whatisgithub

What is image-provenance?

863401402/image-provenance — explained in plain English

Analysis updated 2026-05-18

124JavaScriptAudience · generalComplexity · 1/5LicenseSetup · easy

In one sentence

A browser only tool that checks if an image was AI generated and can strip or disrupt hidden AI watermarks.

Mindmap

mindmap
  root((repo))
    What it does
      Detects AI generated images
      Shows hidden metadata
      Disrupts watermarks
    Tech stack
      JavaScript
      HTML
      Web Workers
    Use cases
      Provenance checking
      Metadata inspection
      Watermark research
    Audience
      General users
      Researchers

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Check whether a photo was likely generated by AI before sharing or publishing it.

USE CASE 2

View all hidden metadata in an image, including GPS location and editing history.

USE CASE 3

Strip AI watermark and provenance metadata from an image for research purposes.

What is it built with?

JavaScriptHTMLWeb Workers

How does it compare?

863401402/image-provenancefastify/fastify-schedulekunchenguid/lavish-axi
Stars124119118
LanguageJavaScriptJavaScriptJavaScript
Last pushed2026-07-01
MaintenanceActive
Setup difficultyeasyeasyeasy
Complexity1/52/51/5
Audiencegeneraldeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

Runs from a simple local HTTP server since ES Modules need http access, not a plain file open.

Free to use, modify, and distribute, including commercially, as long as you keep the copyright notice.

So what is it?

Image Provenance is a browser based tool for checking whether an image was likely generated by AI, and for disrupting invisible AI watermarks hidden inside images. Everything runs entirely inside your browser, so images never leave your device. On the detection side, it checks for several kinds of AI origin signals: C2PA and Content Credentials, which are metadata standards used by companies like Adobe and some camera makers, known signatures left by specific AI image generators, and frequency domain analysis, a technique that looks at the underlying mathematical pattern of an image's pixels, which tends to differ subtly between AI generated and camera captured photos. Results come with a confidence rating, and only strong or medium signals are reported as an actual match. A separate metadata viewer displays all the hidden information stored inside an image file, including GPS location, shown with a privacy warning, a full editing history, and timestamps, drawing on the EXIF, XMP, IPTC, and ICC metadata formats. The conversion tools can strip out C2PA credentials, re encode an image through the browser's own canvas, inject realistic looking camera metadata from real camera models, and apply several watermark disruption techniques, including manipulating an image's frequency domain phase. The author states this disruption feature is meant for research into how well AI detection tools hold up, not for spreading disinformation or committing fraud. The whole project is built with plain HTML and JavaScript, with no framework, and relies on only two small external libraries, one for reading metadata and one for writing it. The README is written mainly in Chinese, with an English version also available, and the project is released under the MIT license.

Copy-paste prompts

Prompt 1
Explain what the frequency domain analysis in this tool is actually checking for.
Prompt 2
Show me how to run this tool locally using Python's http.server.
Prompt 3
What does a strong confidence AI detection signal mean versus a weak one in this tool.
Prompt 4
Explain the ethical guidance this project gives about watermark disruption.

Frequently asked questions

What is image-provenance?

A browser only tool that checks if an image was AI generated and can strip or disrupt hidden AI watermarks.

What language is image-provenance written in?

Mainly JavaScript. The stack also includes JavaScript, HTML, Web Workers.

What license does image-provenance use?

Free to use, modify, and distribute, including commercially, as long as you keep the copyright notice.

How hard is image-provenance to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is image-provenance for?

Mainly general.

Open on GitHub → Ask about another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.