remove-ai-watermarks: Remove visible and invisible AI watermarks from images and video, and AI provenance metadata from images

by wiltodelta · Agent Tool · ★ 6.1k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install remove-ai-watermarks

brew install wiltodelta/tap/remove-ai-watermarks
pip install "remove-ai-watermarks[gpu]"

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillai-watermarkc2paclicomfyuicontent-credentialsexifgeminigemini-watermark-removergenerative-ai

Quick Facts

Stars6,083
Forks565
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score66/100
Open Issues2
Last Updated2026-10-22
Created2026-03-25
Platformscli, gemini, python
Est. Tokens~24k

About remove-ai-watermarks

Remove-AI-Watermarks Remove visible and invisible AI watermarks from images generated by Google Gemini (Nano Banana), ChatGPT / DALL-E, Stable Diffusion, Adobe Firefly, Midjourney, and other AI models. Strips SynthID, C2PA Content Credentials, EXIF/XMP "Made with AI" labels, and visible sparkle overlays — all in one command. ## Try it online: raiw.cc No Python, no GPU, no setup.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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