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rev.ng: A Tale of Reverse Engineering, Dynamic Analysis and Translation of Binaries Using QEMU and LLVM

Published: 24 January 2018 Publication History

Abstract

This talk will provide an overview and an outlook to the future of rev.ng [1-3], a binary analysis tools based on QEMU and LLVM. Thanks to QEMU, and unlike many other binary analysis tools, rev.ng can handle a very large number of diverse architectures in a unified way. "Unified" means that all our analyses are designed to work in a architecture- and ABI-agnostic way: we can detect the arguments of a function no matter if it's SPARC or x86, and no matter the calling convention. As our internal representation we employ the LLVM IR, which means that we are not limited to static analysis, but we can also instrument the IR and recompile it, even across architectures. In fact, we have been able to successfully translate large pieces of software such as GCC and Perl compiled for an architecture (e.g., ARM) to another one (e.g., x86), preserving the original behavior.

References

[1]
Alessandro Di Federico. 2018. rev.ng. https://rev.ng/.
[2]
Alessandro Di Federico and Giovanni Agosta. 2016. A jump-target identification method for multi-architecture static binary translation. In 2016 International Conference on Compilers, Architectures and Synthesis for Embedded Systems, CASES 2016, Pittsburgh, Pennsylvania, USA, October 1-7, 2016. ACM, 17:1--17:10.
[3]
Alessandro Di Federico, Mathias Payer, and Giovanni Agosta. 2017. rev.ng: a unified binary analysis framework to recover CFGs and function boundaries. In Proceedings of the 26th International Conference on Compiler Construction, Austin, TX, USA, February 5-6, 2017, Peng Wu and Sebastian Hack (Eds.). ACM, 131--141.

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CS2 '18: Proceedings of the Fifth Workshop on Cryptography and Security in Computing Systems
January 2018
27 pages
ISBN:9781450363747
DOI:10.1145/3178291
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 24 January 2018

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CS2 '18 Paper Acceptance Rate 2 of 8 submissions, 25%;
Overall Acceptance Rate 27 of 91 submissions, 30%

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