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Git-agecrypt – transparent file-level encryption for Git

Hacker News

Git-agecrypt – transparent file-level encryption for Git

Greetings HN! I've forked the excellent work done by [vlaci/git-agecrypt]( https://github.com/vlaci/git-agecrypt ), looks like the original project has not been maintained for a while, so I decided to pick it up, update all the dependencies and add some thorough testing. I like the ability to store sensitive data in public repositories, it's especially useful when bootstrapping new IaC repositories, you don't have anything at the beginning of a new project so there is no place yet to store secrets, this is "a way" of doing it. I know you can use tools like SOPS but I think the transparent approach offered by tools like this one or git-crypt really shine for many use cases. Looking forward to hear your feedback!

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos
73%73% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
64%64% 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 · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
35%35% predicted probability of success on Indie Hackers, 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 · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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