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Artifact for IEEE Security and Privacy 2022 paper: "SoK: Demystifying Binary Lifters Through the Lens of Downstream Applications"

SoK: Demystifying Binary Lifters Through the Lens of Downstream Applications (IEEE S&P 2022 artifacts)

Artifact for IEEE Security and Privacy 2022 paper: "SoK: Demystifying Binary Lifters Through the Lens of Downstream Applications".

Paper: link

Zenodo link: https://zenodo.org/record/5163174#.YQy6dEC-vb0

(Note: This work started in the summer of 2020. Many of the tools evaluated have been under continuous development and refinement over the past two years (e.g., rev.ng, and Instrew). The results in the paper may not fully reflect the state of each tool at this time. We recommend that users try to use the latest version of tools when choosing the right one and don't rely solely on the results of this paper.)

Lifters:

Downstream Application

Please refer to lifter-summary for the patching & augmenting we made on these four lifters and more details about the downstream applications we leveraged.

Datasets

Pointer Analysis

Discriminability Analysis

  • We use the POJ-104 dataset used in NCC, the lifted LLVM IR can be download from here

Decompilation

Address Sanitizer

We apply the Address Sanitizer on the IR lifted by McSema and RetDec and compare the results with the binary-only tool, RetroWrite.

Code and Data Structure

├── ASan_test          (Data used to compare with binary-only tool: RetroWrite)
├── Binary_Diffing     (Data used to compare with binary-only tool: DeepBinDiff)
├── aarch64            (Data of three downstream applications on ARM64 platform)
├── alias_test         (Data used for Pointer Analysis: SVF test suite)
├── correctness_check  (Scripts used to check correctness of lifted IR)
├── decompile_data     (Data used for Decompilation: SPEC INT 2006)
├── ncc_data           (Data used for Discriminability Analysis: POJ-104)
└── lifter-sm.pdf      (Supplementary Materials)

Main Results

For more detailed evaluation results, please see our paper.