Subdomains analysis and generation tool. Reveal the hidden!
Probable (sub)domains
TL;DR
During bug bounties, penetrations tests, red teams exercises, and other great activities, there is always a room when you need to launch amass, subfinder, sublister, or any other tool to find subdomains you can use to break through - like test.google.com, dev.admin.paypal.com or staging.ceo.twitter.com. Within this repository, you will be able to find out the answers to the following questions:
- What are the most popular subdomains?
- What are the most common words in multilevel subdomains on different levels?
- What are the most used words in subdomains?
And, of course, wordlists for all of the questions above!
Methodology
As sources, I used lists of subdomains from public bugbounty programs, that were collected by chaos.projectdiscovery.io, bounty-targets-data or that just had responsible disclosure programs with a total number of 6831 domains! If subdomains appear more than in 5-10 different scopes, they will be put in a certain list. For example, if dev.stg appears both in *.google.com and *.twitter.com, it will have a frequency of 2. It does not matter how often dev.stg appears in *.google.com. That's all - nothing more, nothing less.
Lists
Subdomains
In these lists you will find most popular subdomains as is.
| Name | Words count | Size |
|---|---|---|
| subdomains.txt.gz | 24837884 | 522MB |
| subdomains_top100.txt | 100 | 655B |
| subdomains_top1000.txt | 1000 | 6.9KB |
| subdomains_top10000.txt | 10000 | 72KB |
Subdomain levels
In these lists, you will find the most popular words from subdomains split by levels. F.E - dev.stg subdomain will be split into two words dev and stg. dev will have level = 2, stg - level = 1. You can use these wordlists for combinatory attacks for subdomain searches. There are several types of level.txt wordlists that follow the idea of subdomains.
| Name | Words count | Size |
|---|---|---|
| level_1.txt.gz | 7703788 | 148MB |
| level_2.txt.gz | 11379683 | 131MB |
| level_3.txt.gz | 1158515 | 14MB |
| level_4.txt.gz | 179719 | 2.7MB |
| level_5.txt.gz | 73384 | 860KB |
| level_1_top100.txt | 100 | 620B |
| level_1_top1000.txt | 1000 | 6.3K |
| level_2_top100.txt | 100 | 550B |
| level_2_top1000.txt | 1000 | 5.8KB |
| level_3_top100.txt | 100 | 553B |
| level_3_top1000.txt | 1000 | 5.2KB |
| level_4_top100.txt | 100 | 530B |
| level_4_top1000.txt | 1000 | 5.1KB |
| level_5_top100.txt | 100 | 444B |
| level_5_top1000.txt | 1000 | 5.1KB |
Popular splitted subdomains
In these lists, you will find the most popular splitted words from subdomains on all levels. For example - dev.stg subdomain will be splitted in two words dev and stg.
| Name | Words count | Size |
|---|---|---|
| words.txt.gz | 20305456 | 293MB |
| words_top100.txt | 100 | 596B |
| words_top1000.txt | 1000 | 5.6KB |
| words_top10000.txt | 10000 | 62KB |
Dropbox
You can download all the files from Dropbox
Attributions
- berzerk0 for the inspiration with the great work Probable-Wordlists
- chaos.projectdiscovery.io
- bounty-targets-data/
- Based on some previous iteration of the same idea - https://github.com/zzzteph/substats
Thanks!
Updates
01.2023
- Sources 4095
- Subdomains 21901389
02.2023
- Sources 6831
- Subdomains 24837884
Probable (sub)domains
Danial Zahoor
Professional Ethical Hacker and Cybersecurity Researcher with a proven track record in dismantling online threats. Successfully neutralized 4 scammer networks, thwarted 13 phishing schemes, and disrupted 4 kidnapper networks. Committed to ensuring online safety and security, I leverage my expertise to protect individuals and organizations from digital threats. Passionate about cybersecurity education and empowering others to stay safe online.
