A hybrid symbolic execution assisted fuzzing method
Li Zhang, Vrizlynn L. L. Thing
Abstract
Li Zhang, Vrizlynn L. L. Thing
Abstract
We present a new automated method for efficient detection of security vulnerabilities in binary programs. This method starts with a bounded symbolic execution of the target program so as to explore as many paths as possible. Constraints of the explored paths are collected and solved for inputs. The inputs will then be fed to the following interleaved coverage-based fuzzing and concolic execution. As the paths explored by the bounded symbolic execution may cover some unique paths that can be rarely reached by random testing featured fuzzing and locality featured concolic execution, the efficiency and effectiveness of the overall exploration can be greatly enhanced. In particular, the bounded symbolic execution can effectively prevent the fuzzing guided exploration from converging to the less interesting but easy-to-fuzz branches.
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We present a new automated method for efficient detection of security vulnerabilities in binary programs. This method starts with a bounded symbolic execution of the target program so as to explore as many paths as possible. Constraints of the explored paths are collected and solved for inputs. The inputs will then be fed to the following interleaved coverage-based fuzzing and concolic execution. As the paths explored by the bounded symbolic execution may cover some unique paths that can be rarely reached by random testing featured fuzzing and locality featured concolic execution, the efficiency and effectiveness of the overall exploration can be greatly enhanced. In particular, the bounded symbolic execution can effectively prevent the fuzzing guided exploration from converging to the less interesting but easy-to-fuzz branches.
Key concepts: Fuzz testing, Symbolic execution, Concolic testing, Computer science, Bounded function, Locality, Programming language, The Symbolic