# 0xZ0F/Z0FCourse_ReverseEngineering

Reverse engineering focusing on x64 Windows.

Repository: https://github.com/0xZ0F/Z0FCourse_ReverseEngineering
Canonical: https://ross.abutalabs.com/products/z0fcourse_reverseengineering
Language: C++
License: AGPL-3.0
License Family: copyleft
Last push: 2026-07-25T18:49:51+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 94, release rhythm 8, longevity 100
- inputs: {"age_days": 2648, "days_push": 39, "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 5906, forks 579 (observed 2026-08-28T04:09:32.112671+00:00)

## What it is
A free open-source course that teaches reverse engineering of x64 Windows binaries, taking learners from beginner to intermediate level. It covers binary basics, reversing DLLs and malware, and practical tooling like debuggers.

## Use cases
- learn reverse engineering from scratch
- understand x64 Windows assembly
- reverse engineer a DLL
- analyze malware binaries
- learn to use debuggers for binary analysis
- get into the reverse engineering field

## When to choose
- you are a beginner wanting a structured, free RE course
- you specifically target Windows x64 binaries
- you prefer markdown-based self-paced learning with community support

## When to avoid
- you need Linux or macOS-specific reversing techniques
- you are already advanced and need expert-level material
- you want a hands-on interactive platform rather than reading material

## Facets
- artifact type: learning-resource
- maturity: active
- function: reverse-engineering, security, documentation
- domain: reverse-engineering, security, tutorials, windows
- platform: windows, cpp
- tags: course, x64-assembly, malware-analysis, binary-analysis, free-course

## Member repositories
- 0xZ0F/Z0FCourse_ReverseEngineering (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:32.112671+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 2026-08-29T17:51:18.152202+00:00, confidence not recorded.
  - readme: https://github.com/0xZ0F/Z0FCourse_ReverseEngineering (fetched 2026-08-28T04:09:32.112671+00:00, sha 2797a81bf457)
- Data as of 2026-08-30T08:39:29.467469+00:00.