typsqt-domains-dnstwist

name	typsqt-domains-dnstwist
description	Detect typosquatting, homograph phishing, and brand impersonation domains using dnstwist to generate domain permutations and identify registered lookalike domains targeting your organization.
domain	cybersecurity
subdomain	threat-intelligence
tags	["dnstwist","typosquatting","phishing","domain-monitoring","brand-protection","homograph","dns","threat-intelligence"]
version	1.0
author	mahipal
license	Apache-2.0
atlas_techniques	["AML.T0073","AML.T0052"]
nist_csf	["ID.RA-01","ID.RA-05","DE.CM-01","DE.AE-02"]

Analyzing Typosquatting Domains with DNSTwist

Overview

DNSTwist is a domain name permutation engine that generates similar-looking domain names to detect typosquatting, homograph phishing attacks, and brand impersonation. It creates thousands of domain permutations using techniques like character substitution, transposition, insertion, omission, and homoglyph replacement, then checks DNS records (A, AAAA, NS, MX), calculates web page similarity using fuzzy hashing (ssdeep) and perceptual hashing (pHash), and identifies potentially malicious registered domains.

When to Use

• When investigating security incidents that require analyzing typosquatting domains with dnstwist
• When building detection rules or threat hunting queries for this domain
• When SOC analysts need structured procedures for this analysis type
• When validating security monitoring coverage for related attack techniques

Prerequisites

• Python 3.9+ with dnstwist installed (pip install dnstwist[full])
• Optional: GeoIP database for IP geolocation
• Optional: Shodan API key for enrichment
• Network access to perform DNS queries
• Understanding of DNS record types and domain registration

Key Concepts

Domain Permutation Techniques

DNSTwist generates permutations using: addition (appending characters), bitsquatting (bit-flip errors), homoglyph (visually similar Unicode characters like rn vs m), hyphenation (adding hyphens), insertion (inserting characters), omission (removing characters), repetition (repeating characters), replacement (replacing with adjacent keyboard keys), subdomain (inserting dots), transposition (swapping adjacent characters), vowel-swap (swapping vowels), and dictionary-based (appending common words).

Fuzzy Hashing and Visual Similarity

DNSTwist uses ssdeep (locality-sensitive hash) to compare HTML content and pHash (perceptual hash) to compare screenshots of web pages. This helps identify cloned phishing sites that visually mimic the legitimate site. A high similarity score indicates a likely phishing page.

Detection Workflow

The typical workflow is: generate domain permutations -> resolve DNS records -> check for registered domains -> compare web page similarity -> flag suspicious domains -> alert security team -> request takedown. For a typical corporate domain, dnstwist generates 5,000-10,000 permutations.

Workflow

Step 1: Basic Domain Permutation Scan

import subprocess
import json
import csv
from datetime  datetime

 ():
    
    cmd = [
        ,
        ,     
        , , 
        , ,
        , ,
        ,        
        ,         
        ,          
        domain,
    ]

    ()
    result = subprocess.run(cmd, capture_output=, text=, timeout=)

     result.returncode == :
        results = json.loads(result.stdout)
        registered = [r  r  results  r.get()  r.get()]
        ()

         output_file:
             (output_file, )  f:
                json.dump(registered, f, indent=)
            ()

         registered
    :
        ()
         []

results = run_dnstwist_scan(, )