Caleb Helbling, Graham Leach-Krouse, Sam Lasser, Greg Sullivan (Draper)

This paper introduces cozy, a tool for analyzing and visualizing differences between two versions of a software binary. The primary use case for cozy is validating “micropatches”: small binary or assembly-level patches inserted into existing compiled binaries. To perform this task, cozy leverages the Python-based angr symbolic execution framework. Our tool analyzes the output of symbolic execution to find end states for the pre- and post-patched binaries that are compatible (reachable from the same input). The tool then compares compatible states for observable differences in registers, memory, and side effects. To aid in usability, cozy comes with a web-based visual interface for viewing comparison results. This interface provides a rich set of operations for pruning, filtering, and exploring different types of program data.

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Andrew Fasano, Zachary Estrada, Luke Craig, Ben Levy, Jordan McLeod, Jacques Becker, Elysia Witham, Cole DiLorenzo, Caden Kline, Ali Bobi (MIT Lincoln Laboratory), Dinko Dermendzhiev (Georgia Institute of Technology), Tim Leek (MIT Lincoln Laboratory), William Robertson (Northeastern University)

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AI-Assisted RF Fingerprinting for Identification of User Devices in...

Aishwarya Jawne (Center for Connected Autonomy & AI, Florida Atlantic University), Georgios Sklivanitis (Center for Connected Autonomy & AI, Florida Atlantic University), Dimitris A. Pados (Center for Connected Autonomy & AI, Florida Atlantic University), Elizabeth Serena Bentley (Air Force Research Laboratory)

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Roee Idan, Roy Peled, Aviel Ben Siman Tov, Eli Markus, Boris Zadov, Ofir Chodeda, Yohai Fadida (Ben Gurion University of the Negev), Oliver Holschke, Jan Plachy (T-Labs (Research & Innovation)), Yuval Elovici, Asaf Shabtai (Ben Gurion University of the Negev)

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Short Paper: Declarative Demand-Driven Reverse Engineering

Yihao Sun, Jeffrey Ching, Kristopher Micinski (Department of Electical Engineering and Computer Science, Syracuse University)

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