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Nullroom.io – Experimental, stateless P2P messaging and file sharing

Hacker News

Nullroom.io – Experimental, stateless P2P messaging and file sharing

Hi HN, I’ve been experimenting with WebRTC and Rails 8 to see if it's possible to build a messaging utility that is truly "stateless". I wanted to create something for those moments when you need to move a snippet of text or a file between devices without leaving a trace on a server, a database, or a third-party cloud. The AI Collaboration: I also want to mention that this project has been a deep dive into collaborating with AI. I used AI to brainstorm the "Zero-Trace" architecture, help me harden the infrastructure after a security audit. How it works: Zero-Trace Architecture: No accounts, no cookies (beyond basic security), and absolutely no server-side logging. Client-Side Encryption: Encryption keys stay in the URL fragment (#). Since fragments are never sent to the server, the signaling layer is cryptographically blind to your data. P2P Signaling: We use ActionCable for the initial handshake. Once the WebRTC DataChannel is established, the conversation and file transfers happen directly between browsers. Zero Third-Party Dependencies: No external fonts, scripts, or trackers. Everything is served from the origin to prevent IP leakage to third-party providers. The Beta Experiment: I'm currently testing the stability of the P2P signaling. I’ve enabled file transfers (up to 24MB) for everyone during this phase. I’m curious to see how the connection logic handles different network environments. The Tech Stack: Framework: Rails 8 Deployment: Kamal 2 on a single VPS I’d love to get your thoughts on the UX and any edge cases you find with the WebRTC handshake!

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Product HuntOn track for Day 1 leaderboard · Strong signals: single · Missing: mac, agents, macos
77%77% 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
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
43%43% 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 · Missing: mobile apps, ios, personal
33%33% 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
25%25% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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