Phishing is a security attack that involves obtaining sensitive or otherwise private data by presenting oneself as a trustworthy entity. Phishers often exploit users' trust on the appearance of a site by using web pages that are visually similar to an authentic site. This paper proposes a phishing detection approach -- PhishZoo -- that uses profiles of trusted websites' appearances to detect phishing. Our approach provides similar accuracy to blacklisting approaches (96%), with the advantage that it can classify zero-day phishing attacks and targeted attacks against smaller sites (such as corporate intranets). A key contribution of this paper is that it includes a performance analysis and a framework for making use of computer vision techniques in a practical way.