Using Linux Text Processing Tools for Subdomain Search

Application Background

In practical scenarios, we often need to collect subdomains of target sites, usually using tools like subdomain excavators, oneforall, etc., or space search engines like fofa, shodan, and eagle map, or Google syntax. Besides the conventional methods, we can also utilize the Linux text processing tools we learned earlier to collect subdomains.

Steps

Identify Target Site

There is a publicly available web site on the internet:<span>www.megacorpone.com</span>

Get index.html

wget www.megacorpone.com

Get Subdomains

We have obtained the index.html file. Based on our knowledge of HTML (HyperText Markup Language), web page links are usually found in the <span><a></span> tag’s href attribute.

grep "href=" index.html
Using Linux Text Processing Tools for Subdomain Search

Then we find out that the main domain is <span>www.megacorpone.com</span>, and we will filter the links to find those containing <span>megacorpone</span>.

grep "href=" index.html | grep "\.megacorpone"
Using Linux Text Processing Tools for Subdomain Search

Since we need subdomains, we will filter out <span>www.megacorpon.com</span>

grep "href=" index.html | grep "\.megacorpone"|grep -v "www.\megacorpone\.com"
Using Linux Text Processing Tools for Subdomain Search

Next, we use <span>awk</span> to take the subdomain part after the <span>http(s)://</span> separator, which is <span>//</span>.

grep "href=" index.html | grep "\.megacorpone" | grep -v "www.\megacorpone\.com" | awk -F "//" '{print $2}'
Using Linux Text Processing Tools for Subdomain Search

Finally, we use <span>cut</span> to remove the file paths after the subdomains.

grep "href=" index.html | grep "\.megacorpone" | grep -v "www.\megacorpone\.com" | awk -F "//" '{print $2}' | cut -d "/" -f 1 |cut -d '"' -f 1
Using Linux Text Processing Tools for Subdomain Search

In this way, we can obtain the subdomains related to <span>www.megacorpone.com</span>.

Pros and Cons

This method allows for quick searching of subdomains, faster and more efficient than traditional subdomain search tools. However, the subdomains found using this method may not be as comprehensive as those collected by dedicated subdomain collection tools, and there is a significant chance of missing some subdomains.

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Using Linux Text Processing Tools for Subdomain Search

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Using Linux Text Processing Tools for Subdomain Search

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Using Linux Text Processing Tools for Subdomain Search

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Using Linux Text Processing Tools for Subdomain Search

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Using Linux Text Processing Tools for Subdomain Search

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