# longld/peda

PEDA - Python Exploit Development Assistance for GDB

Repository: https://github.com/longld/peda
Canonical: https://ross.abutalabs.com/products/peda
Language: Python
License: NOASSERTION
License Family: other
Last push: 2024-07-29T08:32:28+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 5143, "days_push": 765, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6147, forks 826 (observed 2026-08-28T04:09:36.579445+00:00)

## What it is
PEDA is a Python plugin for GDB that enhances the debugger's display and adds exploit development commands. It provides colorized disassembly, register/memory context, and tools for ROP gadget discovery, pattern generation, and security checks.

## Use cases
- develop binary exploits with gdb
- find rop gadgets in a binary
- generate cyclic patterns for buffer overflow offset discovery
- check binary security mitigations like nx and canary
- search process memory for patterns during debugging
- generate shellcode and exploit skeletons

## When to choose
- you are doing CTF challenges or binary exploitation work on Linux
- you want a lightweight gdb enhancement without switching debuggers
- you need ROP gadget search and pattern tools inside gdb

## When to avoid
- you need a modern actively developed exploit debugger like pwndbg or GEF
- you debug on non-Linux platforms
- you need a graphical debugger

## Facets
- artifact type: plugin
- maturity: maintenance
- function: security, reverse-engineering, developer-tools, cli
- domain: security, penetration-testing, developer-tools
- platform: cli, python
- tags: gdb, exploit-development, binary-exploitation, debugging, rop, pwn, command-line, linux

## Member repositories
- longld/peda (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:36.579445+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:47:32.716736+00:00, confidence not recorded.
  - readme: https://github.com/longld/peda (fetched 2026-08-28T04:09:36.579445+00:00, sha 314f8041398e)
  - registry_pypi: https://pypi.org/pypi/peda/json (fetched 2026-08-29T08:44:19.816268+00:00, sha d511d4806481)
- Data as of 2026-08-30T08:39:29.467469+00:00.