"Researchers Develop CAPTCHA Solver to Aid Dark Web Research"

A team of researchers from the Universities of Arizona, Georgia, and South Florida developed a Machine Learning (ML)-based CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart) solver claimed to be capable of overcoming over 90 percent of real challenges on dark web platforms. The goal of this study was to develop a system that can streamline cyber threat intelligence, which currently requires humans to manually solve dark web CAPTCHA challenges. Large-scale dark web data collection is often hindered by anti-crawling measures such as text-based CAPTCHA. This measure in the dark web identifies and blocks automated crawlers by forcing the user to enter a combination of hard-to-recognize alphanumeric characters, thus decreasing the transparency of the dark web for security researchers looking to prevent cyberattacks and data breaches. This article continues to discuss the ML-based system developed to counteract dark web text-based CAPTCHA for proactive cyber threat intelligence. 

Bleeping Computer reports "Researchers Develop CAPTCHA Solver to Aid Dark Web Research"