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SecureBuild – Zero-CVE Images That Pay OSS Projects

Hacker News

SecureBuild – Zero-CVE Images That Pay OSS Projects

We're launching SecureBuild: https://securebuild.com — a new way for open source projects and maintainers to earn revenue by partnering with and endorsing our Zero-CVE container images of their project. We’ve spent the last decade at Replicated ( https://news.ycombinator.com/item?id=9841243 ) helping commercial and open source software vendors securely distribute their apps to enterprise environments. During that time, we saw firsthand how hard it is for maintainers to fund their work, and how increasingly demanding enterprises have become when it comes to demonstrable security and scanning. SecureBuild is our attempt to bridge that gap. Built on top of Wolfi ( https://news.ycombinator.com/item?id=36489847 ), we provide Zero-CVE container images with tight SLAs, full SBOMs, etc, but we route 70% of direct subscription revenue back to the open source projects that create them. We’re especially interested in partnering with open source maintainers who want to make their projects more secure and sustainable without changing licenses. We handle builds, hosting, sales, patching, and customer delivery. I'm Grant ( https://news.ycombinator.com/user?id=grantmiller ), co-founder of Replicated & co-creator of SecureBuild, working with my co-founder Marc Campbell ( https://news.ycombinator.com/user?id=marcc ). We hope this can be part of a broader push toward a more secure, economically sustainable future for open source. Happy to answer questions and share more details!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
89%89% 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
78%78% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, new · Missing: mac, agents, macos
66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, way · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, subscription · Missing: arr, mrr, profit
22%22% 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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