DatAFLow : Toward a Data-Flow-Guided Fuzzer
Autor: | Adrian Herrera, Mathias Payer, Antony L. Hosking |
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Rok vydání: | 2023 |
Předmět: | |
Zdroj: | ACM Transactions on Software Engineering and Methodology. |
ISSN: | 1557-7392 1049-331X |
Popis: | This Replicating Computational Report (RCR) describes (a) our datAFLow fuzzer, and (b) how to replicate the results in “ datAFLow : Toward a Data-Flow-Guided Fuzzer”. Our primary artifact is the datAFLow fuzzer. Unlike traditional coverage-guided greybox fuzzers—which use control-flow coverage to drive program exploration— datAFLow uses data-flow coverage to drive exploration. This is achieved through a set of LLVM-based analyses and transformations. In addition to datAFLow , we also provide a set of tools, scripts, and patches for (a) statically analyzing data flows in a target program, (b) compiling a target program with the datAFLow instrumentation, (c) evaluating datAFLow on the Magma benchmark suite, and (d) evaluating datAFLow on the DDFuzz dataset. datAFLow is available at https://github.com/HexHive/datAFLow. |
Databáze: | OpenAIRE |
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