LspFuzz: Hunting Bugs in Language Servers
Hengcheng Zhu, Songqiang Chen, Valerio Terragni, Lili Wei, Yepang Liu, Jiarong Wu, Shing-Chi Cheung
摘要
The Language Server Protocol (LSP) has revolutionized the integration of code intelligence in modern software development. There are approximately 300 LSP server implementations for various languages and 50 editors offering LSP integration. However, the reliability of LSP servers is a growing concern, as crashes can disable all code intelligence features and significantly impact productivity, while vulnerabilities can put developers at risk even when editing untrusted source code. Despite the widespread adoption of LSP, no existing techniques specifically target LSP server testing. To bridge this gap, we present LspFuzz, a grey-box hybrid fuzzer for systematic LSP server testing. Our key insight is that effective LSP server testing requires holistic mutation of source code and editor operations, as bugs often manifest from their combinations. To satisfy the sophisticated constraints of LSP and effectively explore the input space, we employ a two-stage mutation pipeline: syntax-aware mutations to source code, followed by context-aware dispatching of editor operations. We evaluated LspFuzz on four widely used LSP servers. LspFuzz demonstrated superior performance compared to baseline fuzzers, and uncovered previously unknown bugs in real-world LSP servers. Of the 51 bugs we reported, 42 have been confirmed, 26 have been fixed by developers, and two have been assigned CVE numbers. Our work advances the quality assurance of LSP servers, providing both a practical tool and foundational insights for future research in this domain.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper23
- Evaluating Fuzz TestingGeorge Klees, Andrew Ruef, Benji Cooper, Shiyi Wei 等CCS 2018 · 被引用 753 次
- Skyfire: Data-Driven Seed Generation for FuzzingJunjie Wang, Bihuan Chen, Lei Wei, Yang LiuS&P 2017 · 被引用 382 次
- IoTFuzzer: Discovering Memory Corruptions in IoT Through App-based FuzzingJiongyi Chen, Wenrui Diao, Qingchuan Zhao, Chaoshun Zuo 等NDSS 2018 · 被引用 311 次
- NAUTILUS: Fishing for Deep Bugs with GrammarsCornelius Aschermann, Tommaso Frassetto, Thorsten Holz, Patrick Jauernig 等NDSS 2019 · 被引用 291 次
- Fuzz4All: Universal Fuzzing with Large Language ModelsChunqiu Steven Xia, Matteo Paltenghi, Jia Le Tian, Michael Pradel 等ICSE 2024 · 被引用 155 次
相关 Paper
- One Engine to Fuzz 'em All: Generic Language Processor Testing with Semantic ValidationYongheng Chen, Rui Zhong, Hong Hu, Hangfan Zhang 等S&P 2021 · 被引用 70 次
- Fuzzing JavaScript Interpreters with Coverage-Guided Reinforcement Learning for LLM-Based MutationJueon Eom, Seyeon Jeong, Taekyoung KwonISSTA 2024 · 被引用 26 次
- SemFuzz: A Semantics-Aware Fuzzing Framework for Network Protocol ImplementationsYanbang Sun, Quan Luo, Yuelin Wang, Qian Chen 等WWW 2026
- GrayC: Greybox Fuzzing of Compilers and Analysers for CKarine Even-Mendoza, Arindam Sharma, Alastair F. Donaldson, Cristian CadarISSTA 2023 · 被引用 52 次
- WITFuzz: Validity-Preserving Greybox Fuzzing for WebAssembly Interface Type Binding GeneratorsHanqin Guan, Ningyu He, Shangtong Cao, Yifeng Cai 等ISSTA 2026
