Europa – A self-hosted, encrypted file sharing service

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Hi HN, I'm excited to introduce Europa ( https://europa.migairu.com ), a file sharing service focused on privacy and security. This is my first entrepreneurial project as I wait to begin college, so it's my first time launching something beyond the scope of a personal project. Europa helps protect sensitive files by encrypting them in your browser before upload. The encryption keys come from your passphrase and stay on your device - we never see or store them. This means your files remain private since only people with the passphrase can decrypt them. The service is simple to use: Upload a file, choose when it expires (up to 7 days), and share the download link with the passphrase. There's no need to create an account. Europa can handle files up to 2GB by splitting them into encrypted pieces during upload and putting them back together when downloaded. Since Europa is open source under the GPL v3 license, you can run it on your own systems. The code and setup instructions are available at https://github.com/Migairu/europa . The service uses C# ASP.NET Core for the backend, Azure Blob Storage for files, and Web Crypto APIs for encryption. I designed the interface to be straightforward, with helpful visuals showing how the encryption keeps files secure. My goal is to make strong encryption accessible while keeping the service easy to use. I would appreciate hearing your thoughts on Europa. What features would you find most helpful? How could the self-hosting experience be improved? As a first-time entrepreneur, I also welcome advice from others who have launched similar ventures - your experience and insights would be invaluable. You can learn more at europa.migairu.com or check out the code on GitHub. I look forward to your feedback and suggestions for making Europa better serve users' needs.

Visit product View on Hacker NewsJan 29, 2025

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

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, visual, code · Missing: mac, agents, macos

67%67% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, lua, open source · Missing: https docs, just released, exist

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Strong signals: host, interface, users · Missing: plus, platform, intuitive

46%46% 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

12%12% 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, introduce · Missing: web3, chat, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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