Panagiotis Papadopoulos (FORTH-ICS, Greece), Panagiotis Ilia (FORTH-ICS), Michalis Polychronakis (Stony Brook University, USA), Evangelos P. Markatos (FORTH-ICS, Greece), Sotiris Ioannidis (FORTH-ICS, Greece), Giorgos Vasiliadis (FORTH-ICS, Greece)

The proliferation of web applications has essentially transformed modern browsers into small but powerful operating systems. Upon visiting a website, user devices run implicitly trusted script code, the execution of which is confined within the browser to prevent any interference with the user’s system. Recent JavaScript APIs, however, provide advanced capabilities that not only enable feature-rich web applications, but also allow attackers to perform malicious operations despite the confined nature of JavaScript code execution.
In this paper, we demonstrate the powerful capabilities that modern browser APIs provide to attackers by presenting MarioNet: a framework that allows a remote malicious entity to control a visitor’s browser and abuse its resources for unwanted computation or harmful operations, such as cryptocurrency mining, password-cracking, and DDoS. MarioNet relies solely on already available HTML5 APIs, without requiring the installation of any additional software. In contrast to previous browser- based botnets, the persistence and stealthiness characteristics of MarioNet allow the malicious computations to continue in the background of the browser even after the user closes the window or tab of the initially visited malicious website. We present the design, implementation, and evaluation of our prototype system, which is compatible with all major browsers, and discuss potential defense strategies to counter the threat of such persistent in- browser attacks. Our main goal is to raise awareness about this new class of attacks, and inform the design of future browser APIs so that they provide a more secure client-side environment for web applications.

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NIC: Detecting Adversarial Samples with Neural Network Invariant Checking

Shiqing Ma (Purdue University), Yingqi Liu (Purdue University), Guanhong Tao (Purdue University), Wen-Chuan Lee (Purdue University), Xiangyu Zhang (Purdue University)

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REDQUEEN: Fuzzing with Input-to-State Correspondence

Cornelius Aschermann (Ruhr-Universität Bochum), Sergej Schumilo (Ruhr-Universität Bochum), Tim Blazytko (Ruhr-Universität Bochum), Robert Gawlik (Ruhr-Universität Bochum), Thorsten Holz (Ruhr-Universität Bochum)

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ExSpectre: Hiding Malware in Speculative Execution

Jack Wampler (University of Colorado Boulder), Ian Martiny (University of Colorado Boulder), Eric Wustrow (University of Colorado Boulder)

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PeriScope: An Effective Probing and Fuzzing Framework for the...

Dokyung Song (University of California, Irvine), Felicitas Hetzelt (Technical University of Berlin), Dipanjan Das (University of California, Santa Barbara), Chad Spensky (University of California, Santa Barbara), Yeoul Na (University of California, Irvine), Stijn Volckaert (University of California, Irvine and KU Leuven), Giovanni Vigna (University of California, Santa Barbara), Christopher Kruegel (University of California, Santa Barbara),…

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