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FuzzFactory: Domain-Specific Fuzzing with Waypoints (Replication Package)

Authors: Padhye, Rohan; Lemieux, Caroline;

FuzzFactory: Domain-Specific Fuzzing with Waypoints (Replication Package)

Abstract

This artifact accompanies the paper "FuzzFactory: Domain-Specific Fuzzing with Waypoints", submitted to OOPSLA 2019. Paper abstract: Coverage-guided fuzz testing has gained prominence as a highly effective method of finding security vulnerabilities such as buffer overflows in programs that parse binary data. Recently, researchers have introduced various specializations to the coverage-guided fuzzing algorithm for different domain-specific testing goals, such as finding performance bottlenecks, generating valid inputs, handling magic-byte comparisons, etc. Each such solution can require weeks of development effort and produces a distinct variant of a fuzzing tool. We observe that many of these domain-specific solutions follow a common solution pattern. In this paper, we present FuzzFactory, a framework for rapid prototyping of domain-specific fuzzing applications. FuzzFactory allows users to specify the collection of dynamic domain-specific feedback during test execution. FuzzFactory uses a domain-specific fuzzing algorithm that incorporates such custom feedback to selectively save intermediate inputs, called waypoints, to augment coverage-guided fuzzing. We use FuzzFactory to implement six domain-specific fuzzing applications: three re-implementations of prior work and three novel solutions, and evaluate their effectiveness on benchmarks from Google's fuzzer test suite. We also show how domain-specific feedback can be composed to produce composite applications, which perform better than the sum of their parts. For example, we combine domain-specific feedback about strict equality comparisons and dynamic memory allocations, to enable the automatic generation of ZIP bombs and PNG bombs. We also discover a previously unknown memory leak in libarchive.

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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