Rock art, human-made markings on stone, is an important cultural artifact and the earliest expression of abstract thinking. While there are tens of millions of photographs of rock art in existence, there have been no large-scale attempts to organize, classify or cluster them. This omission is not due to a lack of interest, but reflects the extraordinary difficultly of extracting useful data from an incredibly heterogeneous and noisy dataset. As we shall show, rock art is likely to resist efforts of automatic extraction from images for a long time. In this work we show that we can use CAPTCHAs, puzzles designed to tell hu- mans and computers apart, to segment and index rock art. Unlike other CAPT- CHAs which operate on inherently discrete data and expect discrete responses, our method considers inherently real-valued data and expects real-valued re- sponses. This creates a challenge which we have overcome by using a recently introduced distance measure. We demonstrate our system is capable of acting as a secure CAPTCHA, while producing data that allows for indexing the rock art.