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· 2016

SOK: (State of) The Art of War: Offensive Techniques in Binary Analysis

Yan Shoshitaishvili, Ruoyu Wang, Christopher Salls, Nick Stephens et al.

Short summary

A new unified framework for binary analysis integrates and compares existing offensive techniques, enabling researchers to compose them and develop novel approaches for vulnerability discovery.

AI-generated from the title and abstract; the full text is not read.

Key points

  • Presents a unified framework for implementing and comparing offensive binary analysis techniques.
  • Enables composition of existing techniques to develop novel vulnerability discovery approaches.
  • Framework evaluated using a DARPA dataset for vulnerability analysis effectiveness.
  • The framework has been open-sourced for the security community.

AI-generated from the title and abstract; the full text is not read.

Abstract

Finding and exploiting vulnerabilities in binary code is a challenging task. The lack of high-level, semantically rich information about data structures and control constructs makes the analysis of program properties harder to scale. However, the importance of binary analysis is on the rise. In many situations binary analysis is the only possible way to prove (or disprove) properties about the code that is actually executed. In this paper, we present a binary analysis framework that implements a number of analysis techniques that have been proposed in the past. We present a systematized implementation of these techniques, which allows other researchers to compose them and develop new approaches. In addition, the implementation of these techniques in a unifying framework allows for the direct comparison of these apporaches and the identification of their advantages and disadvantages. The evaluation included in this paper is performed using a recent dataset created by DARPA for evaluating the effectiveness of binary vulnerability analysis techniques. Our framework has been open-sourced and is available to the security community.

The authors' abstract, as published at the source., 2016 · DOI ↗

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Field: Signal Processing

Signal ProcessingComputer Science