Automatically identifying trigger-based behavior in malware

David Brumley, Cody Hartwig, Zhenkai Liang, James Newsome, Dawn Song, Heng Yin

Research output: Chapter in Book/Report/Conference proceedingChapter

91 Scopus citations

Abstract

Malware often contains hidden behavior which is only activated when properly triggered. Well known examples include: the MyDoom worm which DDoS's on particular dates, keyloggers which only log keystrokes for particular sites, and DDoS zombies which are only activated when given the proper command. We call such behavior trigger-based behavior Currently, trigger-based behavior analysis is often performed in a tedious, manual fashion. Providing even a small amount of assistance would greatly assist and speed-up the analysis. In this chapter, we propose that automatic analysis of trigger-based behavior in malware is possible. In particular, we design an approach for automatic trigger-based behavior detection and analysis using dynamic binary instrumentation and mixed concrete and symbolic execution. Our approach shows that in many cases we can: (1) detect the existence of trigger-based behavior, (2) find the conditions that trigger such hidden behavior, and (3) find inputs that satisfy those conditions, allowing us to observe the triggered malicious behavior in a controlled environment. We have implemented MineSweeper, a system utilizing this approach. In our experiments, MineSweeper has successfully identified trigger-based behavior in real-world malware. Although there are many challenges presented by automatic trigger-based behavior detection, MineSweeper shows us that such automatic analysis is possible and encourages future work in this area.

Original languageEnglish (US)
Title of host publicationBotnet Detection
Subtitle of host publicationCountering the Largest Security Threat
EditorsWenke Lee, David Dagon, Cliff Wang
Pages65-88
Number of pages24
StatePublished - Dec 1 2008

Publication series

NameAdvances in Information Security
Volume36
ISSN (Print)1568-2633

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Automatically identifying trigger-based behavior in malware'. Together they form a unique fingerprint.

Cite this