Towards an Effective Method of ReDoS Detection for Non-backtracking Engines

Authors: 

Weihao Su, Hong Huang, and Rongchen Li, Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences; Haiming Chen, Key Laboratory of System Software (Chinese Academy of Sciences) and State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences; Tingjian Ge, Miner School of Computer & Information Sciences, University of Massachusetts, Lowell

Abstract: 

Regular expressions (regexes) are a fundamental concept across the fields of computer science. However, they can also induce the Regular expression Denial of Service (ReDoS) attacks, which are a class of denial of service attacks, caused by super-linear worst-case matching time. Due to the severity and prevalence of ReDoS attacks, the detection of ReDoS-vulnerable regexes in software is thus vital. Although various ReDoS detection approaches have been proposed, these methods have focused mainly on backtracking regex engines, leaving the problem of ReDoS vulnerability detection on non-backtracking regex engines largely open.

To address the above challenges, in this paper, we first systematically analyze the major causes that could contribute to ReDoS vulnerabilities on non-backtracking regex engines. We then propose a novel type of ReDoS attack strings that builds on the concept of simple strings. Next we propose EvilStrGen, a tool for generating attack strings for ReDoS-vulnerable regexes on non-backtracking engines. It is based on a novel incremental determinisation algorithm with heuristic strategies to lazily find the k-simple strings without explicit construction of finite automata. We evaluate EvilStrGen against six state-of-the-art approaches on a broad range of publicly available datasets containing 736,535 unique regexes. The results illustrate the significant efficacy of our tool. We also apply our tool to 85 intensively-tested projects, and have identified 34 unrevealed ReDoS vulnerabilities.

Open Access Media

USENIX is committed to Open Access to the research presented at our events. Papers and proceedings are freely available to everyone once the event begins. Any video, audio, and/or slides that are posted after the event are also free and open to everyone. Support USENIX and our commitment to Open Access.

BibTeX
@inproceedings {299724,
author = {Weihao Su and Hong Huang and Rongchen Li and Haiming Chen and Tingjian Ge},
title = {Towards an Effective Method of {ReDoS} Detection for Non-backtracking Engines},
booktitle = {33rd USENIX Security Symposium (USENIX Security 24)},
year = {2024},
isbn = {978-1-939133-44-1},
address = {Philadelphia, PA},
pages = {271--288},
url = {https://www.usenix.org/conference/usenixsecurity24/presentation/su-weihao},
publisher = {USENIX Association},
month = aug
}