For over 30 years, password requirements and feedback have largely remained a product of LUDS: counts of lower- and uppercase letters, digits and symbols. LUDS remains ubiquitous despite being a conclusively burdensome and ineffective security practice. zxcvbn is an alternative password strength estimator that is small, fast, and crucially no harder than LUDS to adopt. Using leaked passwords, we compare its estimations to the best of four modern guessing attacks and show it to be accurate and conservative at low magnitudes, suitable for mitigating online attacks. We find 1.5 MB of compressed storage is sufficient to accurately estimate the best-known guessing attacks up to 105 guesses, or 104 and 103 guesses, respectively, given 245 kB and 29 kB. zxcvbn can be adopted with 4 lines of code and downloaded in seconds. It runs in milliseconds and works as-is on web, iOS and Android.

Features

  • zxcvbn allows many password styles to flourish so long as it detects sufficient complexity
  • Passphrases are rated highly given enough uncommon words, keyboard patterns are ranked based on length and number of turns, and capitalization adds more complexity when it's unpredictaBle
  • zxcvbn is designed to power simple, rule-free interfaces that give instant feedback
  • zxcvbn includes minimal, targeted verbal feedback that can help guide users towards less guessable passwords
  • zxcvbn detects and supports CommonJS
  • zxcvbn works identically on the server

Project Samples

Project Activity

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License

MIT License

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Additional Project Details

Operating Systems

Android, Apple iPhone

Programming Language

CoffeeScript

Related Categories

CoffeeScript Password Managers

Registered

2021-05-13