Hirosend – Simple Encrypted File Sharing

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I built Hirosend because I needed a fast and secure way to send files to clients without asking them to create accounts or navigate permission screens. Dropbox/Drive were too heavy for one-off transfers, WeTransfer felt clunky for quick sends, and I really missed the simplicity Firefox Send had before it shut down. Hirosend lets you upload a file, set expiration, add an optional password, or generate a one-time magic link. Recipients just click and download — no signup required on their side. Files are encrypted before being stored and automatically deleted after expiration. There are basic access analytics so you know when a link was opened. I’d love feedback on whether this solves a pain point for you, and what features would you like to see added.

Visit product View on Hacker NewsNov 21, 2025

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69%69% 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: open · Missing: mac, agents, macos

65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

60%60% predicted probability of success on AppSumo, 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

32%32% 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

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

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

18%18% 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

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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