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Rozzle: De-Cloaking Internet Malware

Clemens Kolbitsch, livshits, and zorn

Abstract

JavaScript-based malware attacks have increased in recent years and currently represent a signicant threat to the use of desktop computers, smartphones, and tablets. While static and runtime methods for malware detection have been proposed in the literature, both on the client side, for just-in-time in-browser detection, as well as online, crawler-based malware discovery, these approaches encounter the same fundamental limitation. Web-based malware tends to be environment-specific, targeting a particular browser, often attacking specific versions of installed plugins. This targeting occurs because the malware exploits vulnerabilities in specific plugins and fails otherwise. As a result, a fundamental limitation for detecting a piece of malware is that malware is triggered infrequently, only showing itself when the right environment is present. We observe that, using fingerprinting techniques that capture and exploit unique properties of browser configurations, almost all existing malware can be made virtually impossible for malware scanners to detect.

This paper proposes Rozzle, a JavaScript multi- execution virtual machine, as a way to explore multi- ple execution paths within a single execution so that environment-specific malware will reveal itself. Using large-scale experiments, we show that Rozzle increases the detection rate for online runtime detection by almost seven times. In addition, Rozzle triples the effectiveness of online runtime detection. We show that Rozzle incurs virtually no runtime overhead and allows us to replace multiple VMs running different browser configurations with a single Rozzle-enabled browser, reducing the hardware requirements, network bandwidth, and power consumption.

Details

Publication typeInproceedings
Published inProceedings of the Oakland Symposium on Security and Privacy
PublisherIEEE

Previous versions

Scott Kaplan, Benjamin Livshits, Ben Zorn, Christian Siefert, and Charlie Cursinger. "NOFUS: Automatically Detecting" + String.fromCharCode(32) + "ObFuSCateD ".toLowerCase() + "JavaScript Code", 5 May 2011.

Paruj Ratanaworabhan, Benjamin Livshits, and Benjamin G. Zorn. Nozzle: A Defense Against Heap-spraying Code Injection Attacks, November 2008.

Paruj Ratanaworabhan, Benjamin Livshits, and Benjamin Zorn. Nozzle: A Defense Against Heap-spraying Code Injection Attacks, USENIX, 2009.

Charles Curtsinger, Benjamin Livshits, Benjamin Zorn, and Christian Seifert. Zozzle: Low-overhead Mostly Static JavaScript Malware Detection, 27 November 2010.

Charles Curtsinger, Benjamin Livshits, Benjamin Zorn, and Christian Seifert. Zozzle: Low-overhead Mostly Static JavaScript Malware Detection, 27 November 2010.

Charles Curtsinger, Benjamin Livshits, Benjamin Zorn, and Christian Seifert. Zozzle: Low-overhead Mostly Static JavaScript Malware Detection., USENIX, 8 August 2011.

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