|Home > Theses > Optimizing Re-Evaluation of Malware Distribution Networks|
12 October 2011
Abstract: The retrieval and analysis of malicious content is an essential task for security researchers. Security labs use automated HTTP clients known as client honeypots to visit hundreds of thousands of suspicious URLs daily. The dynamic nature of malware distribution networks necessitate periodic re-evaluation of a subset of the confirmed malicious sites, which introduces two problems: 1) the number of URLs requiring re-evaluation exhaust available resources, and 2) repeated evaluation exposes the system to adversarial blacklisting, which affects the accuracy of the content collected. To address these problems, I propose optimizations to the re-evaluation logic that reduce the number of re-evaluations while maintaining a constant sample discovery rate during URLs re-evaluation. I study these problems in two adversarial scenarios: 1) monitoring malware repositories where no provenance is available, and 2) monitoring Fake Anti-Virus (AV) distribution networks. I perform a study of the adversary by repeatedly downloading content from the distribution networks. This re- veals trends in the update patterns and lifetimes of the distribution sites and malicious executa- bles. Using these observations I propose optimizations to reduce the amount of re-evaluations necessary to maintain a high malicious sample discovery rate. In the first scenario the proposed techniques, when evaluated versus a fixed interval scheduler, are shown to reduce the number of re-evaluations by 80-93% (assuming a re-evaluation interval of 1 hour to 1 day) with a corresponding impact on sample discovery rate of only 2-7% percent. In the second scenario, optimizations proposed are shown to reduce fetch volume by orders of magnitude and, more importantly, reduce the likelihood of blacklisting. During direct evaluation of malware repositories I observe multiple instances of blacklisting, but on the whole, less than 1% of the repositories studied show evidence of blacklisting. Fake AV dis- tribution networks actively blacklist IPs; I encountered repeated occurrences of IP blacklisting while monitoring Fake AV distribution networks.
Keyword(s): malware distribution networks ; adversarial blacklisting ; honeyclient ; scareware ; fake antivirus ; neveragain
Published in: Kyle Zeeuwen, "Optimizing Re-Evaluation of Malware Distribution Networks", MASc thesis, Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, Canada, October 2011.:
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