| Name | angr JSON |
| Version |
9.2.181
JSON |
| download |
| home_page | None |
| Summary | A multi-architecture binary analysis toolkit, with the ability to perform dynamic symbolic execution and various static analyses on binaries |
| upload_time | 2025-10-21 18:20:15 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | BSD-2-Clause |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# angr
[](https://pypi.python.org/pypi/angr/)
[](https://pypi.python.org/pypi/angr/)
[](https://pypistats.org/packages/angr)
[](https://github.com/angr/angr/blob/master/LICENSE)
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)**.
## Project Links
Homepage: https://angr.io
Project repository: https://github.com/angr/angr
Documentation: https://docs.angr.io
API Documentation: https://docs.angr.io/en/latest/api.html
## What is angr?
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/core-concepts/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 sources in the angr [Github repository](https://github.com/angr/angr/tree/master/docs)
- 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://docs.angr.io/en/latest/api.html)
- [awesome-angr repo](https://github.com/degrigis/awesome-angr)
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