Zhen Huang (Pennsylvania State University), Gang Tan (Pennsylvania State University)

The existence of pre-patch windows allows adversaries to exploit vulnerabilities before they are patched. Prior work has proposed to harden programs with security workarounds to enable users to mitigate vulnerabilities before a patch is available. However, it requires access to the source code of the programs. This paper introduces RVM, an approach to automatically hardening binary code with security workarounds. RVM statically analyzes binary code of programs to identify error-handling code in the programs, in order to synthesize security workarounds. We designed and implemented a prototype of RVM for Windows and Linux binaries. We evaluate the coverage and performance of RVM on binaries of popular Windows and Linux applications containing real-world vulnerabilities.

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Binary Code Patching: An Ancient Art Refined for the...

Dr. Barton P. Miller (Vilas Distinguished Achievement Professor at The University of Wisconsin-Madison)

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PyPANDA: Taming the PANDAmonium of Whole System Dynamic Analysis

Luke Craig, Tim Leek (MIT Lincoln Laboratory), Andrew Fasano, Tiemoko Ballo (MIT Lincoln Laboratory, Northeastern University), Brendan Dolan-Gavitt (New York University), William Robertson (Northeastern University)

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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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Effects of Precise and Imprecise Value-Set Analysis (VSA) Information...

Laura Matzen, Michelle A Leger, Geoffrey Reedy (Sandia National Laboratories)

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Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

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

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

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)