DatAFLow : Toward a Data-Flow-Guided Fuzzer

Autor:	Adrian Herrera, Mathias Payer, Antony L. Hosking
Rok vydání:	2023
Předmět:	Software
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
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0f81b5faf5753913402e68685dcf6740 https://doi.org/10.1145/3587159 Zobrazit plný text záznamu