This project implements a data-driven password meter. Its effects on password security and usability were evaluated in the following publication: http://www.blaseur.com/papers/CHI17meter.pdf and a demo is available at: https://cups.cs.cmu.edu/meter/
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abcdefghijklmnopqrstuvwxyz is a strong password #7
The utility judges abcdefghijklmnopqrstuvwxyz to be a strong password even though it clearly has a pattern. I understand that since this meter is data-driven, it cannot be expected to identify such patterns. Anyhow,
Is it feasible to improve the model to understand (such and other) patterns along with those in the training data?
Does it actually make sense for a password meter to have this capability?
The utility judges
abcdefghijklmnopqrstuvwxyzto be a strong password even though it clearly has a pattern. I understand that since this meter is data-driven, it cannot be expected to identify such patterns. Anyhow,