Program Environment Fuzzing
Ruijie Meng, Gregory J. Duck, Abhik Roychoudhury
摘要
Computer programs are not executed in isolation, but rather interact with the execution environment which drives the program behaviors. Software validation methods thus need to capture the effect of possibly complex environmental interactions. Program environments may come from files, databases, configurations, network sockets, human-user interactions, and more. Conventional approaches for environment capture in symbolic execution and model checking employ environment modeling, which involves manual effort. In this paper, we take a different approach based on an extension of greybox fuzzing. Given a program, we first record all observed environmental interactions at the kernel/usermode boundary in the form of system calls. Next, we replay the program under the original recorded interactions, but this time with selective mutations applied, in order to get the effect of different program environments-all without environment modeling. Via repeated (feedback-driven) mutations over a fuzzing campaign, we can search for program environments that induce crashing behaviors. Our Efuzz tool found 33 previously unknown bugs in well-known real-world protocol implementations and GUI applications. Many of these are security vulnerabilities and 16 CVEs were assigned. CCS CONCEPTS • Security and privacy → Software security engineering.
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引用它的顶会 Paper3
- Large Language Model Powered Symbolic ExecutionYihe Li, Ruijie Meng, Gregory J. DuckOOPSLA 2025 · 被引用 12 次
- NCFuzz: Configuration-Guided Network Service FuzzingXuesong Bai, Hengkai Ye, Shenghan Zheng, Fenglu Zhang 等ISSTA 2026
- GUIFuzz++: Unleashing Grey-box Fuzzing on Desktop Graphical User Interfacing ApplicationsDillon Otto, Tanner Rowlett, Stefan NagyASE 2025
它引用的顶会 Paper14
- Coverage-based Greybox Fuzzing as Markov ChainMarcel Böhme, Van-Thuan Pham, Abhik RoychoudhuryCCS 2016 · 被引用 1,026 次
- Evaluating Fuzz TestingGeorge Klees, Andrew Ruef, Benji Cooper, Shiyi Wei 等CCS 2018 · 被引用 753 次
- Ijon: Exploring Deep State Spaces via FuzzingCornelius Aschermann, Sergej Schumilo, Ali Abbasi, Thorsten HolzS&P 2020 · 被引用 146 次
- Snipuzz: Black-box Fuzzing of IoT Firmware via Message Snippet InferenceXiaotao Feng, Ruoxi Sun, Xiaogang Zhu, Minhui Xue 等CCS 2021 · 被引用 146 次
- On the Reliability of Coverage-Based Fuzzer BenchmarkingMarcel Böhme, László Szekeres, Jonathan MetzmanICSE 2022 · 被引用 91 次
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