C-Frame: Characterizing and measuring in-the-wild CAPTCHA attacks

In this paper, we design and implement C-Frame, the first measurement system to collect real-time, in-the-wild data on modern CAPTCHA attacks. For this, we study the recent evolution in the protocols of CAPTCHAs as well as human-driven farms that facilitate attacks against CAPTCHAs. This study leads us directly to the discovery of a unique vantage point to conduct a global-scale CAPTCHA attack measurement study. Harnessing this, we design and build C-Frame to be CAPTCHA-agnostic and ethically considerate. We then deploy our system for a 92-day period resulting in capturing of 425,257 CAPTCHA attacks on 1417 sites.In order to characterize these attacks, we leverage a carefully designed qualitative analysis approach using 3 analysts. Our study results in delineation of 34 different CAPTCHA-attack categories with several interesting real world attack examples. Twitter received the largest number of CAPTCHA attacks overall (about 255,480 attack requests) most of which attempt to create bot accounts. We also categorized and captured attacks such as ticket scalping attempts (e.g. a Taylor Swift concert event in Brazil), fraudulent lawsuit claims, and abusive appointment booking attempts (e.g. a Spain visa site in China). We also found CAPTCHA-assisted attempts to download data from government website (e.g. websites of 20 US states). We ascribe our attacks to 58 different countries across 5 continents. We present a detailed measurement analysis to give insights on this attack data and also suggest some future potential remediation measures that can be inspired by our system.