So, even if a bot does correctly decipher one, it must repeat the process thousands of times, which negatively impacts the speed that makes credential stuffing so viable. Furthermore, a solved CAPTCHA cannot be reused. And while a bot could be developed with these capabilities, it would be both incredibly time-consuming and expensive. The narrowly-defined nature of the tasks that bots perform prevents them from being able to interpret images or replicate the human responses that CAPTCHAs are based on.
Most people are familiar with the nature of these tests - having to pick things like buses and crosswalks out of a lineup of images - but they pose a problem for most bots. CAPTCHA stands for Completely Automated Public Turing Test to Tell Computers and Humans Apart. To combat this bot traffic over the past two decades, companies have been relying on the use of CAPTCHAs to distinguish between humans and bots. And all of this non-human traffic leads to both fraud losses for companies in addition to the increased compute costs it generates.
This incessant bot activity defrauds both users and businesses – when a user’s bank account is stolen, it’s typically the victim of a bot-powered credential stuffing attack. When you consider how pervasive non-human traffic is on the web and the potential threat this bot activity can pose to companies (brute forcing users’ passwords to steal their accounts, executing scripts to buy out concert tickets in order to profit on the secondary market, etc.), it’s not surprising that we’re often asked as users to prove our personhood when browsing the web. The other 61.5% is non-human (bots, hacking tools, etc). Today, humans only make up 38.5% of internet traffic.
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