# YelpArchive/osxcollector

A forensic evidence collection & analysis toolkit for OS X

Repository: https://github.com/YelpArchive/osxcollector
Canonical: https://ross.abutalabs.com/products/osxcollector
Homepage: http://yelp.github.io/osxcollector
Language: Python
License: NOASSERTION
License Family: other
Archived: true
Last push: 2019-06-19T15:40:49+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4412, "days_push": 2632, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1894, forks 239 (observed 2026-08-28T04:05:50.685585+00:00)

## What it is
OSXCollector is a forensic evidence collection and analysis toolkit for macOS/OS X. It is a single-file Python script that gathers system data (plists, SQLite databases, files) into a JSON archive for malware incident response.

## Use cases
- collect forensic evidence from a potentially infected mac
- investigate malware on os x
- answer how malware got on a machine
- gather plists and sqlite data for incident response
- package system state into a tar.gz for analysts

## When to choose
- you need a dependency-free single-file collector for macOS incident response
- you want JSON output for automated analysis pipelines

## When to avoid
- you need active development or support for modern macOS versions
- you need Windows or Linux forensics

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: security, cli, developer-tools
- domain: security, apple-ecosystem, developer-tools
- platform: python, cli
- tags: incident-response, malware-analysis, digital-forensics, osx, evidence-collection, forensics, macos

## Member repositories
- YelpArchive/osxcollector (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:50.685585+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 2026-08-30T03:12:53.851385+00:00, confidence not recorded.
  - readme: https://github.com/YelpArchive/osxcollector (fetched 2026-08-28T04:05:50.685585+00:00, sha 83a0751d46c5)
- Data as of 2026-08-30T08:39:29.467469+00:00.