Wordlist Download: A Guide to Finding and Using Wordlists
A wordlist is a list of words, phrases, passwords, or other strings that are used for various purposes, such as password cracking, content discovery, language learning, etc. Wordlists can be obtained from different sources, such as online repositories, dictionaries, corpora, or generated by tools. In this article, I will show you some examples of wordlists and how to use them effectively.
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Types of wordlists
Wordlists can be classified into different types based on their content and format. Some common types are:
General vs. specific wordlists: General wordlists contain common words or strings that are likely to appear in any context, such as the most frequent words in a language or the most common passwords. Specific wordlists contain words or strings that are relevant to a particular domain or topic, such as technical terms, names, or slang.
Static vs. dynamic wordlists: Static wordlists are fixed and do not change over time. They are usually based on existing sources or data sets. Dynamic wordlists are updated or generated on the fly based on new information or user input. They are usually created by tools or algorithms.
Sources of wordlists
There are many sources of wordlists available online or offline. Some popular sources are:
Online repositories: These are websites or platforms that host and share wordlists created by users or communities. Some examples are GitHub, SecLists, and Probable-Wordlists. These repositories often contain a variety of wordlists for different purposes and languages.
Dictionaries: These are collections of words and their meanings, usually arranged alphabetically. They can be used as wordlists for language learning or vocabulary expansion. Some examples are Oxford Learner's Dictionaries, Cambridge Dictionary, and Merriam-Webster Dictionary. These dictionaries often provide additional information about the words, such as pronunciation, usage, synonyms, etc.
Corpora: These are large and structured sets of texts or speech that represent natural language use in a specific context or genre. They can be used as wordlists for linguistic analysis or text generation. Some examples are British National Corpus, Corpus of Contemporary American English, and SUBTLEX. These corpora often provide frequency data and other statistics about the words.
Tools: These are software applications or scripts that can generate or modify wordlists based on various criteria or inputs. Some examples are Hashcat, Mentalist, and CUPP. These tools often allow users to customize and optimize their wordlists for specific tasks or targets.
Examples of wordlists
Wordlists can be used for different purposes depending on the user's needs and goals. Here are some examples of wordlists for common scenarios:
Wordlists for password cracking
Password cracking is the process of recovering passwords from data that has been stored in or transmitted by a computer system. Wordlists are often used in password cracking to perform dictionary attacks, which try to guess passwords by using a list of possible candidates. Password cracking can be done for legitimate reasons, such as testing the security of a system or recovering forgotten passwords, or for malicious reasons, such as hacking into someone else's account or stealing sensitive information.
To perform a successful dictionary attack, the word list should contain words or strings that are likely to be used as passwords by the target system or user. Some factors that can affect the choice of wordlist are:
The type of system or service: Different systems or services may have different password policies or requirements, such as length, complexity, or format. For example, some websites may require passwords to contain at least one uppercase letter, one lowercase letter, one digit, and one special character. Some systems or services may also have common or default passwords that can be easily guessed.
The language or culture of the user: Different languages or cultures may have different preferences or habits for choosing passwords, such as using words from their native language, personal names, dates, slang, etc. For example, some Spanish speakers may use words like "amor", "familia", or "futbol" as passwords. Some Chinese users may use numbers that sound like words, such as "520" for "I love you".
The level of sophistication of the user: Different users may have different levels of awareness or knowledge about password security and best practices, such as using unique and random passwords, avoiding common or predictable patterns, or changing passwords regularly. For example, some novice or careless users may use simple or weak passwords, such as "password", "123456", or "qwerty". Some advanced or cautious users may use complex or strong passwords, such as "g4H!2#n9", "Mj7@xQ3Z", or "pR8wT6yK".
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Wordlist
Description
Source
RockYou
A list of 14 million passwords that were leaked from the social networking site RockYou in 2009. It contains many common and weak passwords, such as "123456", "iloveyou", or "princess".
SecLists Passwords
A collection of wordlists for password cracking curated by Daniel Miessler. It contains various types of wordlists, such as common passwords, default passwords, leaked passwords, keyboard patterns, etc.
Probable-Wordlists Top 207
A list of the top 207 most probable passwords based on frequency analysis and probability calculations. It contains many popular and easy-to-guess passwords, such as "password1", "abc123", or "letmein".
CUPP Common User Passwords Profiler
A tool that can generate wordlists based on personal information about the target user, such as name, date of birth, hobbies, pets, etc. It can create customized and realistic passwords that the user may use.
Hashcat Rule-based Attack
A method that can modify wordlists by applying rules that mimic common password transformations, such as appending numbers, changing cases, replacing letters with symbols, etc. It can increase the chances of cracking passwords that are based on words with slight variations.
Wordlists for web content discovery
Web content discovery is the process of finding and identifying web pages, files, directories, or other resources that are hosted on a web server or application. Wordlists are often used in web content discovery to perform brute force attacks, which try to enumerate and request possible URLs by using a list of common names or extensions. Web content discovery can be done for legitimate reasons, such as testing the security or functionality of a web site or application, or for malicious reasons, such as finding vulnerabilities or sensitive information.
To perform a successful brute force attack, the wordlist should contain names or extensions that are likely to be used by the target web server or application. Some factors that can affect the choice of wordlist are:
The type of web server or application: Different web servers or applications may have different naming conventions or structures for their web resources, such as directories, files, parameters, etc. For example, some web servers may use default names for their directories, such as "admin", "images", or "css". Some web applications may use specific extensions for their files, such as ".php", ".asp", or ".jsp".
The language or framework of the web server or application: Different languages or frameworks may have different features or components that can be used to create web resources, such as libraries, modules, plugins, etc. For example, some Python web applications may use Flask, Django, or Bottle as their frameworks. Some WordPress sites may use WooCommerce, Jetpack, or Yoast as their plugins.
The content or purpose of the web server or application: Different web servers or applications may have different types of content or functionality that can be accessed by web resources, such as images, videos, documents, forms, etc. For example, some e-commerce sites may have web resources related to products, categories, carts, orders, etc. Some social media sites may have web resources related to profiles, posts, messages, etc.
Some examples of wordlists for web content discovery are:
Wordlist
Description
Source
DirBuster
A list of common directory and file names that are used by many web servers and applications. It contains over 2000 entries with various extensions and variations.
SecLists Discovery
A collection of wordlists for web content discovery curated by Daniel Miessler. It contains various types of wordlists, such as directory names, file names, parameter names, subdomain names, etc.
FuzzDB
A list of common and uncommon strings that are used to test the security and functionality of web servers and applications. It contains over 1000 entries with various formats and encodings.
Wfuzz
A tool that can generate wordlists based on patterns and permutations. It can create customized and flexible wordlists for different scenarios and targets.
Gobuster
A tool that can perform brute force attacks using wordlists. It can request multiple URLs in parallel and filter the results based on status codes, sizes, words, etc.
Wordlists for language learning
Language learning is the process of acquiring or improving one's knowledge and skills of a language other than one's native language. Wordlists are often used in language learning to expand one's vocabulary, improve one's pronunciation, or practice one's grammar. Language learning can be done for various reasons, such as personal interest, education, travel, work, etc.
To use wordlists effectively for language learning, the wordlist should contain words or phrases that are relevant to one's level, goal, and interest. Some factors that can affect the choice of wordlist are:
The level of proficiency: Different levels of proficiency may require different types and amounts of words or phrases to learn. For example, beginners may need to learn basic words and phrases that are essential for everyday communication, such as greetings, numbers, colors, etc. Intermediate learners may need to learn more complex words and phrases that are related to specific topics or situations, such as hobbies, travel, health, etc. Advanced learners may need to learn more nuanced words and phrases that are used in formal or academic contexts, such as idioms, metaphors, synonyms, etc.
The goal of learning: Different goals of learning may require different focus or emphasis on certain aspects of the language. For example, learners who want to improve their speaking or listening skills may need to learn more words and phrases that are commonly used in spoken language, such as slang, expressions, filler words, etc. Learners who want to improve their reading or writing skills may need to learn more words and phrases that are commonly used in written language, such as vocabulary, grammar, punctuation, etc.
The interest of learning: Different interests of learning may require different selection or preference of words or phrases to learn. For example, learners who are interested in a particular culture or country may need to learn more words and phrases that are related to that culture or country, such as food, music, history, etc. Learners who are interested in a particular field or subject may need to learn more words and phrases that are related to that field or subject, such as science, art, business, etc.
Some examples of wordlists for language learning are:
Wordlist
Description
Source
Oxford 3000
A list of the 3000 most important and useful words to learn in English. It covers various topics and levels and is based on extensive research and analysis.
Cambridge English Vocabulary Profile
A list of the words and phrases that learners of English typically know at each level of the Common European Framework of Reference (CEFR). It provides detailed information about the meaning, usage, and frequency of each word or phrase.
Mosalingua
A list of the most frequent and relevant words and phrases to learn in various languages, such as Spanish, French, German, Italian, etc. It uses a spaced repetition system (SRS) to help learners memorize and recall the words or phrases effectively.
Anki
A tool that can create and use wordlists based on flashcards. It allows users to customize and organize their wordlists according to their needs and preferences.
Duolingo
A tool that can teach and test wordlists based on interactive lessons and exercises. It offers wordlists for various languages and levels and adapts to the user's progress and performance.
How to use wordlists
Wordlists are powerful and versatile tools that can help users achieve various goals and tasks. However, to use wordlists effectively, users need to consider some factors and apply some strategies, such as:
Choosing the right wordlist: Users need to select a wordlist that matches their purpose, target, and context. They need to evaluate the quality, quantity, and relevance of the wordlist and compare it with other available options. They also need to check the source, format, and license of the wordlist and make sure it is reliable, compatible, and legal.
Applying rules and filters: Users need to optimize their wordlist by applying rules and filters that can enhance or reduce its effectiveness. They need to use rules and filters that can modify, combine, or exclude words or strings based on various criteria, such as length, frequency, pattern, etc. They also need to test and measure the impact of the rules and filters on the wordlist and adjust them accordingly.
Combining and modifying wordlists: Users need to diversify their wordlist by combining and modifying it with other wordlists or sources. They need to use tools or methods that can merge, append, or generate new words or strings based on existing ones. They also need to update and maintain their wordlist by adding or removing words or strings based on new information or feedback.
Conclusion
Wordlists are useful and valuable resources that can help users with various purposes and tasks, such as password cracking, web content discovery, language learning, etc. Wordlists can be obtained from different sources, such as online repositories, dictionaries, corpora, or tools. Wordlists can be classified into different types based on their content and format, such as general vs. specific wordlists or static vs. dynamic wordlists. To use wordlists effectively, users need to choose the right wordlist, apply rules and filters, and combine and modify wordlists according to their needs and goals.
FAQs
What is a wordlist?
A wordlist is a list of words, phrases, passwords, or other strings that are used for various purposes, such as password cracking, content discovery, language learning, etc.
Where can I find wordlists?
You can find wordlists from different sources, such as online repositories, dictionaries, corpora, or tools. Some examples are GitHub, SecLists, Probable-Wordlists, Oxford Learner's Dictionaries, Cambridge Dictionary, Merriam-Webster Dictionary, British National Corpus, Corpus of Contemporary American English, SUBTLEX, Hashcat, Mentalist, and CUPP.
How can I use wordlists?
You can use wordlists for different purposes depending on your needs and goals. Some examples are password cracking, web content discovery, language learning, etc. To use wordlists effectively, you need to choose the right wordlist, apply rules and filters, and combine and modify wordlists according to your purpose, target, and context.
What are some types of wordlists?
Wordlists can be classified into different types based on their content and format. Some common types are general vs. specific wordlists; static vs. dynamic wordlists; alphabetical vs. frequency-based wordlists; single-word vs. multi-word wordlists; etc.
How can I create my own wordlist?
You can create your own wordlist by using tools or methods that can generate or modify words or strings based on various criteria or inputs. Some examples are Hashcat, Mentalist, CUPP, Wfuzz, Gobuster, etc. 44f88ac181