# wtsxDev/reverse-engineering

List of awesome reverse engineering resources

Repository: https://github.com/wtsxDev/reverse-engineering
Canonical: https://ross.abutalabs.com/products/wtsxdev-reverse-engineering
License Family: other
Last push: 2023-07-29T08:23:45+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3517, "days_push": 1131, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10392, forks 1194 (observed 2026-08-28T04:10:41.848357+00:00)

## What it is
A curated awesome-list of reverse engineering resources including books, courses, tools, and practice materials. It covers topics like disassemblers, binary analysis, debugging, malware analysis, and Android reversing.

## Use cases
- find books on reverse engineering
- learn malware analysis
- discover disassembler tools
- find reverse engineering courses for beginners
- locate binary analysis resources
- find practice challenges for learning reversing
- learn Android reverse engineering

## When to choose
- you want a curated starting point for learning reverse engineering
- you need a directory of tools, books, and courses on binary analysis and malware analysis

## When to avoid
- you need an actual reverse engineering tool rather than a list of resources
- you need actively maintained or up-to-date content, as the list is no longer frequently updated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: reverse-engineering, security, developer-tools
- domain: reverse-engineering, security, tutorials, awesome-lists
- platform: cross-platform
- tags: awesome-list, curated-resources, malware-analysis, disassembly, binary-analysis, debugging

## Member repositories
- wtsxDev/reverse-engineering (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:41.848357+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 2026-08-29T17:19:05.261929+00:00, confidence not recorded.
  - readme: https://github.com/wtsxDev/reverse-engineering (fetched 2026-08-28T04:10:41.848357+00:00, sha 5919374ce9d5)
- Data as of 2026-08-30T08:39:29.467469+00:00.