Yubo Du (University of Pittsburgh), Youtao Zhang (University of Pittsburgh), Jun Yang (University of Pittsburgh)

Low-level programming languages like C and C++ offer dynamic memory management capabilities but are vulnerable to Use-After-Free (UAF) vulnerabilities due to improper deallocation handling. These vulnerabilities, arising from accessing memory through dangling pointers, pose significant risks. While various defense mechanisms have been proposed, existing solutions often face challenges such as high performance overhead, excessive memory usage, or inadequate security guarantees, limiting their practicality. Pointer Nullification (PN) has gained attention as a promising UAF mitigation technique by tracking pointers and nullifying them upon buffer deallocation. However, existing PN techniques incur inefficiencies due to precisely associating each pointer with its target buffer, leading to expensive metadata lookups. Moreover, they overlook spatial locality in pointer storage, resulting in a larger number of registrations than necessary. This paper introduces Fast Pointer Nullification (FPN), a new PN-based defense that organizes metadata at the region level to eliminate costly search operations and uses block-based registration to efficiently capture pointer locality. Experiments on SPEC CPU benchmarks and real-world applications demonstrate that FPN provides strong security guarantees while significantly reducing performance and memory overhead compared to prior PN techniques.

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Scalable Off-Chain Auctions

Mohsen Minaei (Visa Research), Ranjit Kumaresan (Visa Research), Andrew Beams (Visa Research), Pedro Moreno-Sanchez (IMDEA Software Institute, MPI-SP), Yibin Yang (Georgia Institute of Technology), Srinivasan Raghuraman (Visa Research and MIT), Panagiotis Chatzigiannis (Visa Research), Mahdi Zamani (Visa Research), Duc V. Le (Visa Research)

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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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Not What It Used To Be: Generational Analysis of...

Janos Szurdi (Palo Alto Networks), Reethika Ramesh (Palo Alto Networks), Ram Sundara Raman (University of California Santa Cruz), Daiping Liu (Palo Alto Networks)

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