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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/angr/angr/llms.txt

Use this file to discover all available pages before exploring further.

angr is a suite of Python libraries that let you load a binary and perform sophisticated analysis on it. Built by the Computer Security Lab at UC Santa Barbara, SEFCOM at Arizona State University, and the open source community, angr brings academic-grade binary analysis techniques to security researchers and CTF players.

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What can you do with angr?

angr provides a comprehensive toolkit for binary analysis:

Symbolic Execution

Explore multiple execution paths simultaneously to discover program behavior and find inputs that trigger specific conditions.

Control-Flow Analysis

Generate control-flow graphs (CFGs) to understand program structure and execution flow across multiple architectures.

Decompilation

Convert binary code back into readable source code with angr’s built-in decompiler.

Multi-Architecture Support

Analyze binaries for x86, ARM, MIPS, PowerPC, and many other architectures with a unified API.

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Key capabilities

angr offers a rich set of analysis techniques:
  • Disassembly and lifting - Convert machine code to intermediate representation (IR)
  • Program instrumentation - Hook functions and modify program behavior during execution
  • Symbolic execution - Reason about program behavior with symbolic values
  • Data-dependency analysis - Track how data flows through a program
  • Value-set analysis (VSA) - Determine possible values of variables
  • Decompilation - Generate high-level pseudocode from binaries

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Getting started

The most common angr operation is loading a binary: 
import angr

p = angr.Project('/bin/bash')
From there, you can use tab-autocomplete in enhanced REPLs like IPython to explore the available methods and their documentation.

Quickstart

Get up and running with angr in minutes

Installation

Detailed installation instructions and troubleshooting

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Who uses angr?

angr is used by:
  • Security researchers for vulnerability discovery and exploit development
  • CTF teams (including Shellphish) for solving reverse engineering challenges
  • Academics for binary analysis research
  • Developers for understanding and testing compiled code

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Learn more

angr Documentation

Visit the official angr documentation for comprehensive guides and API references
angr requires Python 3.10 or higher. The framework has fully transitioned to Python 3 to provide the best performance and latest features.