# corkami/pics

File formats dissections and more...

Repository: https://github.com/corkami/pics
Canonical: https://ross.abutalabs.com/products/pics
Language: Assembly
License Family: other
Topics: poster, patreon, dissection, fileformats
Last push: 2024-02-18T13:37:21+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": 4178, "days_push": 927, "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 11475, forks 790 (observed 2026-08-28T04:10:48.266917+00:00)

## What it is
A collection of visual posters and diagrams dissecting binary file formats such as PDF, JPG, MP4, and WAD, created by Corkami. It serves as educational reference material illustrating the internal structure of file formats, hardware, and protocols.

## Use cases
- understand the internal structure of file formats like PDF or MP4
- learn binary file format layouts visually
- find reference posters for reverse engineering binary formats
- study file format dissections for security research
- teach students how binary files are structured

## When to choose
- you need visual, poster-style documentation of binary file format structures
- you are learning or teaching reverse engineering and file format internals
- you want quick reference diagrams for formats like JPG, PDF, or WAD

## When to avoid
- you need a library or tool to programmatically parse file formats
- you require machine-readable format specifications rather than images
- you need actively updated documentation for the latest format versions

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: files, education, tutorials
- platform: cross-platform
- tags: file-formats, binary-posters, reverse-engineering, reference-material, visualizations

## Member repositories
- corkami/pics (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:48.266917+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 2026-08-29T17:15:33.862497+00:00, confidence not recorded.
  - readme: https://github.com/corkami/pics (fetched 2026-08-28T04:10:48.266917+00:00, sha 088c11a9d95d)
- Data as of 2026-08-30T08:39:29.467469+00:00.