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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Corban Villa (New York University Abu Dhabi), Constantine Doumanidis (New York University Abu Dhabi), Hithem Lamri (New York University Abu Dhabi), Prashant Hari Narayan Rajput (InterSystems), Michail Maniatakos (New York University Abu Dhabi)

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Investigating Graph Embedding Neural Networks with Unsupervised Features Extraction...

Luca Massarelli (Sapienza University of Rome), Giuseppe A. Di Luna (CINI - National Laboratory of Cybersecurity), Fabio Petroni (Independent Researcher), Leonardo Querzoni (Sapienza University of Rome), Roberto Baldoni (Italian Presidency of Ministry Council)

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Ring of Gyges: Accountable Anonymous Broadcast via Secret-Shared Shuffle

Wentao Dong (City University of Hong Kong), Peipei Jiang (Wuhan University; City University of Hong Kong), Huayi Duan (ETH Zurich), Cong Wang (City University of Hong Kong), Lingchen Zhao (Wuhan University), Qian Wang (Wuhan University)

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Translating C To Rust: Lessons from a User Study

Ruishi Li (National University of Singapore), Bo Wang (National University of Singapore), Tianyu Li (National University of Singapore), Prateek Saxena (National University of Singapore), Ashish Kundu (Cisco Research)

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