Title
Improving the Effectiveness of Grey-box Fuzzing By Extracting Program Information
Abstract
Fuzzing has been widely adopted as an effective techniques to detect vulnerabilities in softwares. However, existing fuzzers suffer from the problems of generating excessive test inputs that either cannot pass input validation or are ineffective in exploring unvisited regions in the program under test (PUT). To tackle these problems, we propose a greybox fuzzer called MuFuzzer based on AFL, which incorporates two heuristics that optimize seed selection and automatically extract input formatting information from the PUT to increase the chance of generating valid test inputs, respectively. In particular, the first heuristic collects the branch coverage and execution information during a fuzz session, and utilizes such information to guide fuzzing tools in selecting seeds that are fast to execute, small in size, and more importantly, more likely to explore new behaviors of the PUT for subsequent fuzzing activities. The second heuristic automatically identifies string comparison operations that the PUT uses for input validation, and establishes a dictionary with string constants from these operations to help fuzzers generate test inputs that have higher chances to pass input validation. We have evaluated the performance of MuFuzzer, in terms of code coverage and bug detection, using a set of realistic programs and the LAVA-M test bench. Experiment results demonstrate that MuFuzzer is able to achieve higher code coverage and better or comparative bug detection performance than state-of-the-art fuzzers.
Year
DOI
Venue
2020
10.1109/TrustCom50675.2020.00066
2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)
Keywords
DocType
ISSN
automated testing,fuzzing,program analysis
Conference
2324-898X
ISBN
Citations 
PageRank 
978-1-6654-0393-1
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Yu Fu14612.20
Siming Tong200.34
XiangYu Guo325.71
Liang Cheng4114.31
Yang Zhang5673.73
Deng-Guo Feng61991190.95