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

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

2016 | Yan Shoshitaishvili, Ruoyu Wang, Christopher Salls, Nick Stephens, Mario Polino, Andrew Dutcher, John Grosen, Siji Feng, Christophe Hauser, Christopher Kruegel, Giovanni Vigna
The paper presents a binary analysis framework called *angr* that implements several advanced techniques for identifying and exploiting vulnerabilities in binary code. The framework aims to address the challenges of binary analysis, such as the lack of high-level, semantically rich information about data structures and control constructs, and the need for efficient and scalable methods to analyze complex programs. *angr* is designed to be flexible, cross-architecture, and cross-platform, supporting various analysis paradigms and providing a user-friendly API. The authors evaluate *angr* using a dataset created by DARPA for the Cyber Grand Challenge, a competition aimed at evaluating automated binary analysis systems. The evaluation includes reproducing existing approaches and comparing their effectiveness, demonstrating the strengths and weaknesses of different techniques. The paper also discusses the design and implementation of key components of *angr*, such as the intermediate representation (IR), binary loading, and program state representation, highlighting the modular and extensible nature of the framework.The paper presents a binary analysis framework called *angr* that implements several advanced techniques for identifying and exploiting vulnerabilities in binary code. The framework aims to address the challenges of binary analysis, such as the lack of high-level, semantically rich information about data structures and control constructs, and the need for efficient and scalable methods to analyze complex programs. *angr* is designed to be flexible, cross-architecture, and cross-platform, supporting various analysis paradigms and providing a user-friendly API. The authors evaluate *angr* using a dataset created by DARPA for the Cyber Grand Challenge, a competition aimed at evaluating automated binary analysis systems. The evaluation includes reproducing existing approaches and comparing their effectiveness, demonstrating the strengths and weaknesses of different techniques. The paper also discusses the design and implementation of key components of *angr*, such as the intermediate representation (IR), binary loading, and program state representation, highlighting the modular and extensible nature of the framework.
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[slides and audio] SOK%3A (State of) The Art of War%3A Offensive Techniques in Binary Analysis