All Versions
10
Latest Version
Avg Release Cycle
79 days
Latest Release
539 days ago

Changelog History

  • v1.4.3

    December 04, 2018

    🚀 Release 1.4.3 fixes some performance issues which could lead to extremely long estimation times, and adds some new features.

    • ➕ Add support for scaling the offline guess speeds by a hardware cost.
    • Set minimum entropy now is able to be set by passing in how much time you want an attack to take using a specific guess type.
    • There is now a getBasicScore() method on Result which emulates the zxcvbn score (0-4)
  • v1.4.2

    July 20, 2018

    🚀 Release 1.4.2 adds support for using nbvcxz with Java 1.7+.

  • v1.4.1

    March 24, 2018

    🚀 Release 1.4.1 improves some translations, as well as adds support for additional languages.

    👍 The new languages supported are:

    • Dutch (nl)
    • German (de)
    • Italian (it)
    • Telugu (te)

    🌐 Thanks again to all who contributed their help with translation.

    🚀 Other features in this release are...

    • ⚡️ Updated the guesses / second for offline modes to provide more accurate representation of current hardware.
    • 👌 Improvements to feedback. We now give more customized recommendations based on the analysis of the password.
  • v1.4.0

    March 29, 2017

    🚀 Release 1.4.0 contains a few user visible features, most notably of which: Nbvcxz now supports 8 languages.

    👍 The languages supported are:

    • 0️⃣ English (default)
    • French (fr)
    • Spanish (es)
    • Portuguese (pt)
    • Russian (ru)
    • Ukrainian (uk)
    • Afrikaans (af)
    • Hungarian (hu)

    Thanks to all who contributed their help in translating.

    🚀 Other features in this release are...

    • 0️⃣ Default guesses/sec for offline guess types now have a Maintainer-hit-by-a-bus scaling mode.
      • In the case this library is no longer maintained (or you choose to stay on an old version of it), we will scale the existing values by Moore's law every year.
    • Feedback now returns a "result" text, letting the user know if their password met the minimum entropy or not.
  • v1.3.4

    February 27, 2017

    🚀 Update the default hashing speed to reflect new advances in hardware in the last 8 months. ~$20k will buy you approximately 1.7x hashing power now than it would prior to the Nvidia Pascal release.

  • v1.3.3

    February 17, 2017

    🚀 Release 1.3.3 - Fix for: #7

    Exclusion dictionaries were not working as expected with partial words. They previously only matched if the value in the exclusion dictionary matched the entire password. Now they will match a portion of the password.

    For example, if we added the users last name to an exclusion dictionary: Johnson
    and their password was mylongjohnson, it previously wouldn't match that exclusion dictionary on the "johnson" portion of that password. Now it will (giving that portion of the password 0 bits of entropy).

    ⚡️ I also added a new builder class for creating custom dictionaries, because they require all lower case words within them to work properly, so we need to make an easy way for users to do so. I also updated all javadoc comments to reflect that dictionaries need to contain lower case words.

  • v1.3.2

    February 09, 2017

    🚀 Release 1.3.2 - Fix for: #6

    🔧 Implemented a timeout for the findBestMatches algorithm which can be configured. If it exceeds the time specified, it will fallback to the findGoodEnoughMatches algorithm which is much faster, but also less likely to find the optimal match combination.

  • v1.3.1

    December 23, 2016

    🚑 Hotfix for last release.

  • v1.3.0

    December 23, 2016

    🚀 Release 1.3.0 - Nbvcxz gets a passphrase and password generator.

    🔧 You are now able to generate passphrases from either the standard (eff_large) dictionary, or any user supplied dictionary, with a configurable number of words and word delimiter.

    💅 There is also a random password generator if that's more your style. You can configure the character set to generate from, and the number of characters to generate.

  • v1.2.1

    December 19, 2016

    🔖 Version 1.2.1 is an optimization release.

    • 🐎 Performance improvements
    • 👍 Better memory use
    • Drastically less object allocations during estimation