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Passwords remain the most widely used form of user authentication, despiteadvancements in other methods. However, their limitations, such assusceptibility to attacks, especially weak passwords defined by human users,are well-documented. The existence of weak human-defined passwords has led torepeated password leaks from websites, many of which are of large scale. Whilesuch password leaks are unfortunate security incidents, they provide securityresearchers and practitioners with good opportunities to learn valuableinsights from such leaked passwords, in order to identify ways to improvepassword policies and other security controls on passwords. Researchers haveproposed different data visualisation techniques to help analyse leakedpasswords. However, many approaches rely solely on frequency analysis, withlimited exploration of distance-based graphs. This paper reports PassViz, anovel method that combines the edit distance with the t-SNE (t-distributedstochastic neighbour embedding) dimensionality reduction algorithm forvisualising and analysing leaked passwords in a 2-D space. We implementedPassViz as an easy-to-use command-line tool for visualising large-scalepassword databases, and also as a graphical user interface (GUI) to supportinteractive visual analytics of small password databases. Using the"000webhost" leaked database as an example, we show how PassViz can be used tovisually analyse different aspects of leaked passwords and to facilitate thediscovery of previously unknown password patterns. Overall, our approachempowers researchers and practitioners to gain valuable insights and improvepassword security through effective data visualisation and analysis.

PassViz: A Visualisation System for Analysing Leaked Passwords