Unmarker.it – Client-Side Tool to Disrupt Invisible AI Watermarks

Hacker News

I built a browser-only tool that disrupts invisible AI watermarks using Canvas, geometry, noise, and JPEG recompression. No backend, no uploads, no tracking. Pipeline: Shake – Random rotation (±0.5°) + slight zoom Stir – Low-amplitude RGB noise via getImageData Crush – JPEG recompression at ~0.85 quality Tested with SynthID (Google Gemini AI watermarking), and it remained undetected in all tests. Pipeline improvements? What would you add/change? Github: https://github.com/ing-norante/unmarker.it

Visit product View on Hacker NewsNov 30, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, gemini, using · Missing: mac, agents, macos

55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

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Indie HackersIH features products with proven revenue · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, pipe, io · Missing: https docs, excited, just released

37%37% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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