radareorg/radare2

UNIX-like reverse engineering framework and command-line toolset

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Summary Information

Updated 11 minutes ago
Added to GitGenius on September 2nd, 2026
Created on July 3rd, 2012
Open Issues & Pull Requests: 823 (+0)
GitHub issues: Enabled
Number of forks: 3,314
Total Stargazers: 24,750 (+1)
Total Subscribers: 490 (+0)

Charts & Analytics

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Issue Activity (beta)

Open issues: 53
New in 7 days: 1
Closed in 7 days: 3
Avg open age: 1,192 days
Stale 30+ days: 48
Stale 90+ days: 41

Recent activity

Opened in 7 days: 1
Closed in 7 days: 3
Comments in 7 days: 2
Events in 7 days: 3

Top labels

  • good first issue (56)
  • RDebug (17)
  • enhancement (15)
  • high-priority (11)
  • refactor (10)
  • RBin (9)
  • RAnal (8)
  • DWARF (7)

Detailed Description

Radare2 is a reverse engineering framework and command-line toolset for analyzing binary files and malware.

The tool addresses the need to inspect, understand, and modify compiled binaries across multiple architectures and file formats. It provides a unified command-line interface for disassembly, debugging, binary patching, and forensic analysis. The framework supports numerous CPU architectures and executable formats, allowing security researchers and developers to work with diverse binary targets through a consistent set of commands and scripting capabilities.

Radare2 suits security professionals conducting malware analysis, vulnerability researchers examining compiled code, and developers performing low-level debugging and binary instrumentation. It works well for projects requiring deep binary inspection without dependency on proprietary tools. The tool is particularly valuable when working across multiple platforms and architectures, as its architecture-agnostic design handles varied binary types through a single interface. Teams should adopt it when they need scriptable, extensible binary analysis capabilities that integrate into automated workflows.

The project maintains steady development activity with regular commits addressing bug fixes, feature additions, and architecture support improvements. The codebase receives consistent updates to its core analysis engines and command implementations. Community contributions flow in regularly, with pull requests being reviewed and integrated. The project sustains active issue tracking and responds to reported problems. Development focuses on expanding architecture support and improving analysis accuracy rather than pursuing major architectural rewrites.