How to be angry

This is a collection of documentation for angr. By reading this, you'll become an angr pro and will be able to fold binaries to your whim.

We've tried to make using angr as pain-free as possible - our goal is to create a user-friendly binary analysis suite, allowing a user to simply start up iPython and easily perform intensive binary analyses with a couple of commands. That being said, binary analysis is complex, which makes angr complex. This documentation is an attempt to help out with that, providing narritive explanation and exploration of angr and its design.

Get Started

Installation instructions can be found here.

To dive right into angr's capabilities, start with the top level methods, or read over the overview.

A searchable HTML version of this documentation is hosted at docs.angr.io, and an HTML API reference can be found at angr.io/api-doc.

Citing angr

If you use angr in an academic work, please cite the papers for which it was developed:

@article{shoshitaishvili2016state,
  title={SoK: (State of) The Art of War: Offensive Techniques in Binary Analysis},
  author={Shoshitaishvili, Yan and Wang, Ruoyu and Salls, Christopher and Stephens, Nick and Polino, Mario and Dutcher, Andrew and Grosen, John and Feng, Siji and Hauser, Christophe and Kruegel, Christopher and Vigna, Giovanni},
  booktitle={IEEE Symposium on Security and Privacy},
  year={2016}
}

@article{stephens2016driller,
  title={Driller: Augmenting Fuzzing Through Selective Symbolic Execution},
  author={Stephens, Nick and Grosen, John and Salls, Christopher and Dutcher, Andrew and Wang, Ruoyu and Corbetta, Jacopo and Shoshitaishvili, Yan and Kruegel, Christopher and Vigna, Giovanni},
  booktitle={NDSS},
  year={2016}
}

@article{shoshitaishvili2015firmalice,
  title={Firmalice - Automatic Detection of Authentication Bypass Vulnerabilities in Binary Firmware},
  author={Shoshitaishvili, Yan and Wang, Ruoyu and Hauser, Christophe and Kruegel, Christopher and Vigna, Giovanni},
  booktitle={NDSS},
  year={2015}
}

Support

To get help with angr, you can ask via:

• the mailing list: angr@lists.cs.ucsb.edu
• the IRC channel: #angr on freenode
• opening an issue on the appropriate github repository

Going further:

You can read this paper, explaining some of the internals, algorithms, and used techniques to get a better understanding on what's going on under the hood.