A Large-Scale Measurement of Website Login Policies

Authenticating on a website using a password involves a multi-stage login process, where each stage entails critical policy and implementation decisions that impact login security and usability. While the security community has identified best practices for each stage of the login workflow, we currently lack a broad understanding of website login policies in practice. Prior work relied upon manual inspection of websites, producing evaluations of only a small population of sites skewed towards the most popular ones.

In this work, we seek to provide a more comprehensive and systematic picture of real-world website login policies. We develop an automated method for inferring website login policies and apply it to domains across the Google CrUX Top 1 Million. We successfully evaluate the login policies on between 18K and 359K sites (varying depending on the login stage considered), providing characterization of a population two to three orders of magnitude larger than previous studies. Our findings reveal the extent to which insecure login policies exist and identify some underlying causes. Ultimately, our study provides the most comprehensive empirical grounding to date on the state of website login security, shedding light on directions for improving online authentication.