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Copyright (c) 2015, The Regents of the University of California
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
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Metadata-Version: 2.1
Name: angr
Version: 9.2.35
Summary: A multi-architecture binary analysis toolkit, with the ability to perform dynamic symbolic execution and various static analyses on binaries
Home-page: https://github.com/angr/angr
License: BSD-2-Clause
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
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angr
====
[![Latest Release](https://img.shields.io/pypi/v/angr.svg)](https://pypi.python.org/pypi/angr/)
[![PyPI Statistics](https://img.shields.io/pypi/dm/angr.svg)](https://pypistats.org/packages/angr)
[![Build Status](https://github.com/angr/angr/actions/workflows/.github/workflows/ci.yml/badge.svg)](https://github.com/angr/angr/actions/workflows/.github/workflows/ci.yml/badge.svg)
[![License](https://img.shields.io/github/license/angr/angr.svg)](https://github.com/angr/angr/blob/master/LICENSE)
[![Gitbook](https://img.shields.io/badge/docs-gitbook-green.svg)](https://docs.angr.io)
[![API Docs](https://img.shields.io/badge/docs-api-green.svg)](https://angr.io/api-doc)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit)](https://github.com/pre-commit/pre-commit)
angr is a platform-agnostic binary analysis framework.
It is brought to you by [the Computer Security Lab at UC Santa Barbara](https://seclab.cs.ucsb.edu), [SEFCOM at Arizona State University](https://sefcom.asu.edu), their associated CTF team, [Shellphish](https://shellphish.net), the open source community, and **[@rhelmot](https://github.com/rhelmot)**.
# What?
angr is a suite of Python 3 libraries that let you load a binary and do a lot of cool things to it:
- Disassembly and intermediate-representation lifting
- Program instrumentation
- Symbolic execution
- Control-flow analysis
- Data-dependency analysis
- Value-set analysis (VSA)
- Decompilation
The most common angr operation is loading a binary: `p = angr.Project('/bin/bash')` If you do this in an enhanced REPL like IPython, you can use tab-autocomplete to browse the [top-level-accessible methods](https://docs.angr.io/docs/toplevel) and their docstrings.
The short version of "how to install angr" is `mkvirtualenv --python=$(which python3) angr && python -m pip install angr`.
# Example
angr does a lot of binary analysis stuff.
To get you started, here's a simple example of using symbolic execution to get a flag in a CTF challenge.
```python
import angr
project = angr.Project("angr-doc/examples/defcamp_r100/r100", auto_load_libs=False)
@project.hook(0x400844)
def print_flag(state):
print("FLAG SHOULD BE:", state.posix.dumps(0))
project.terminate_execution()
project.execute()
```
# Quick Start
- [Install Instructions](https://docs.angr.io/introductory-errata/install)
- Documentation as [HTML](https://docs.angr.io/) and as a [Github repository](https://github.com/angr/angr-doc)
- Dive right in: [top-level-accessible methods](https://docs.angr.io/core-concepts/toplevel)
- [Examples using angr to solve CTF challenges](https://docs.angr.io/examples).
- [API Reference](https://angr.io/api-doc/)
- [awesome-angr repo](https://github.com/degrigis/awesome-angr)

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