Interactive, Visual-aided Tools To Analyze Malware Behavior

Malicious software attacks can disrupt information systems, violating security principles of availability, confidentiality and integrity. Attackers use malware to gain control, steal data, keep access and cover traces left on the compromised systems. The dynamic analysis of malware is useful to obtain an execution trace that can be used to assess the extent of an attack, to do incident response and to point to adequate counter-measures. An analysis of the captured malware can provide analysts with information about its behavior, allowing them to review the malicious actions performed during its execution on the target. The behavioral data gathered during the analysis consists of filesystem and network activity traces; a security analyst would have a hard time sieving through a maze of textual event data in search of relevant information. We present a behavioral event visualization framework that allows for an easier realization of the malicious chain of events and for quickly spotting interesting actions performed during a security compromise. Also, we analyzed more than 400 malware samples from different families and showed that they can be classified based on their visual signature. Finally, we distribute one of our tools to be freely used by the community. © 2012 Springer-Verlag.7336 LNCSPART 4302313Universidade Federal da Bahia (UFBA),Universidade Federal do Reconcavo da Bahia (UFRB),Universidade Estadual de Feira de Santana (UEFS),University of Perugia,University of Basilicata (UB)Buehlmann, S., Liebchen, C., Joebox: A Secure Sandbox Application for Windows to Analyse the Behaviour of Malware, , http://www.joebox.orgClam Antivirus, , http://www.clamav.netConti, G., Dean, E., Sinda, M., Sangster, B., Visual Reverse Engineering of Binary and Data Files (2008) LNCS, 5210, pp. 1-17. , Goodall, J.R., Conti, G., Ma, K.-L. (eds.) VizSec 2008. Springer, HeidelbergEick, S.G., Steffen, J.L., Sumner Jr., E.E., Seesoft-A Tool for Visualizing Line Oriented Software Statistics (1992) IEEE Transactions on Software Engineering, 18 (11), pp. 957-968Grégio, A.R.A., Oliveira, I.L., Dos Santos, R.D.C., Cansian, A.M., De Geus, P.L., Malware distributed collection and pre-classification system using honeypot technology (2009) Proceedings of SPIE, 7344, pp. 73440B-73440B10Grégio, A.R.A., Fernandes Filho, D.S., Afonso, V.M., Dos Santos, R.D.C., Jino, M., De Geus, P.L., Behavioral analysis of malicious code through network traffic and system call monitoring (2011) Proceedings of SPIE, 8059, pp. 80590O-80590O10http://dionaea.carnivore.it, The Honeynet ProjectKruegel, C., Kirda, E., Bayer, U., Ttanalyze: A tool for analyzing malware Proceedings of the 15th European Institute for Computer Antivirus Research (EICAR 2006) Annual Conference (2006)MBS Tool. Malicious Behavior's Spiral - Beta Version, , http://www.las.ic.unicamp.br/~gregio/mbsProvos, N., Holz, T., (2007) Virtual Honeypots: From Botnet Tracking to Intrusion Detection, , Addison-Wesley ProfessionalProvos, N., Honeyd - A Virtual Honeypot Daemon 10th DFNCERT Workshop (2003)Quist, D., Liebrock, L., Visualizing Compiled Executables for Malware Analysis (2009) Proceedings of the Workshop on Visualization for Cyber Security, pp. 27-32Read, H., Xynos, K., Blyth, A., Presenting DEViSE: Data Exchange for Visualizing Security Events (2009) IEEE Computer Graphics and Applications, 29, pp. 6-11http://www.threatexpert.comTrinius, P., Holz, T., Gobel, J., Freiling, F.C., Visual analysis of malware behavior using treemaps and thread graphs (2009) International Workshop on Visualization for Cyber Security(VizSec), pp. 33-3