Affiliation:
1. University of Wisconsin-Madison, USA
2. University of Wisconsin-Madison, USA / GrammaTech, USA
Abstract
Machine-code slicing is an important primitive for building binary analysis and rewriting tools, such as taint trackers, fault localizers, and partial evaluators. However, it is not easy to create a machine-code slicer that exhibits a high level of precision. Moreover, the problem of creating such a tool is compounded by the fact that a small amount of local imprecision can be amplified via cascade effects.
Most instructions in instruction sets such as Intel's IA-32 and ARM are multi-assignments: they have several inputs and several outputs (registers, flags, and memory locations). This aspect of the instruction set introduces a granularity issue during slicing: there are often instructions at which we would like the slice to include only a subset of the instruction's semantics, whereas the slice is forced to include the entire instruction. Consequently, the slice computed by state-of-the-art tools is very imprecise, often including essentially the entire program.
This paper presents an algorithm to slice machine code more accurately. To counter the granularity issue, our algorithm performs slicing at the microcode level, instead of the instruction level, and obtains a more precise microcode slice. To reconstitute a machine-code program from a microcode slice, our algorithm uses machine-code synthesis. Our experiments on IA-32 binaries of FreeBSD utilities show that, in comparison to slices computed by a state-of-the-art tool, our algorithm reduces the size of backward slices by 33%, and forward slices by 70%.
Funder
Defense Advanced Research Projects Agency
Wisconsin Alumni Research Foundation
Air Force Research Laboratory
Rajiv and Ritu Batra
UW-Madison Office of the Vice Chancellor for Research and Graduate Education
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Graphics and Computer-Aided Design,Software
Reference35 articles.
1. Design and implementation of a fine-grained software inspection tool
2. ARM instruction-set manual. http:// infocenter.arm.com/help/topic/com. arm.doc.qrc0001m/QRC0001_UAL.pdf. ARM instruction-set manual. http:// infocenter.arm.com/help/topic/com. arm.doc.qrc0001m/QRC0001_UAL.pdf.
3. Specialization Slicing
4. WYSINWYX
5. CodeSurfer/x86—A Platform for Analyzing x86 Executables
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