Hongwei Wu (Purdue University), Jianliang Wu (Simon Fraser University), Ruoyu Wu (Purdue University), Ayushi Sharma (Purdue University), Aravind Machiry (Purdue University), Antonio Bianchi (Purdue University)

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 VeriBin, 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, VeriBin checks functional equivalence between the original and patched binaries.
In particular, VeriBin 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, VeriBin'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 VeriBin 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 VeriBin can be used to detect the recently discovered XZ Utils backdoor.

View More Papers

NodeMedic-FINE: Automatic Detection and Exploit Synthesis for Node.js Vulnerabilities

Darion Cassel (Carnegie Mellon University), Nuno Sabino (IST & CMU), Min-Chien Hsu (Carnegie Mellon University), Ruben Martins (Carnegie Mellon University), Limin Jia (Carnegie Mellon University)

Read More

Hidden and Lost Control: on Security Design Risks in...

Haoqiang Wang, Yiwei Fang (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Indiana University Bloomington), Yichen Liu (Indiana University Bloomington), Ze Jin (Institute of Information Engineering, Chinese Academy of Sciences; School of Cyber Security, University of Chinese Academy of Sciences; Indiana University Bloomington), Emma Delph…

Read More

Vision: Towards True User-Centric Design for Digital Identity Wallets

Yorick Last (Paderborn University), Patricia Arias Cabarcos (Paderborn University)

Read More

Misdirection of Trust: Demystifying the Abuse of Dedicated URL...

Zhibo Zhang (Fudan University), Lei Zhang (Fudan University), Zhangyue Zhang (Fudan University), Geng Hong (Fudan University), Yuan Zhang (Fudan University), Min Yang (Fudan University)

Read More