A realistic password strength estimation library for iOS, using pattern matching and conservative entropy calculations.
DBZxcvbn is an iOS library that estimates password strength using pattern matching and entropy calculations. It helps developers build secure authentication flows by analyzing passwords against common patterns, dictionaries, and user inputs to provide realistic security feedback.
iOS developers building apps with password-based authentication who need to implement robust password strength estimation and user guidance.
Developers choose DBZxcvbn because it offers a realistic, pattern-based approach to password strength estimation, avoiding simplistic rules, and includes ready-to-use UI components like DBPasswordStrengthMeter for easy integration.
A realistic password strength estimator.
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Uses advanced detection for sequences, repeats, dates, and QWERTY layouts to avoid simplistic rules, aligning with the project's philosophy of realistic estimation.
Includes DBPasswordStrengthMeter for ready-to-use UI components in forms, as shown in the example DBCreateAccountViewController.m for seamless implementation.
Allows adding user inputs like email or name via the userInputs parameter to heavily penalize personal info, enhancing security for specific contexts.
Provides entropy, crack time estimates, and a 0-4 score in DBResult, enabling deep analysis for developers to build informed password strength meters.
The README states 'Installation: Coming soon.', making setup difficult and suggesting potential maintenance issues or poor documentation.
Limited to Objective-C, requiring bridging for Swift projects, which adds complexity and may not align with modern iOS development trends.
As a port of the original zxcvbn, it might not receive updates as quickly as the JavaScript or Python versions, risking feature gaps.