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Sneak Link – Share links from Nextcloud, Immich, without full exposure

Hacker News

Sneak Link – Share links from Nextcloud, Immich, without full exposure

Hi HN! I've built Sneak Link to solve a common selfhosting problem: securely sharing content from internal services like NextCloud, Immich, or Paperless without exposing the entire service to the internet. Sneak Link works by using the share link itself as a kind of "knock", similar to old school port knocking. When someone accesses the link, Sneak Link verifies it with the backend service (e.g. NextCloud) to confirm that it's valid and public. If it checks out, SneakLink sets a signed cookie that grants temporary access to the service. It's designed for self-hosters running these services on internal networks who still want to share files or photos with friends and family. Right now, it supports NextCloud, Paperless-ngx, Immich, Seafile and Photoprism. It has a simple dashboard: https://github.com/felixandersen/sneak-link?tab=readme-ov-fi... and a Prometheus metrics endpoint. The project is open source. I have aimed at making it lightweight, with minimal dependencies. The architecture allows new services to be added. I'd love feedback from others running self-hosted setups or ideas for new integrations! Repo: https://github.com/felixandersen/sneak-link

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
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.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive
59%59% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, open · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% 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
11%11% 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.

Incorrect prediction on native model

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