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See what sort of trouble users can get in trying to type your domain name. Find lookalike domains that adversaries can use to attack you. Can detect typosquatters, phishing attacks, fraud, and brand impersonation. Useful as an additional source of targeted threat intelligence.


DNS fuzzing is an automated workflow for discovering potentially malicious domains targeting your organisation. This tool works by generating a large list of permutations based on a domain name you provide and then checking if any of those permutations are in use. Additionally, it can generate fuzzy hashes of the web pages to see if they are part of an ongoing phishing attack or brand impersonation, and much more!

In a hurry? Try it in your web browser:

Key features

  • Variety of highly effective domain fuzzing algorithms
  • Unicode domain names (IDN)
  • Additional domain permutations from dictionary files
  • Efficient multithreaded task distribution
  • Live phishing webpage detection:
    • HTML similarity with fuzzy hashes (ssdeep/tlsh)
    • Screenshot visual similarity with perceptual hashes (pHash)
  • Rogue MX host detection (intercepting misdirected e-mails)
  • GeoIP location
  • Export to CSV and JSON


Python PIP

$ pip install dnstwist[full]

Alternatively install the bare minimum and add other requirements manually depending on your needs:

$ pip install dnstwist


If you want to run the latest version of the code, you can install it from Git:

$ git clone
$ cd dnstwist
$ pip install .

Debian/Ubuntu/Kali Linux

Invoke the following command to install the tool with all extra packages:

$ sudo apt install dnstwist

Fedora Linux

$ sudo dnf install dnstwist


This will install dnstwist along with all dependencies, and the binary will be added to $PATH.

$ brew install dnstwist


Pull and run official image from the Docker Hub:

$ docker run -it elceef/dnstwist

Alternatively you can build your local images:

$ docker build -t dnstwist .
$ docker build -t dnstwist:phash --build-arg phash=1 .

Quick start guide

The tool will run the provided domain name through its fuzzing algorithms and generate a list of potential phishing domains along with DNS records.

Usually thousands of domain permutations are generated - especially for longer input domains. In such cases, it may be practical to display only the ones that are registered:

$ dnstwist --registered

Ensure your DNS server can handle thousands of requests within a short period of time. Otherwise, you can specify an external DNS or DNS-over-HTTPS server with --nameservers argument.

If domain permutations generated by the fuzzing algorithms are insufficient, please supply dnstwist with a dictionary file. Some dictionary samples with a list of the most common words used in phishing campaigns are included.

$ dnstwist --dictionary dictionaries/english.dict

If you need to check whether domains with different TLD exist, just supply a dictionary file with the list of TLD.

$ dnstwist --tld dictionaries/common_tlds.dict

On the other hand, if only selected algorithms need to be used, --fuzzers argument is available, which takes a comma-separated list.

Note: non-existent algorithm names will be silently ignored.

$ dnstwist --fuzzers homoglyph,hyphenation

Apart from the colorful terminal output, the tool allows exporting results to CSV and JSON:

$ dnstwist --format csv | column -t -s,
$ dnstwist --format json | jq

In case you need just the bare permutations without making any DNS lookups, use --format list argument:

$ dnstwist --format list

The tool can perform real-time lookups to return geographical location (approximated to the country) of IPv4 addresses.

$ dnstwist --geoip

The GeoIP2 library is used by default. Country database location has to be specified with $GEOLITE2_MMDB environment variable. If the library or the database are not present, the tool will fall-back to the older GeoIP Legacy.

To display all available options with brief descriptions simply execute the tool without any arguments.

Phishing detection

Manually checking each domain name in terms of serving a phishing site might be time-consuming. To address this, dnstwist makes use of so-called fuzzy hashes (locality-sensitive hash, LSH) and perceptual hashes (pHash). Fuzzy hashing is a concept that involves the ability to compare two inputs (HTML code) and determine a fundamental level of similarity, while perceptual hash is a fingerprint derived from visual features of an image (web page screenshot).

Fuzzy hashing

The unique feature of detecting similar HTML source code can be enabled with --lsh argument. For each generated domain, dnstwist will fetch content from responding HTTP server (following possible redirects), normalize HTML code and compare its fuzzy hash with the one for the original (initial) domain. The level of similarity is be expressed as a percentage.

In cases when the effective URL is the same as for the original domain, the fuzzy hash is not calculated at all in order to reject false positive indications.

Note: Keep in mind it's rather unlikely to get 100% match, even for MITM attack frameworks, and that a phishing site can have a completely different HTML source code.

$ dnstwist --lsh

In some cases, phishing sites are served from a specific URL. If you provide a full or partial URL address as an argument, dnstwist will parse it and apply for each generated domain name variant. Use --lsh-url to override URL to fetch the original web page from.

$ dnstwist --lsh
$ dnstwist --lsh --lsh-url https://different.domain/owa/

By default, ssdeep is used as LSH algorithm, but TLSH is also available and can be enabled like so:

$ dnstwist --lsh tlsh

Perceptual hashing

If Chromium browser is installed, dnstwist can run it in so called headless mode (without GUI) to render web pages, take their screenshots and calculate pHash to evaluate visual similarity.

$ dnstwist --phash

Additionally, screenshots in PNG format can be saved to selected location:

$ dnstwist --phash --screenshots /tmp/domain

Note: Due to the multi-threaded use of a fully functional web browser, an appropriate amount of free resources (mainly memory) should be provided.


In case you need to consume the data produced by the tool within your code, probably the most convenient and fast way is to pass the input as follows.

>>> import dnstwist
>>> data ='', registered=True, format='null')

The arguments for are translated internally, so the usage is very similar to the command line. The returned data structure is an easy-to-process list of dictionaries. Keep in mind that spawns a number of daemon threads.

Notes on coverage

Along with the length of the domain, the number of variants generated by the algorithms increases considerably, and therefore the time and resources needed to verify them. It's mathematically impossible to check all domain permutations - especially for longer input domains which would require millions of DNS lookups. For this reason, this tool generates and checks domains very close to the original one. Theoretically, these are the most attractive domains from the attacker's point of view. However, be aware that the imagination of the aggressors is unlimited.

Unicode tables consist of thousands of characters with many of them visually similar to each other. However, despite the fact certain characters are encodable using punycode, most TLD authorities will reject them during domain registration process. In general, TLD authorities disallow mixing of characters coming from different Unicode scripts or maintain their own sets of acceptable characters. With that being said, the homoglyph fuzzer was build on top of carefully researched range of Unicode characters (homoglyphs) to ensure that generated domains can be registered in practice.


The scanner is utilized by tens of SOC and incident response teams around the globe, as well as independent information security analysts and researchers. On top of this, it's integrated into products and services of many security providers, in particular but not only:

Splunk ESCU, RecordedFuture, SpiderFoot, DigitalShadows, SecurityRisk, SmartFense, ThreatPipes, PaloAlto Cortex XSOAR, Rapid7 InsightConnect SOAR, Mimecast, Watcher, Intel Owl, PatrOwl, VDA Labs, Appsecco, Maltego, Conscia ThreatInsights.


To send questions, thoughts or a bar of chocolate, just drop an e-mail at Any feedback is appreciated. If you have found some confirmed phishing domains or just like this tool, please don't hesitate and send a message. Thank you.