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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maTLS: How to Make TLS middlebox-aware?

Hyunwoo Lee (Seoul National University), Zach Smith (University of Luxembourg), Junghwan Lim (Seoul National University), Gyeongjae Choi (Seoul National University), Selin Chun (Seoul National University), Taejoong Chung (Rochester Institute of Technology), Ted "Taekyoung" Kwon (Seoul National University)

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Daniele Antonioli (Singapore University of Technology and Design (SUTD)), Nils Ole Tippenhauer (CISPA), Kasper Rasmussen (University of Oxford)

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Suphannee Sivakorn (Columbia University), Kangkook Jee (NEC Labs America), Yixin Sun (Princeton University), Lauri Korts-Pärn (Cyber Defense Institute), Zhichun Li (NEC Labs America), Cristian Lumezanu (NEC Labs America), Zhenyu Wu (NEC Labs America), Lu-An Tang (NEC Labs America), Ding Li (NEC Labs America)

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JavaScript Template Attacks: Automatically Inferring Host Information for Targeted...

Michael Schwarz (Graz University of Technology), Florian Lackner (Graz University of Technology), Daniel Gruss (Graz University of Technology)

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Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

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Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)