I developed a novel type of CAPTCHA based on text comprehension and random tokens. Given a task
Pick the first pair of adjacent letters and a random token
8NBA596V, the user has to provide the solution
NB. It offers basic protection and an attacker can solve individual tasks with specific effort. I am curious, whether contemporary AI can solve it generically?
You can access more example tasks here: https://www.topincs.com/manual/captcha
There is a task database and at every attempt a new task is presented with a new random token. They always have a solution of varying length and pure guessing thus has limited chances of success. It is easy to attack an individual task by writing a small piece of code, thus a large task database is essential. What intrigues me is the question whether natural language processing or machine learning at its current state can attack the CAPTCHA generically by building a model of the meaning of the task – essentially a predicate in a tiny universe of discourse – and then applying it to the random token.