links. This leaves 90% of the application untested.

This article explores the Web Crawler (or Spider) — the most essential automated tool in your reconnaissance arsenal. We will cover what it is, how it works, and the modern GitHub tools that every pentester should have in their CLI.

1. What is a Web Crawler?

A Web Crawler is an automated script or bot designed to systematically browse the World Wide Web. While Google uses crawlers to index the internet for search results, hackers use them for a different purpose: Attack Surface Mapping.

In pentesting, a crawler's job is to visit a starting URL (the seed), find all the hyperlinks, JavaScript files, and API endpoints on that page, and then visit those new links recursively.

The Goal: To build a complete map of the application, discovering every possible input vector where a vulnerability might hide.

2. How It Works (The Mechanics)

Here is a step-by-step visual guide on how a web crawler works :

Step 1: The Seed URL :

The process begins with a seed URL, which is the starting point for the crawler. You provide this initial URL to the crawler, and it will begin its journey from there.

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In this image, a crawler bot is shown with the initial "Seed URL" (https://start-here.com). This is the first piece of information it receives to start its task.

Step 2: Fetch and Parse :

Once the crawler has the seed URL, it visits that page and downloads its content (HTML). It then "parses" this HTML to find new links (URLs) embedded within the page's code.

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As shown here, the bot is on the https://start-here.com page, actively extracting new links like /about, /contact, and /products from the page's HTML code.

Step 3: The URL Queue :

The newly discovered links are not visited immediately. Instead, they are added to a "queue," which is a list of URLs waiting to be processed. This ensures the crawler has a structured way to manage its work.

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This image illustrates the bot placing the links it just found into a "URL Queue." This queue already contains other links, showing a continuous process.

Step 4: Recursion and Final Output :

The crawler then takes a URL from the queue, visits that new page, and repeats the entire process (fetch, parse, and queue). This is called recursion. The process continues until the queue is empty or a predefined limit is reached. The final result is a comprehensive list of all the URLs discovered.

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In this final image, the bot is taking a new URL (/about) from the queue to continue its work. A clipboard on the right displays the "Final Crawl Output," a list of all the URLs the crawler has successfully mapped.

3. Why Bug Hunters Need Crawlers

You cannot hack what you cannot see. Here is why automated crawling is non-negotiable in modern security assessments:

A. Discovering "Hidden" Endpoints

Developers often leave old files on the server that aren't linked in the main menu. A crawler might find a reference to /v1/api/admin buried inside a forgotten JavaScript file. These "orphaned" endpoints are often less secure than the main app.

B. Analyzing JavaScript (The Gold Mine)

Modern applications (Single Page Apps using React, Vue, Angular) are heavy on Client-Side code. A good crawler will download all .js files. These files often leak:

  • API Keys / Secrets
  • Hardcoded credentials
  • Internal API routes
  • DOM-based XSS sinks

C. Parameter Discovery

To find SQL Injection or XSS, you need inputs (parameters). A crawler scrapes every ?id=, ?search=, and ?redirect= it encounters, giving you a list of parameters to fuzz later.

4. Selecting a "Modern" Tool

Not all crawlers are created equal. In 2024/2025, you should avoid old, slow Python scripts and look for tools with these features:

  • Written in Go (Golang): Go allows for high concurrency. You can scan thousands of URLs in seconds without crashing your machine.
  • Headless Support: Old crawlers only read static HTML. Modern apps generate links dynamically using JavaScript. You need a crawler that can launch a "Headless Browser" (like a hidden Chrome tab) to render the page and find those dynamic links.
  • Pipeline Friendly: The tool should accept input from stdin (pipes) so you can chain it with other tools like subfinder or nuclei.

5. The Arsenal: Top GitHub Tools

Here are the industry-standard tools you should be using. They are free, open-source, and maintained by the community.

1. Katana (The Powerhouse)

Created by ProjectDiscovery, Katana is arguably the best crawler available today. It supports both standard crawling and headless crawling (using Chromium).

  • Best for: Deep analysis of complex applications.
  • Key Feature: Can fill out forms automatically and render JS.

Installation:

go install github.com/projectdiscovery/katana/cmd/katana@latest

How to use it:

# Standard crawl (Fast)
katana -u https://target.com -d 3 -o output.txt

# Headless crawl (Slower, but finds much more)
# -jc: Javascript Crawling (Headless)
katana -u https://target.com -jc -d 3 -o output.txt

2. Hakrawler (The Fast Pipe)

Created by Luke Stephens (hakluke), this tool is designed for the Unix philosophy: "Do one thing well." It is lightweight and perfect for scanning a list of subdomains.

  • Best for: Quick reconnaissance on many targets.
  • Key Feature: Easy to pipe with other tools.

Installation:

go install github.com/hakluke/hakrawler@latest

How to use it:

# Find subdomains and pipe them immediately to hakrawler
subfinder -d target.com | hakrawler -depth 2 | tee endpoints.txt

3. GAU (Get All Urls) / Waymore (The Time Traveler)

Technically, these are Passive Crawlers. They don't visit the target website directly. Instead, they query public archives like the Wayback Machine, AlienVault, and Common Crawl.

  • Best for: Finding old, deleted, or interesting files without alerting the target's firewall (WAF).
  • Key Feature: Extremely stealthy.

Installation:

go install github.com/lc/gau/v2/cmd/gau@latest

How to use it:

# Fetch every URL ever known for this domain
gau target.com --subs | tee archive_urls.txt

Conclusion

Automated crawling is the bridge between a URL and a Vulnerability. By moving away from manual browsing and utilizing powerful, Go-based tools like Katana and Hakrawler, you expand your attack surface significantly.

Remember: The more endpoints you find, the more chances you have to break something.

Happy Hacking!