Samuel Mergendahl (MIT Lincoln Laboratory), Nathan Burow (MIT Lincoln Laboratory), Hamed Okhravi (MIT Lincoln Laboratory)

Memory corruption attacks against unsafe programming languages like C/C++ have been a major threat to computer systems for multiple decades. Various sanitizers and runtime exploit mitigation techniques have been shown to only provide partial protection at best. Recently developed ‘safe’ programming languages such as Rust and Go hold the promise to change this paradigm by preventing memory corruption bugs using a strong type system and proper compile-time and runtime checks. Gradual deployment of these languages has been touted as a way of improving the security of existing applications before entire applications can be developed in safe languages. This is notable in popular applications such as Firefox and Tor. In this paper, we systematically analyze the security of multi-language applications. We show that because language safety checks in safe languages and exploit mitigation techniques applied to unsafe languages (e.g., Control-Flow Integrity) break different stages of an exploit to prevent control hijacking attacks, an attacker can carefully maneuver between the languages to mount a successful attack. In essence, we illustrate that the incompatible set of assumptions made in various languages enables attacks that are not possible in each language alone. We study different variants of these attacks and analyze Firefox to illustrate the feasibility and extent of this problem. Our findings show that gradual deployment of safe programming languages, if not done with extreme care, can indeed be detrimental to security.

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Building Embedded Systems Like It’s 1996

Ruotong Yu (Stevens Institute of Technology, University of Utah), Francesca Del Nin (University of Padua), Yuchen Zhang (Stevens Institute of Technology), Shan Huang (Stevens Institute of Technology), Pallavi Kaliyar (Norwegian University of Science and Technology), Sarah Zakto (Cyber Independent Testing Lab), Mauro Conti (University of Padua, Delft University of Technology), Georgios Portokalidis (Stevens Institute of…

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ProvTalk: Towards Interpretable Multi-level Provenance Analysis in Networking Functions...

Azadeh Tabiban (CIISE, Concordia University, Montreal, QC, Canada), Heyang Zhao (CIISE, Concordia University, Montreal, QC, Canada), Yosr Jarraya (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Makan Pourzandi (Ericsson Security Research, Ericsson Canada, Montreal, QC, Canada), Mengyuan Zhang (Department of Computing, The Hong Kong Polytechnic University, China), Lingyu Wang (CIISE, Concordia University, Montreal, QC, Canada)

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Fighting Fake News in Encrypted Messaging with the Fuzzy...

Linsheng Liu (George Washington University), Daniel S. Roche (United States Naval Academy), Austin Theriault (George Washington University), Arkady Yerukhimovich (George Washington University)

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MIRROR: Model Inversion for Deep LearningNetwork with High Fidelity

Shengwei An (Purdue University), Guanhong Tao (Purdue University), Qiuling Xu (Purdue University), Yingqi Liu (Purdue University), Guangyu Shen (Purdue University); Yuan Yao (Nanjing University), Jingwei Xu (Nanjing University), Xiangyu Zhang (Purdue University)

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