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Unrevealed Patterns in Password Databases Part One: Analyses of Cleartext Passwords

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Technology and Practice of Passwords (PASSWORDS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9393))

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Abstract

In this paper we present a regression based analyses of cleartext passwords moving towards an efficient password cracking methodology. Hundreds of available databases were examined and it was observed that they had similar behavior regardless of their size: password length distribution, entropy, letter frequencies form similar characteristics in each database. Exploiting these characteristics a huge amount of cleartext passwords were analyzed in order to be able to design more sophisticated brute-force attack methods. New patterns are exposed by analyzing millions of cleartext passwords.

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Notes

  1. 1.

    Exact numbers of PLD of Rockyou database can be found on passcape.com [14].

References

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Acknowledgment

We would like to thank the opportunity to the Hungarian NSA to grant access to unpublished Hungaraian databases that can not be found on the internet. Databases are originated from different vulnerability assessments and security hardening projects conducted by the National Security Authority of Hungary. For this project only truncated databases were provided. It means that databases do not contain any additional personal information about users, so it cannot be determined to whom the password belongs to. Password analysis and publication of this article is made with the authorization of the Hungarian NSA.

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Correspondence to Norbert Tihanyi .

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Tihanyi, N., Kovács, A., Vargha, G., Lénárt, Á. (2015). Unrevealed Patterns in Password Databases Part One: Analyses of Cleartext Passwords. In: Mjølsnes, S. (eds) Technology and Practice of Passwords. PASSWORDS 2014. Lecture Notes in Computer Science(), vol 9393. Springer, Cham. https://doi.org/10.1007/978-3-319-24192-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-24192-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24191-3

  • Online ISBN: 978-3-319-24192-0

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