Sigil – A zero-knowledge steganography vault for AI training data

Hacker News

Hi HN, I’ve been experimenting with ways to protect digital assets from automated AI web scrapers. I built Sigil, a local-first desktop application that embeds cryptographically signed ownership IDs into the LSB (Least Significant Bit) layer of images. The desktop vault itself (Svelte/Tauri/SQLite) is closed-source to protect the HMAC-SHA256 signing architecture, but I have open-sourced the Rust extraction standard today. The idea is to create an open protocol where AI data procurement teams can run the extractor against their scraped datasets. If it detects a payload, they know the asset is cryptographically locked and requires a license. The extractor logic relies entirely on image and hex crates for memory-safe pixel parsing. I'd love any feedback on the extraction architecture or the LSB approach. Extractor Repo: https://github.com/nishal21/Sigil-extractor Landing Page (Astro): https://nishal21.github.io/Sigil-extractor/

Visit product View on Hacker NewsMar 28, 2026

Share card

Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: mac, open · Missing: agents, macos, agent

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

TrueTrace: A Passkey-Only, Zero-Knowledge Encrypted Vault55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TrueTrace: A Passkey-Only, Zero-Knowledge Encrypted Vault

Hacker News1

Zero-Knowledge Proofs in WebAssembly70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zero-Knowledge Proofs in WebAssembly

Hacker News81

A zero-knowledge VM with only one instruction50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A zero-knowledge VM with only one instruction

Hacker News1

Crystal Vault zero knowledge secrets storage48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Crystal Vault zero knowledge secrets storage

Hacker News9

Occson – a zero-knowledge configuration store54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Occson – a zero-knowledge configuration store

Hacker News7

Zero Knowledge Documents (on Dropbox)53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zero Knowledge Documents (on Dropbox)

Hacker News1

SaecretHeaven – Zero-knowledge encrypted photo vault with IPFS backup38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SaecretHeaven – Zero-knowledge encrypted photo vault with IPFS backup

Hacker News2

I built a Zero-Knowledge text shredder that deletes data on read70%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I built a Zero-Knowledge text shredder that deletes data on read

Hacker News2

SafeTrigger53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zero-knowledge vault - secure files, share on your terms

Product Hunt+133Privacy

The FPGA Zero-Knowledge Playground57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The FPGA Zero-Knowledge Playground

Hacker News3

Browse all products Analyze your launch