Proceedings of the USENIX Security Symposium (2016)
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In this work, we explore the ecosystem of commercial pay-per-install (PPI) and the role it plays in the proliferation of unwanted software. Commercial PPI enables companies to bundle their applications with more popular software in return for a fee, effectively commoditizing access to user devices. We develop an analysis pipeline to track the business relationships underpinning four of the largest commercial PPI networks and classify the software families bundled. In turn, we measure their impact on end users and enumerate the distribution techniques involved. We find that unwanted ad injectors, browser settings hijackers, and cleanup utilities dominate the software families buying installs. Developers of these families pay $0.10--$1.50 per install---upfront costs that they recuperate by monetizing users without their consent or by charging exorbitant subscription fees. Based on Google Safe Browsing telemetry, we estimate that PPI networks drive over 60 million download attempts every week---nearly three times that of malware. While anti-virus and browsers have rolled out defenses to protect users from unwanted software, we find evidence that PPI networks actively interfere with or evade detection. Our results illustrate the deceptive practices of some commercial PPI operators that persist today.View details
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In this work we expose wide-spread efforts by criminals to abuse the Chrome Web Store as a platform for distributing malicious extensions. A central component of our study is the design and implementation of WebEval, the first system that broadly identifies malicious extensions with a concrete, measurable detection rate of 96.5%. Over the last three years we detected 9,523 malicious extensions: nearly 10% of every extension submitted to the store. Despite a short window of operation---we removed 50% of malware within 25 minutes of creation---a handful of under 100 extensions escaped immediate detection and infected over 50 million Chrome users. Our results highlight that the extension abuse ecosystem is drastically different from malicious binaries: miscreants profit from web traffic and user tracking rather than email spam or banking theft.View details
Large-Scale Exploits and Emergent Threats, USENIX (2010)
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We present a study of Fake Anti-Virus attacks on the web. Fake AV software masquerades as a legitimate security product with the goal of deceiving victims into paying registration fees to seemingly remove malware from their computers. Our analysis of 240 million web pages collected by Google's malware detection infrastructure over a 13 month period discovered over 11,000 domains involved in Fake AV distribution. We show that the Fake AV threat is rising in prevalence, both absolutely, and relative to other forms of web-based malware. Fake AV currently accounts for 15% of all malware we detect on the web. Our investigation reveals several characteristics that distinguish Fake AVs from other forms of web-based malware and shows how these characteristics have changed over time. For instance, Fake AV attacks occur frequently via web sites likely to reach more users including spam web sites and on-line Ads. These attacks account for 60% of the malware discovered on domains that include trending keywords. As of this writing, Fake AV is responsible for 50% of all malware delivered via Ads, which represents a five-fold increase from just a year ago.View details
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As the web continues to play an ever increasing role in information exchange, so too is it becoming the prevailing platform for infecting vulnerable hosts. In this paper, we provide a detailed study of the pervasiveness of so-called drive-by downloads on the Internet. Driveby downloads are caused by URLs that attempt to exploit their visitors and cause malware to be installed and run automatically. Over a period of 10 months we processed billions of URLs, and our results shows that a non-trivial amount, of over 3 million malicious URLs, initiate driveby downloads. An even more troubling finding is that approximately 1.3% of the incoming search queries to Google’s search engine returned at least one URL labeled as malicious in the results page. We also explore several aspects of the drive-by downloads problem. Specifically, we study the relationship between the user browsing habits and exposure to malware, the techniques used to lure the user into the malware distribution networks, and the different properties of these networks.View details