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Auto-Unpublish NPM Packages Published Outside CI
Hacker NewsAuto-Unpublish NPM Packages Published Outside CI
A lot of vendors and open-source projects shared guidance on protecting users from downloading malicious NPM packages after the Shai-Hulud campaign — but almost nothing focused on protecting maintainers from accidentally (or maliciously) publishing them. So we built a small tool that continuously monitors your NPM packages and automatically unpublishes any version not produced by your CI workflow.
Share cardActual performance
6points
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Did not reach leaderboard
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, open · Missing: mac, agents, macos55%55% 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 NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting36%36% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% 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, crypto7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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