Towards Measuring and Mitigating Social Engineering Malware Download Attacks

Terry Nelms, Roberto Perdisci, Manos Antonakakis, Mustaque Ahamad
25th USENIX Security Symposium, 2016

Most modern malware infections happen through the browser, typically as the result of a drive-by or social engineering attack. While there have been numerous studies on measuring and defending against drive-by downloads, little attention has been dedicated to studying social engineering attacks. In this paper, we present the first systematic study of web-based social engineering (SE) attacks that successfully lure users into downloading malicious and unwanted software. To conduct this study, we collect and reconstruct more than two thousand examples of in-thewild SE download attacks from live network traffic. Via a detailed analysis of these attacks, we attain the following results: (i) we develop a categorization system to identify and organize the tactics typically employed by attackers to gain the user’s attention and deceive or persuade them into downloading malicious and unwanted applications; (ii) we reconstruct the web path followed by the victims and observe that a large fraction of SE download attacks are delivered via online advertisement, typically served from “low tier” ad networks; (iii) we measure the characteristics of the network infrastructure used to deliver such attacks and uncover a number of features that can be leveraged to distinguish between SE and benign (or non-SE) software downloads.