TOFU: Target-Oriented FUzzer

04/29/2020

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by   Zi Wang, et al.

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Program fuzzing—providing randomly constructed inputs to a computer program—has proved to be a powerful way to uncover bugs, find security vulnerabilities, and generate test inputs that increase code coverage. In many applications, however, one is interested in a target-oriented approach-one wants to find an input that causes the program to reach a specific target point in the program. We have created TOFU (for Target-Oriented FUzzer) to address the directed fuzzing problem. TOFU's search is biased according to a distance metric that scores each input according to how close the input's execution trace gets to the target locations. TOFU is also input-structure aware (i.e., the search makes use of a specification of a superset of the program's allowed inputs). Our experiments on xmllint show that TOFU is 28 reaching 45 exploitation of knowledge of the input structure contribute significantly to TOFU's performance.