A feature matching-based attack on text CAPTCHAs
Jiawei Nian, Zongnan Liang, Xuru Wang, Jiaxuan Gao, Hongjin liu, Shaolin Zhang · 2022
CAPTCHA is a key defense technology that improves the security of a website. Text CAPTCHA schemes are the first barrier against attacks on major websites because of simplicity and low cost. In this paper, we proposed a novel, simple, and easy-to-operate feature matching approach to attack text CAPTCHAs. Our method combines a localization network and a feature matching network to attack three real-world text CAPTCHA schemes, including Wikipedia, Baidu and JD. We used 2000 samples for our attack experiments, and the results showed that our proposed method achieved high success rates on all three schemes.