Lune

NDSS2025顶会

VeriBin: Adaptive Verification of Patches at the Binary Level

Hongwei Wu, Jianliang Wu, Ruoyu Wu, Ayushi Sharma, Aravind Machiry, Antonio Bianchi

出版方
2025年份
2顶会引用

摘要

—Vendors are often provided with updated versions of a piece of software, fixing known security issues. However, the inability to have any guarantee that the provided patched software does not break the functionality of its original version often hinders patch deployment. This issue is particularly severe when the patched software is only provided in its compiled binary form. In this case, manual analysis of the patch’s source code is impossible, and existing automated patch analysis techniques, which rely on source code, are not applicable. Even when the source code is accessible, the necessity of binary-level patch verification is still crucial, as highlighted by the recent XZ Utils backdoor. To tackle this issue, we propose V ERI B IN , a system able to compare a binary with its patched version and determine whether the patch is “Safe to Apply”, meaning it does not introduce any modification that could potentially break the functionality of the original binary. To achieve this goal, V ERI B IN checks functional equivalence between the original and patched binaries. In particular, V ERI B IN first uses symbolic execution to systematically identify patch-introduced modifications. Then, it checks if the detected patch-introduced modifications respect specific properties that guarantee they will not break the original binary’s functionality. To work without source code, V ERI B IN ’s design solves several challenges related to the absence of semantic information (removed during the compilation process) about the analyzed code and the complexity of symbolically executing large functions precisely. Our evaluation of V ERI B IN on a dataset of 86 samples shows that it achieves an accuracy of 93.0% with no false positives, requiring only minimal analyst input. Additionally, we showcase how V ERI B IN can be used to detect the recently discovered XZ Utils backdoor.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper2

问问它们各自怎么用它

它引用的顶会 Paper22

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖