# dronesploit/dronesploit

Drone pentesting framework console

Repository: https://github.com/dronesploit/dronesploit
Canonical: https://ross.abutalabs.com/products/dronesploit
Language: Python
License: GPL-3.0
License Family: copyleft
Topics: python, cli, console, drone, hacking, pentest-tools, security-tools, tinyscript, drones, fpv-drones, drones-security
Last push: 2024-11-23T13:13:00+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": 2551, "days_push": 648, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2161, forks 329 (observed 2026-08-28T04:06:19.472599+00:00)

## What it is
DroneSploit is a Metasploit-style console framework for pentesting commercial drones, built on sploitkit. It gathers drone-focused hacking techniques and exploits behind a familiar module-based CLI interface.

## Use cases
- pentest a commercial drone
- hack FPV drones
- find drone security vulnerabilities
- run drone exploits from a Metasploit-like console
- assess drone wireless security with aircrack-ng

## When to choose
- you need a dedicated drone pentesting framework with a Metasploit-like workflow
- you want a curated collection of drone hacking modules in one console
- you are doing security research on commercial or FPV drones

## When to avoid
- you need general network or web application pentesting
- you require a GUI tool
- you cannot install external dependencies like aircrack-ng

## Facets
- artifact type: cli-tool
- maturity: active
- function: penetration-testing, security, cli, developer-tools
- domain: security, penetration-testing, hardware
- platform: python, cli
- tags: drone-hacking, metasploit-like, sploitkit, fpv-drones, wireless-security, command-line, linux, macos

## Member repositories
- dronesploit/dronesploit (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:19.472599+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 2026-08-30T02:50:15.287233+00:00, confidence not recorded.
  - readme: https://github.com/dronesploit/dronesploit (fetched 2026-08-28T04:06:19.472599+00:00, sha 73c314559391)
- Data as of 2026-08-30T08:39:29.467469+00:00.