Bokai Zhang, Monika Santra, Syed Rafiul Hussain, Gang Tan (Pennsylvania State University)

Sound indirect-call resolution for stripped binaries is critical for security applications such as CFI enforcement, debloating, and large-scale vulnerability discovery, yet it remains challenging in the absence of symbol and type information. A recent work, Block-Based Points-to Analysis (BPA) addresses this problem with a scalable block memory model, but its implementation is tightly coupled to 32-bit x86 through an ISA-specific disassembly pipeline.

To overcome this limitation, we present BPA-X, an architecture-agnostic block-based points-to analysis framework for stripped binaries across multiple ISAs. BPA-X preserves the core soundness assumptions of BPA’s block memory model while replacing x86-specific components with an architecture-agnostic VEX IR via binary analysis platform angr. It generalizes local and global memory-block partitioning using VEX semantics instead of x86-specific patterns, lifts VEX IR into SSA form, and performs fixpoint computation on interprocedural value tracking and reachability analysis.

Our evaluation on SPEC CPU 2006 and real-world server binaries shows that BPA-X improves memory-block partitioning, reduces AICT on many x86 programs compared to BPA, and extends the analysis to x64 without degrading much precision. BPA-X also reduces memory consumption by 25% and improves runtime on large benchmarks.

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Tillson Galloway (Georgia Institute of Technology), Omar Alrawi (Georgia Institute of Technology), Allen Chang (Georgia Institute of Technology), Athanasios Avgetidis (Georgia Institute of Technology), Manos Antonakakis (Georgia Institute of Technology), Fabian Monrose (Georgia Institute of Technology)

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DuoLungo: Usability Study of Duo 2FA

Renascence Tarafder Prapty (University of California Irvine), Gene Tsudik (University of California Irvine)

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Zion Leonahenahe Basque (Arizona State University), Samuele Doria (University of Padua), Ananta Soneji (Arizona State University), Wil Gibbs (Arizona State University), Adam Doupe (Arizona State University), Yan Shoshitaishvili (Arizona State University), Eleonora Losiouk (University of Padua), Ruoyu “Fish” Wang (Arizona State University), Simone Aonzo (EURECOM)

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