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Node Version Audit – Audit Your Node Version for Known CVEs and Patches

Hacker News

Node Version Audit – Audit Your Node Version for Known CVEs and Patches

I wrote Node Version Audit to automatically keep track of Node patches, particularly for releases that fix CVEs. While it can be ran directly, it is designed to run as part of a pipeline to produce warnings if the runtime version of Node has CVEs, or is no longer supported. The cool part (IMO), is that Node Version Audit automatically keeps track of node releases and CVEs by parsing the change log, and so there is no curation needed to maintain it. I would love any thoughts!

Visit product View on Hacker NewsAug 31, 2022

Actual performance

3points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Strong signals: pipe, io · Missing: https docs, excited, just released

47%47% 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 HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

44%44% 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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

22%22% 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

13%13% 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

9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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