Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2068816.2068854acmconferencesArticle/Chapter ViewAbstractPublication PagesimcConference Proceedingsconference-collections
research-article

GQ: practical containment for measuring modern malware systems

Published: 02 November 2011 Publication History
  • Get Citation Alerts
  • Abstract

    Measurement and analysis of modern malware systems such as botnets relies crucially on execution of specimens in a setting that enables them to communicate with other systems across the Internet. Ethical, legal, and technical constraints however demand containment of resulting network activity in order to prevent the malware from harming others while still ensuring that it exhibits its inherent behavior. Current best practices in this space are sorely lacking: measurement researchers often treat containment superficially, sometimes ignoring it altogether. In this paper we present GQ, a malware execution "farm" that uses explicit containment primitives to enable analysts to develop containment policies naturally, iteratively, and safely. We discuss GQ's architecture and implementation, our methodology for developing containment policies, and our experiences gathered from six years of development and operation of the system.

    References

    [1]
    P. Barford and M. Blodgett. Toward botnet mesocosms. In Proceedings of the First Workshop on Hot Topics in Understanding Botnets, Berkeley, CA, USA, 2007. USENIX Association.
    [2]
    U. Bayer, C. Kruegel, and E. Kirda. TTAnalyze: A tool for analyzing malware. In 15th Annual Conference of the European Institute for Computer Antivirus Research (EICAR), 2006.
    [3]
    J. Caballero, C. Grier, C. Kreibich, and V. Paxson. Measuring Pay-per-Install: The Commoditization of Malware Distribution. In Proceedings of the 20th USENIX Security Symposium, San Francisco, CA, USA, August 2011.
    [4]
    J. Caballero, P. Poosankam, C. Kreibich, and D. Song. Dispatcher: Enabling active botnet infiltration using automatic protocol reverse-engineering. In Proceedings of the 16th ACM CCS, pages 621--634, Chicago, IL, USA, November 2009.
    [5]
    J. Calvet, C. R. Davis, J. M. Fernandez, J.-Y. Marion, P.-L. St-Onge, W. Guizani, P.-M. Bureau, and A. Somayaji. The case for in-the-lab botnet experimentation: creating and taking down a 3000-node botnet. In Proceedings of the 26th ACSAC Conference, pages 141--150, New York, NY, USA, 2010. ACM.
    [6]
    CBL. Composite Blocking List. http://cbl.abuseat.org, 2003.
    [7]
    J. Chen, J. McCullough, and A. C. Snoeren. Universal Honeyfarm Containment. Technical Report CS2007-0902, UCSD, September 2007.
    [8]
    X. Chen, J. Andersen, Z. Mao, M. Bailey, and J. Nazario. Towards an understanding of anti-virtualization and anti-debugging behavior in modern malware. In Proceedings of the 38th Conference on Dependable Systems and Networks (DSN), pages 177--186. IEEE, 2008.
    [9]
    W. Cui, V. Paxson, and N. Weaver. GQ: Realizing a System to Catch Worms in a Quarter Million Places. Technical Report TR-06-004, International Computer Science Institute, September 2006.
    [10]
    A. W. Jackson, D. Lapsley, C. Jones, M. Zatko, C. Golubitsky, and W. T. Strayer. SLINGbot: A System for Live Investigation of Next Generation Botnets. In Proceedings of the 2009 Cybersecurity Applications & Technology Conference for Homeland Security, pages 313--318, Washington, DC, USA, 2009. IEEE Computer Society.
    [11]
    X. Jiang and D. Xu. Collapsar: A VM-based architecture for network attack detention center. In Proceedings of the 13th USENIX Security Symposium, page 2. USENIX Association, 2004.
    [12]
    J. John, A. Moshchuk, S. Gribble, and A. Krishnamurthy. Studying spamming botnets using Botlab. In Proceedings of the 6th USENIX Symposium on Networked Systems Design and Implementation, pages 291--306. USENIX Association, 2009.
    [13]
    C. Kanich, C. Kreibich, K. Levchenko, B. Enright, G. M. Voelker, V. Paxson, and S. Savage. Spamalytics: An empirical analysis of spam marketing conversion. In Proceedings of the 15th ACM Conference on Computer and Communications Security, pages 3--14, Alexandria, Virginia, USA, October 2008.
    [14]
    T. Kerremans and B. Verstricht. Trinity Rescue Kit. http://trinityhome.org.
    [15]
    D. Koblas. SOCKS. In Proceedings of the 3rd USENIX Security Symposium. USENIX Association, September 1992.
    [16]
    E. Kohler, R. Morris, B. Chen, J. Jannotti, and M. Kaashoek. The Click modular router. ACM Transactions on Computer Systems (TOCS), 18(3):263--297, 2000.
    [17]
    C. Kolbitsch, T. Holz, C. Kruegel, and E. Kirda. Inspector Gadget: Automated extraction of proprietary gadgets from malware binaries. In 2010 IEEE Symposium on Security and Privacy, pages 29--44. IEEE, 2010.
    [18]
    C. Kreibich, C. Kanich, K. Levchenko, B. Enright, G. M. Voelker, V. Paxson, and S. Savage. On the Spam Campaign Trail. In Proceedings of the First USENIX Workshop on Large-scale Exploits and Emergent Threats (LEET), San Francisco, USA, April 2008.
    [19]
    C. Kreibich, C. Kanich, K. Levchenko, B. Enright, G. M. Voelker, V. Paxson, and S. Savage. Spamcraft: An inside look at spam campaign orchestration. In Proceedings of the Second USENIX Workshop on Large-scale Exploits and Emergent Threats (LEET), Boston, USA, April 2009.
    [20]
    N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner. OpenFlow: Enabling Innovation In Campus Networks. ACM SIGCOMM Computer Communication Review, 38(2):69--74, 2008.
    [21]
    B. Miller, P. Pearce, C. Grier, C. Kreibich, and V. Paxson. What's Clicking What? Techniques and Inovations of Today's Clickbots. In Conference on Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA). Springer, July 2011.
    [22]
    J. Mirkovic, T. V. Benzel, T. Faber, R. Braden, J. T. Wroclawski, and S. Schwab. The DETER project: Advancing the science of cyber security experimentation and test. In IEEE Intl. Conference on Technologies for Homeland Security (HST), page 7, November 2010.
    [23]
    Norman ASA. Norman SandBox. http://www.norman.com/security_center/security_tools/.
    [24]
    V. Paxson. Bro: A System for Detecting Network Intruders in Real-Time. Proceedings of the 7th USENIX Security Symposium, pages 31--51, 1998.
    [25]
    A. Pitsillidis, K. Levchenko, C. Kreibich, C. Kanich, G. Voelker, V. Paxson, N. Weaver, and S. Savage. Botnet Judo: Fighting Spam with Itself . In Proceedings of the 17th Annual Network and Distributed System Security Symposium(NDSS), San Diego, CA, USA, March 2010.
    [26]
    J. Postel. Simple Mail Transfer Protocol. RFC 821, August 1982.
    [27]
    G. Tenebro. W32.Waledac Threat Analysis. http://www.symantec.com/content/en/us/enterprise/media/security_respons%e/whitepapers/W32_Waledac.pdf, 2009.
    [28]
    N. Villeneuve. Koobface: Inside a Crimeware Network. http://www.infowar-monitor.net/reports/iwm-koobface.pdf, November 2010.
    [29]
    M. Vrable, J. Ma, J. Chen, D. Moore, E. Vandekieft, A. Snoeren, G. Voelker, and S. Savage. Scalability, fidelity, and containment in the potemkin virtual honeyfarm. ACM SIGOPS Operating Systems Review, 39(5):148--162, 2005.
    [30]
    Y. Wang, D. Beck, X. Jiang, and R. Roussev. Automated Web Patrol with Strider Honeymonkeys: Finding Web Sites that Exploit Browser Vulnerabilities. In Proceedings of the 13th Annual Network and Distributed System Security Symposium (NDSS), San Diego, CA, USA, March 2006.
    [31]
    C. Willems, T. Holz, and F. Freiling. Toward automated dynamic malware analysis using CWSandbox. IEEE Security & Privacy, pages 32--39, 2007.

    Cited By

    View all
    • (2019)Improving IoT Botnet Investigation Using an Adaptive Network LayerSensors10.3390/s1903072719:3(727)Online publication date: 11-Feb-2019
    • (2019)A Secure Contained Testbed for Analyzing IoT BotnetsTestbeds and Research Infrastructures for the Development of Networks and Communities10.1007/978-3-030-12971-2_8(124-137)Online publication date: 2-Feb-2019
    • (2018)HoneyCirculatorInternational Journal of Information Security10.1007/s10207-017-0361-517:2(135-151)Online publication date: 1-Apr-2018
    • Show More Cited By

    Index Terms

    1. GQ: practical containment for measuring modern malware systems

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      IMC '11: Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
      November 2011
      612 pages
      ISBN:9781450310130
      DOI:10.1145/2068816
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

      Sponsors

      In-Cooperation

      • USENIX Assoc: USENIX Assoc

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 02 November 2011

      Permissions

      Request permissions for this article.

      Check for updates

      Author Tags

      1. botnets
      2. command-and-control
      3. honeyfarm
      4. malware containment
      5. malware execution

      Qualifiers

      • Research-article

      Conference

      IMC '11
      IMC '11: Internet Measurement Conference
      November 2 - 4, 2011
      Berlin, Germany

      Acceptance Rates

      Overall Acceptance Rate 277 of 1,083 submissions, 26%

      Upcoming Conference

      IMC '24
      ACM Internet Measurement Conference
      November 4 - 6, 2024
      Madrid , AA , Spain

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)19
      • Downloads (Last 6 weeks)1

      Other Metrics

      Citations

      Cited By

      View all
      • (2019)Improving IoT Botnet Investigation Using an Adaptive Network LayerSensors10.3390/s1903072719:3(727)Online publication date: 11-Feb-2019
      • (2019)A Secure Contained Testbed for Analyzing IoT BotnetsTestbeds and Research Infrastructures for the Development of Networks and Communities10.1007/978-3-030-12971-2_8(124-137)Online publication date: 2-Feb-2019
      • (2018)HoneyCirculatorInternational Journal of Information Security10.1007/s10207-017-0361-517:2(135-151)Online publication date: 1-Apr-2018
      • (2018)A Honeyfarm Data Control Mechanism and Forensic StudyCommunications and Networking10.1007/978-3-319-78139-6_37(362-372)Online publication date: 27-Mar-2018
      • (2017)Handling Anti-Virtual Machine Techniques in Malicious SoftwareACM Transactions on Privacy and Security10.1145/313929221:1(1-31)Online publication date: 6-Dec-2017
      • (2017)To Catch a Ratter: Monitoring the Behavior of Amateur DarkComet RAT Operators in the Wild2017 IEEE Symposium on Security and Privacy (SP)10.1109/SP.2017.48(770-787)Online publication date: May-2017
      • (2017)Using Botnet structure to construct the communication system of a real-time monitoring platform: Botnet structure for real-time monitoring platform2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)10.1109/FSKD.2017.8393235(2860-2865)Online publication date: Jul-2017
      • (2016)HogMapProceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization10.1145/2876019.2876023(7-12)Online publication date: 11-Mar-2016
      • (2016)MARS: An SDN-based malware analysis solution2016 IEEE Symposium on Computers and Communication (ISCC)10.1109/ISCC.2016.7543792(525-530)Online publication date: Jun-2016
      • (2016)Membrane: A Posteriori Detection of Malicious Code Loading by Memory Paging AnalysisComputer Security – ESORICS 201610.1007/978-3-319-45744-4_10(199-216)Online publication date: 15-Sep-2016
      • Show More Cited By

      View Options

      Get Access

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Media

      Figures

      Other

      Tables

      Share

      Share

      Share this Publication link

      Share on social media