Hyperlocal DNSSEC Validating Unbound Docker Image

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Hello there! I've built a secure and trustworthy NLnetLabs Unbound Docker image as the most images didn't meet my standards on a zero trust policy. It supports DNSSEC, is sealed with chroot, runs with a non-root user and exposes only unprivileged ports. It is intended to provide a hyperlocal setup holding a local copy of the DNS root zone using zone transfers though but it will also run perfectly with your own unbound.conf if you'd rather like to use an upstream server which provides DoT or DoH features. So if your ISP's DNS servers having issues, you won't be affected at all. This setup will also add a plus on circumventing censorship using blocked DNS entries and adds a little more privacy but your ISP will still be able to see what you did there anyway. The image is built entirely online using workflows with GitHub Action and not locally on my systems at home. All downloads, even the downloads of the root files, are verified with PGP keys and the respective PGP armored signature files where available to provide maximum trust. It's a quite tiny Alpine Linux multiarch image and the architectures are on par with the architectures Pi-hole uses. In fact, it is a perfect complement for Pi-hole as an upstream server if you are already running Pi-hole for ad blocking and tracking prevention. As I wrote on my GitHub page, it was created with Pi-hole in mind. And with lots of love. I hope you enjoy the image and forgive me my shameless promotion^^ of my open source project. :) Just come and visit my GitHub repository https://github.com/madnuttah/unbound-docker if you'd like to learn more about this project. If you'd like to contribute, you're very welcome. Cheers and wishing all the best, madnuttah

Visit product View on Hacker NewsFeb 9, 2022

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77%77% 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, dock, tiny · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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.

AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews

40%40% 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

33%33% 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

14%14% 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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