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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PANDORA: Jailbreak GPTs by Retrieval Augmented Generation Poisoning

Gelei Deng, Yi Liu (Nanyang Technological University), Yuekang Li (The University of New South Wales), Wang Kailong(Huazhong University of Science and Technology), Tianwei Zhang, Yang Liu (Nanyang Technological 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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Stacking up the LLM Risks: Applied Machine Learning Security

Dr. Gary McGraw, Berryville Institute of Machine Learning

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