# LaurieWired/Malimite

iOS and macOS Decompiler

Repository: https://github.com/LaurieWired/Malimite
Canonical: https://ross.abutalabs.com/products/malimite
Language: Java
License: Apache-2.0
License Family: permissive
Last push: 2025-08-26T05:59:43+00:00

## Health v2 (maintenance only)
Score: 38/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 38, release rhythm 20, longevity 71
- inputs: {"age_days": 1000, "days_push": 372, "days_rel": 372, "gap_med": 132.0, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3174, forks 130 (observed 2026-08-28T04:07:47.584936+00:00)

## What it is
Malimite is a Java-based decompiler for iOS and macOS binaries, built on Ghidra, that analyzes IPA files and Application Bundles with direct support for Swift, Objective-C, and Apple resources. It reconstructs Swift classes, decodes iOS resources, and offers built-in LLM-assisted method translation.

## Use cases
- decompile an iOS IPA file to readable source
- analyze macOS application bundles for reverse engineering
- reconstruct Swift class structures from compiled binaries
- decode iOS app resources automatically
- use an LLM to translate decompiled methods
- audit third-party iOS apps for security research

## When to choose
- you need to reverse engineer iOS or macOS binaries with Swift and Objective-C support
- you want Ghidra-based decompilation tailored to Apple platforms
- you want automated resource decoding and Swift class reconstruction

## When to avoid
- you need to decompile Android APKs or Windows binaries
- you need a lightweight command-line-only decompiler
- you are not working with Apple platform binaries

## Facets
- artifact type: application
- maturity: active
- function: reverse-engineering, security, developer-tools
- domain: reverse-engineering, security, apple-ecosystem
- platform: windows, jvm
- tags: decompiler, ghidra, swift, objective-c, ipa, ios, macos, llm-assisted, java, linux, desktop

## Member repositories
- LaurieWired/Malimite (main) score 38

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:47.584936+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 2026-08-29T18:45:26.239254+00:00, confidence not recorded.
  - readme: https://github.com/LaurieWired/Malimite (fetched 2026-08-28T04:07:47.584936+00:00, sha cf4912b0bb20)
- Data as of 2026-08-30T08:39:29.467469+00:00.