JShield: towards real-time and vulnerability-based detection of polluted drive-by download attacks

Drive-by download attacks, which exploit vulnerabilities of web browsers to control client computers, have become a major venue for attackers. To detect such attacks, researchers have proposed many approaches such as anomaly-based [22, 23] and vulnerability-based [44, 50] detections. However, anomaly-based approaches are vulnerable to data pollution, and existing vulnerability-based approaches cannot accurately describe the vulnerability condition of all the drive-by download attacks. In this paper, we propose a vulnerability-based approach, namely JShield, which uses novel opcode vulnerability signature, a deterministic finite automaton (DFA) with a variable pool at opcode level, to match drive-by download vulnerabilities. We investigate all the JavaScript engine vulnerabilities of web browsers from 2009 to 2014, as well as those of portable document files (PDF) readers from 2007 to 2014. JShield is able to match all of those vulnerabilities; furthermore, the overall evaluation shows that JShield is so lightweight that it only adds 2.39 percent of overhead to original execution as the median among top 500 Alexa web sites.