What You See is NOT What You Get: Discovering and Tracking Social Engineering Attack Campaigns

Abstract

Malicious ads often use social engineering (SE) tactics to coax users into downloading unwanted software, purchasing fake products or services, or giving up valuable personal information. These ads are often served by low-tier ad networks that may not have the technical means (or simply the will) to patrol the ad content they serve to curtail abuse. In this paper, we propose a system for large-scale automatic discovery and tracking of SE Attack Campaigns delivered via Malicious Advertisements (SEACMA). Our system aims to be generic, allowing us to study the SEACMA ad distribution problem without being biased towards specific categories of ad-publishing websites or SE attacks. Starting with a seed of low-tier ad networks, we measure which of these networks are the most likely to distribute malicious ads and propose a mechanism to discover new ad networks that are also leveraged to support the distribution of SEACMA campaigns. The results of our study aim to be useful in a number of ways. For instance, we show that SEACMA ads use a number of tactics to successfully evade URL blacklists and ad blockers. By tracking SEACMA campaigns, our system provides a mechanism to more proactively detect and block such evasive ads. Therefore, our results provide valuable information that could be used to improve defense systems against social engineering attacks and malicious ads in general.