PhishInPatterns: measuring elicited user interactions at scale on phishing websites

Despite phishing attacks and detection systems being extensively studied, phishing is still on the rise and has recently reached an all-time high. Attacks are becoming increasingly sophisticated, leveraging new web design patterns to add perceived legitimacy and, at the same time, evade state-of-the-art detectors and web security crawlers.

In this paper, we study phishing attacks from a new angle, focusing on how modern phishing websites are designed. Specifically, we aim to better understand what type of user interactions are elicited by phishing websites and how their user experience (UX) and interface (UI) design patterns can help them accomplish two main goals: i) lend a sense of professionalism and legitimacy to the phishing website, and ii) contribute to evading phishing detectors and web security crawlers. To study phishing at scale, we built an intelligent crawler that combines browser automation with machine learning methods to simulate user interactions with phishing pages and explore their UX and UI characteristics. Using our novel methodology, we explore more than 50,000 phishing websites and make the following new observations: i) modern phishing sites often impersonate a brand (e.g., Microsoft Office), but surprisingly, without necessarily cloning or closely mimicking the design of the corresponding legitimate website; ii) they often elicit personal information using a multi-step (or multi-page) process, to mimic users' experience on legitimate sites; iii) they embed modern user verification systems (including CAPTCHAs); and ironically, iv) they sometimes conclude the phishing experience by reassuring the user that their private data was not stolen. We believe our findings can help the community gain a more in-depth understanding of how web-based phishing attacks work from a users' perspective and can be used to inform the development of more accurate and robust phishing detectors.