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WebCop: Locating Neighborhoods of Malware on the Web

Jack W. Stokes, Reid Andersen, Christian Seifert, and Kumar Chellapilla


In this paper, we propose WebCop to identify malicious web pages and neighborhoods of malware on the internet. Using a bottom-up approach, telemetry data from commercial Anti-Malware (AM) clients running on millions of computers first identify malware distribution sites hosting malicious executables on the web. Next, traversing hyperlinks in a web graph constructed from a commercial search engine crawler in the reverse direction quickly discovers malware landing pages linking to the malware distribution sites. In addition, the malicious distribution sites and web graph are used to identify neighborhoods of malware, locate additional executables distributed on the internet which may be unknown malware and identify false positives in AM signatures. We compare the malicious URLs generated by the proposed method with those found by a commercial, drive-by download approach and show that lists are independent; both methods can be used to identify malware on the internet and help protect end users.


Publication typeInproceedings
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