# psal/anonymouth

Repository: https://github.com/psal/anonymouth
Canonical: https://ross.abutalabs.com/products/anonymouth
Language: Java
License: NOASSERTION
License Family: other
Last push: 2021-07-17T23:38:02+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4818, "days_push": 1873, "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 1943, forks 169 (observed 2026-08-28T04:05:57.599397+00:00)

## What it is
Anonymouth is a Java-based desktop application that helps users anonymize documents by detecting and suggesting edits to stylometric patterns like word length and n-grams. It was developed by Drexel University's Privacy, Security and Automation Lab and builds on the JStylo authorship detection libraries.

## Use cases
- anonymize a document before publishing it
- remove stylometric fingerprints from my writing
- avoid authorship detection in essays
- check which writing features reveal my identity
- rewrite text to obscure my writing style

## When to choose
- you need to reduce stylometric authorship signals in a document
- you want a guided, interactive tool for de-identifying your writing style
- you are researching authorship obfuscation techniques

## When to avoid
- you need guaranteed anonymity - the tool explicitly cannot guarantee documents are anonymous
- you need a modern, actively maintained tool - it requires Java 7 and development has largely stalled
- you need automated bulk anonymization rather than interactive editing

## Facets
- artifact type: application
- maturity: maintenance
- function: nlp, security, privacy
- domain: privacy, security
- platform: cross-platform, jvm
- tags: stylometry, authorship-anonymization, document-anonymization, java-swing, desktop-app, natural-language-processing, desktop

## Member repositories
- psal/anonymouth (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:57.599397+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 2026-08-30T03:08:02.785703+00:00, confidence not recorded.
  - readme: https://github.com/psal/anonymouth (fetched 2026-08-28T04:05:57.599397+00:00, sha 3073bb2e38cc)
- Data as of 2026-08-30T08:39:29.467469+00:00.