skip to main content
10.1145/2976749.2978330acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
research-article
Free Access
Best Student Paper

PhishEye: Live Monitoring of Sandboxed Phishing Kits

Published:24 October 2016Publication History

ABSTRACT

Phishing is a form of online identity theft that deceives unaware users into disclosing their confidential information. While significant effort has been devoted to the mitigation of phishing attacks, much less is known about the entire life-cycle of these attacks in the wild, which constitutes, however, a main step toward devising comprehensive anti-phishing techniques. In this paper, we present a novel approach to sandbox live phishing kits that completely protects the privacy of victims. By using this technique, we perform a comprehensive real-world assessment of phishing attacks, their mechanisms, and the behavior of the criminals, their victims, and the security community involved in the process -- based on data collected over a period of five months.

Our infrastructure allowed us to draw the first comprehensive picture of a phishing attack, from the time in which the attacker installs and tests the phishing pages on a compromised host, until the last interaction with real victims and with security researchers. Our study presents accurate measurements of the duration and effectiveness of this popular threat, and discusses many new and interesting aspects we observed by monitoring hundreds of phishing campaigns.

References

  1. Kaspersky: Top 7 Cyberthreats to Watch Out for in 2015--2016. http://usa.kaspersky.com/internet-security-center/threats/top-7-cyberthreats.Google ScholarGoogle Scholar
  2. G. Aaron and R. Manning. APWG global phishing report 2014. http://apwg.org/download/document/245/APWG_Global_Phishing_Report_2H_2014.pdf.Google ScholarGoogle Scholar
  3. G. Aaron and R. Manning. APWG phishing activity trends report 2015. https://docs.apwg.org/reports/apwg_trends_report_q1-q3_2015.pdf.Google ScholarGoogle Scholar
  4. E. Bursztein, B. Benko, D. Margolis, T. Pietraszek, A. Archer, A. Aquino, A. Pitsillidis, and S. Savage. Handcrafted fraud and extortion: Manual account hijacking in the wild. In Internet Measurement Conference (IMC), 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. D. Canali and D. Balzarotti. Behind the scenes of online attacks: an analysis of exploitation behaviors on the web. In Annual Network and Distributed System Security Symposium (NDSS), 2013.Google ScholarGoogle Scholar
  6. N. Chou, R. Ledesma, Y. Teraguchi, and J. C. Mitchell. Client-side defense against web-based identity theft. In Annual Network and Distributed System Security Symposium (NDSS), 2004.Google ScholarGoogle Scholar
  7. R. Clayton, T. Moore, and N. Christin. Concentrating correctly on cybercrime concentration. In Workshop on the Economics of Information Security, 2015.Google ScholarGoogle Scholar
  8. M. Cova, C. Kruegel, and G. Vigna. There is no free phish: An analysis of "free" and live phishing kits. In Workshop on Offensive Technologies (WOOT), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. R. Dhamija and J. D. Tygar. The battle against phishing: Dynamic security skins. In Symposium on Usable Privacy and Security, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. R. Dhamija, J. D. Tygar, and M. Hearst. Why phishing works. In SIGCHI conference on Human Factors in computing systems, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. S. Egelman, L. F. Cranor, and J. Hong. You've been warned: an empirical study of the effectiveness of web browser phishing warnings. In SIGCHI Conference on Human Factors in Computing Systems, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. I. Fette, N. Sadeh, and A. Tomasic. Learning to detect phishing emails. In World Wide Web (WWW) Conference, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. S. Garera, N. Provos, M. Chew, and A. D. Rubin. A framework for detection and measurement of phishing attacks. In Workshop on Recurring malcode, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Gupta and P. Kumaraguru. Emerging phishing trends and effectiveness of the anti-phishing landing page. In Electronic Crime Research (eCrime), 2014.Google ScholarGoogle ScholarCross RefCross Ref
  15. X. Han, N. Kheir, and D. Balzarotti. The role of cloud services in malicious software: Trends and insights. In Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 2015. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Hong. The state of phishing attacks. Communications of the ACM, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. T. N. Jagatic, N. A. Johnson, M. Jakobsson, and F. Menczer. Social phishing. Communications of the ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. M. Jakobsson and S. Myers. Phishing and countermeasures: understanding the increasing problem of electronic identity theft. 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. M. Jakobsson and J. Ratkiewicz. Designing ethical phishing experiments: a study of (rot13) ronl query features. In World Wide Web (WWW) Conference, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Y. Joshi, S. Saklikar, D. Das, and S. Saha. Phishguard: a browser plug-in for protection from phishing. In Internet Multimedia Services Architecture and Applications (IMSAA), 2008.Google ScholarGoogle ScholarCross RefCross Ref
  21. P. Kumaraguru, L. F. Cranor, and L. Mather. Anti-phishing landing page: Turning a 404 into a teachable moment for end users. In Conference on Email and Anti-Spam (CEAS), 2009.Google ScholarGoogle Scholar
  22. P. Kumaraguru, Y. Rhee, S. Sheng, S. Hasan, A. Acquisti, L. F. Cranor, and J. Hong. Getting users to pay attention to anti-phishing education: evaluation of retention and transfer. In Anti-phishing working groups annual eCrime researchers summit, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. P. Kumaraguru, S. Sheng, A. Acquisti, L. F. Cranor, and J. Hong. Teaching johnny not to fall for phish. ACM Transactions on Internet Technology (TOIT), 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. A. Le, A. Markopoulou, and M. Faloutsos. Phishdef: Url names say it all. In Conference on Computer Communications (INFOCOM), 2011.Google ScholarGoogle ScholarCross RefCross Ref
  25. Z. Li, S. Alrwais, Y. Xie, F. Yu, and X. Wang. Finding the linchpins of the dark web: a study on topologically dedicated hosts on malicious web infrastructures. In Security and Privacy (S&P), 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. C. Ludl, S. McAllister, E. Kirda, and C. Kruegel. On the effectiveness of techniques to detect phishing sites. In Detection of Intrusions and Malware & Vulnerability Assessment (DIMVA), 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. D. K. McGrath and M. Gupta. Behind phishing: An examination of phisher modi operandi. In Workshop on Large-Scale Exploits and Emergent Threats (LEET), 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. E. Medvet, E. Kirda, and C. Kruegel. Visual-similarity-based phishing detection. In Security and Privacy in Communication Netowrks Conference, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. T. Moore and R. Clayton. Examining the impact of website take-down on phishing. In Anti-phishing working groups annual eCrime researchers summit, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. T. Moore and R. Clayton. Evil searching: Compromise and recompromise of internet hosts for phishing. In Financial Cryptography and Data Security. 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. T. Moore and R. Clayton. Discovering phishing dropboxes using email metadata. In eCrime Researchers Summit (eCrime), 2012.Google ScholarGoogle Scholar
  32. T. Moore and R. Clayton. Ethical dilemmas in take-down research. In Financial Cryptography and Data Security. 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. T. Moore, R. Clayton, and H. Stern. Temporal correlations between spam and phishing websites. In Workshop on Large-Scale Exploits and Emergent Threats (LEET), 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. K. Onarlioglu, U. O. Yilmaz, D. Balzarotti, and E. Kirda. Insights into user behavior in dealing with internet attacks. In Annual Network and Distributed System Security Symposium (NDSS), 2012.Google ScholarGoogle Scholar
  35. Y. Pan and X. Ding. Anomaly based web phishing page detection. In Annual Computer Security Applications Conference (ACSAC), 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. S. Sheng, M. Holbrook, P. Kumaraguru, L. F. Cranor, and J. Downs. Who falls for phish?: a demographic analysis of phishing susceptibility and effectiveness of interventions. In SIGCHI Conference on Human Factors in Computing Systems, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. S. Sheng, B. Wardman, G. Warner, L. F. Cranor, J. Hong, and C. Zhang. An empirical analysis of phishing blacklists. In Conference on Email and Anti-Spam (CEAS), 2009.Google ScholarGoogle Scholar
  38. L. Spitzner. The honeynet project: Trapping the hackers. Security and Privacy (S&P), 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Trusteer. Measuring the Effectiveness of In-the-Wild Phishing Attacks. https://web.archive.org/web/20120324061250/http://www.trusteer.com/sites/default/files/Phishing-Statistics-Dec-2009-FIN.pdf.Google ScholarGoogle Scholar
  40. D. Watson, T. Holz, and S. Mueller. Know your enemy: Phishing. https://www.honeynet.org/papers/phishing, 2005.Google ScholarGoogle Scholar
  41. C. Whittaker, B. Ryner, and M. Nazif. Large-scale automatic classification of phishing pages. In Annual Network and Distributed System Security Symposium (NDSS), 2010.Google ScholarGoogle Scholar
  42. M. Wu, R. C. Miller, and S. L. Garfinkel. Do security toolbars actually prevent phishing attacks? In SIGCHI conference on Human Factors in computing systems, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. G. Xiang and J. I. Hong. A hybrid phish detection approach by identity discovery and keywords retrieval. In World Wide Web (WWW) conference, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Y. Zhang, S. Egelman, L. Cranor, and J. Hong. Phinding phish: Evaluating anti-phishing tools. In Annual Network and Distributed System Security Symposium (NDSS), 2007.Google ScholarGoogle Scholar
  45. Y. Zhang, J. I. Hong, and L. F. Cranor. Cantina: a content-based approach to detecting phishing web sites. In World Wide Web (WWW) Conference, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. PhishEye: Live Monitoring of Sandboxed Phishing Kits

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          CCS '16: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security
          October 2016
          1924 pages
          ISBN:9781450341394
          DOI:10.1145/2976749

          Copyright © 2016 ACM

          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 the author(s) 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].

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 24 October 2016

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          CCS '16 Paper Acceptance Rate137of831submissions,16%Overall Acceptance Rate1,261of6,999submissions,18%

          Upcoming Conference

          CCS '24
          ACM SIGSAC Conference on Computer and Communications Security
          October 14 - 18, 2024
          Salt Lake City , UT , USA

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader