Chloe Fortuna (STR), JT Paasch (STR), Sam Lasser (Draper), Philip Zucker (Draper), Chris Casinghino (Jane Street), Cody Roux (AWS)

Modifying a binary program without access to the original source code is an error-prone task. In many cases, the modified binary must be tested or otherwise validated to ensure that the change had its intended effect and no others—a process that can be labor-intensive. This paper presents CBAT, an automated tool for verifying the correctness of binary transformations. CBAT’s approach to this task is based on a differential program analysis that checks a relative correctness property over the original and modified versions of a function. CBAT applies this analysis to the binary domain by implementing it as an extension to the BAP binary analysis toolkit. We highlight several features of CBAT that contribute to the tool’s efficiency and to the interpretability of its output. We evaluate CBAT’s performance by using the tool to verify modifications to three collections of functions taken from real-world binaries.

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LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

Chengkun Wei (Zhejiang University), Wenlong Meng (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University), Min Chen (CISPA Helmholtz Center for Information Security), Minghu Zhao (Zhejiang University), Wenjing Fang (Ant Group), Lei Wang (Ant Group), Zihui Zhang (Zhejiang University), Wenzhi Chen (Zhejiang University)

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“I used to live in Florida”: Exploring the Impact...

Imani N. S. Munyaka (University of California, San Diego), Daniel A Delgado, Juan Gilbert, Jaime Ruiz, Patrick Traynor (University of Florida)

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Aligning Confidential Computing with Cloud-native ML Platforms

Angelo Ruocco, Chris Porter, Claudio Carvalho, Daniele Buono, Derren Dunn, Hubertus Franke, James Bottomley, Marcio Silva, Mengmei Ye, Niteesh Dubey, Tobin Feldman-Fitzthum (IBM Research)

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