Abstract
Adobe Flash is a popular platform for providing dynamic and multimedia content on web pages. Despite being declared dead for years, Flash is still deployed on millions of devices. Unfortunately, the Adobe Flash Player increasingly suffers from vulnerabilities, and attacks using Flash-based malware regularly put users at risk of being remotely attacked. As a remedy, we present Gordon, a method for the comprehensive analysis and detection of Flash-based malware. By analyzing Flash animations at different levels during the interpreter’s loading and execution process, our method is able to spot attacks against the Flash Player as well as malicious functionality embedded in ActionScript code. To achieve this goal, Gordon combines a structural analysis of the container format with guided execution of the contained code, a novel analysis strategy that manipulates the control flow to maximize the coverage of indicative code regions. In an empirical evaluation with 26,600 Flash samples collected over 12 consecutive weeks, Gordon significantly outperforms related approaches when applied to samples shortly after their first occurrence in the wild, demonstrating its ability to provide timely protection for end users.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
md5: cac794adea27aa54f2e5ac3151050845.
- 2.
md5: 4f293f0bda8f851525f28466882125b7.
- 3.
Versions not supported by FlashDetect (version 8 and below) have been excluded.
References
Adobe Systems Incooperated: ActionScript virtual machine 2 (AVM2) overview. Technical report, Adobe System Incooperated (2007)
Adobe Systems Incooperated: SWF file format specification. Technical report, Adobe System Incooperated (2013)
Aho, A.V., Sethi, R., Ullman, J.D.: Compilers Principles, Techniques, and Tools, 2nd edn. Addison-Wesley, Reading (2006)
Baecher, P., Koetter, M.: libemu - x86 Shellcode Emulation (2008)
Biggio, B., Nelson, B., Laskov, P.: Poisoning attacks against support vector machines. In: Proceedings of International Conference on Machine Learning (ICML) (2012)
Brumley, D., Hartwig, C., Liang, Z., Newsome, J., Song, D., Yin, H.: Automatically identifying trigger-based behavior in malware. In: Lee, W., Wang, C., Dagon, D. (eds.) Botnet Detection, pp. 65–88. Springer, US (2008)
Canali, D., Cova, M., Vigna, G., Kruegel, C.: Prophiler: a fast filter for the large-scale detection of malicious web pages. In: Proceedings of the International World Wide Web Conference (WWW), pp. 197–206, April 2011
Cavallaro, L., Saxena, P., Sekar, R.: On the limits of information flow techniques for malware analysis and containment. In: Zamboni, D. (ed.) DIMVA 2008. LNCS, vol. 5137, pp. 143–163. Springer, Heidelberg (2008)
Cavnar, W., Trenkle, J.: N-gram-based text categorization. In: Proceedings of SDAIR, Las Vegas, pp. 161–175, NV, USA, April 1994
Chen, X., Andersen, J., Mao, Z.M., Bailey, M., Nazario, J.: Towards an understanding of anti-virtualization and anti-debugging behavior in modern malware. In: Proceedings of Conference on Dependable Systems and Networks (DSN), pp. 177–186 (2008)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms, 3rd edn. MIT Press, Cambridge (2009)
Cova, M., Felmetsger, V., Banks, G., Vigna, G.: Static detection of vulnerabilities in x86 executables. In: Proceedings of Annual Computer Security Applications Conference (ACSAC), pp. 269–278 (2006)
Cova, M., Kruegel, C., Vigna, G.: Detection and analysis of drive-by-download attacks and malicious JavaScript code. In: Proceedings of the International World Wide Web Conference (WWW), pp. 281–290 (2010)
Crandall, J.R., Wassermann, G., Oliveira, D.A.S., Su, Z., Wu, S.F., Chong, F.T.: Temporal search: detecting hidden malware timebombs with virtual machines. In: Proceedings of International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 25–36 (2006)
Cretu, G., Stavrou, A., Locasto, M., Stolfo, S., Keromytis, A.: Casting out demons: Sanitizing training data for anomaly sensors. In: Proceedings of IEEE Symposium on Security and Privacy, pp. 81–95 (2008)
Curtsinger, C., Livshits, B., Zorn, B., Seifert, C.: Zozzle: fast and precise in-browser JavaScript malware detection. In: Proceedings of USENIX Security Symposium, pp. 33–48 (2011)
Fogla, P., Lee, W.: Evading network anomaly detection systems: formal reasoning and practical techniques. In: Proceedings of ACM Conference on Computer and Communications Security (CCS), pp. 59–68 (2006)
Fogla, P., Sharif, M., Perdisci, R., Kolesnikov, O., Lee, W.: Polymorphic blending attacks. In: Proceedings of USENIX Security Symposium, pp. 241–256 (2006)
Ford, S., Cova, M., Kruegel, C., Vigna, G.: Analyzing and detecting malicious flash advertisements. In: Proceedings of Annual Computer Security Applications Conference (ACSAC), pp. 363–372 (2009)
gnash. GNU Gnash. https://www.gnu.org/software/gnash. Accessed April 2016
Hirvonen, T.: Dynamic flash instrumentation for fun and profit. In: Proceedings of Black Hat USA (2014)
httparchive. http://www.httparchive.org. Accessed April 2016
Huang, L., Joseph, A.D., Nelson, B., Rubinstein, B.I.P., Tygar, J.D.: Adversarial machine learning. In: Proceedings of ACM Workshop on Artificial Intelligence and Security (AISEC), pp. 43–58 (2011)
Jang, J., Agrawal, A., Brumley, D.: ReDeBug: finding unpatched code clones in entire os distributions. In: Proceedings of IEEE Symposium on Security and Privacy, pp. 48–62 (2012)
Johns, M., Lekies, S.: Biting the hand that serves you: a closer look at client-side flash proxies for cross-domain requests. In: Holz, T., Bos, H. (eds.) DIMVA 2011. LNCS, vol. 6739, pp. 85–103. Springer, Heidelberg (2011)
Kapravelos, A., Shoshitaishvili, Y., Cova, M., Kruegel, C., Vigna, G.: Revolver: an automated approach to the detection of evasive web-based malware. In: Proceedings of USENIX Security Symposium, pp. 637–651, August 2013
Kolbitsch, C., Livshits, B., Zorn, B., Seifert, C.: Rozzle: de-cloaking internet malware. In: Proceedings of IEEE Symposium on Security and Privacy, pp. 443–457 (2012)
Laskov, P., Šrndić, N.: Static detection of malicious javascript-bearing PDF documents. In: Proceedings of Annual Computer Security Applications Conference (ACSAC), pp. 373–382 (2011)
Louw, M.T., Thotta, K., Venkatakrishnan, V.N.: AdJail: practical enforcement of confidentiality and integrity policies on web advertisments. In: Proceedings of USENIX Security Symposium, pp. 371–388 (2010)
Moser, A., Kruegel, C., Kirda, E.: Exploring multiple execution paths for malware analysis. In: Proceedings of IEEE Symposium on Security and Privacy, pp. 231–245 (2007)
Nair, S.K., Simpson, P.N.D., Crispo, B., Tanenbaum, A.S.: A virtual machine based information flow control system for policy enforcement. Electron. Notes Theor. Comput. Sci. (ENTCS) 197(1), 3–16 (2008)
Özkan, S.: CVE Details. http://www.cvedetails.com. Accessed April 2016
Perdisci, R., Ariu, D., Fogla, P., Giacinto, G., Lee, W.: McPAD: a multiple classifier system for accurate payload-based anomaly detection. Comput. Netw. 5(6), 864–881 (2009)
Pignotti, A.: Lightspark. https://github.com/lightspark. Accessed April 2016
Ratanaworabhan, P., Livshits, B., Zorn, B.: Nozzle: a defense against heap-spraying code injection attacks. In: Proceedings of USENIX Security Symposium, pp. 169–186 (2009)
Saxena, P., Akhawe, D., Hanna, S., Mao, F., McCamant, S., Song, D.: A symbolic execution framework for javascript. In: Proceedings of IEEE Symposium on Security and Privacy, pp. 513–528 (2010)
Schölkopf, B., Smola, A.J.: Learning with Kernels. MIT Press, Cambridge (2002)
Sedgewick, R., Wayne, K.: Algorithms, 4th edn. Addison-Wesley, Boston (2011)
Shafiq, M.Z., Khayam, S.A., Farooq, M.: Embedded malware detection using markov n-grams. In: Zamboni, D. (ed.) DIMVA 2008. LNCS, vol. 5137, pp. 88–107. Springer, Heidelberg (2008)
Stolfo, S.J., Wang, K., Li, W.-J.: Towards stealthy malware detection. In: Christodorescu, M., Jha, S., Maughan, D., Song, D., Wang, C. (eds.) Malware Detection, pp. 231–249. Springer, USA (2007)
Suen, C.: N-gram statistics for natural language understanding, text processing. IEEE Trans. Pattern Anal. Mach. Intell. 1(2), 164–172 (1979)
Systems, A.: Adobe Flash runtimes: Statistics. http://www.adobe.com/products/flashruntimes/statistics.html. Accessed April 2016
van Acker, S., Nikiforakis, N., Desmet, L., Joosen, W., Piessens, F.: FlashOver: automated discovery of cross-site scripting vulnerabilities in rich internet applications. In: Proceedings of ACM Symposium on Information, Computer and Communications Security (ASIACCS) (2012)
Van Overveldt, T., Kruegel, C., Vigna, G.: FlashDetect: actionscript 3 malware detection. In: Balzarotti, D., Stolfo, S.J., Cova, M. (eds.) RAID 2012. LNCS, vol. 7462, pp. 274–293. Springer, Heidelberg (2012)
Šrndić, N., Laskov, P.: Detection of malicious PDF files based on hierarchical document structure. In: Proceedings of Network and Distributed System Security Symposium (NDSS) (2013)
Wagner, D., Soto, P.: Mimicry attacks on host based intrusion detection systems. In: Proceedings of ACM Conference on Computer and Communications Security (CCS), pp. 255–264 (2002)
Wang, K., Parekh, J.J., Stolfo, S.J.: Anagram: a content anomaly detector resistant to mimicry attack. In: Zamboni, D., Kruegel, C. (eds.) RAID 2006. LNCS, vol. 4219, pp. 226–248. Springer, Heidelberg (2006)
Wilhelm, J., Chiueh, T.: A forced sampled execution approach to kernel rootkit identification. In: Kruegel, C., Lippmann, R., Clark, A. (eds.) RAID 2007. LNCS, vol. 4637, pp. 219–235. Springer, Heidelberg (2007)
Wook Oh, J.: AVM inception - how we can use AVM instrumentation in a beneficial way. In: Shmoocon (2012)
Wressnegger, C., Boldewin, F., Rieck, K.: Deobfuscating embedded malware using probable-plaintext attacks. In: Stolfo, S.J., Stavrou, A., Wright, C.V. (eds.) RAID 2013. LNCS, vol. 8145, pp. 164–183. Springer, Heidelberg (2013)
Acknowledgments
The authors would like to thank Emiliano Martinez of VirusTotal for supporting the acquisition of malicious Flash files. Furthermore, we gratefully acknowledge funding from the German Federal Ministry of Education and Research (BMBF) under the projects APT-Sweeper (FKZ 16KIS0307) and INDI (FKZ 16KIS0154K) as well as the German Research Foundation (DFG) under project DEVIL (RI 2469/1-1).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Wressnegger, C., Yamaguchi, F., Arp, D., Rieck, K. (2016). Comprehensive Analysis and Detection of Flash-Based Malware. In: Caballero, J., Zurutuza, U., Rodríguez, R. (eds) Detection of Intrusions and Malware, and Vulnerability Assessment. DIMVA 2016. Lecture Notes in Computer Science(), vol 9721. Springer, Cham. https://doi.org/10.1007/978-3-319-40667-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-40667-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40666-4
Online ISBN: 978-3-319-40667-1
eBook Packages: Computer ScienceComputer Science (R0)