ViruSaas – Virus Checks as a Service

Hacker News

Hi all, here is a side project I've just launched which might come in handy for certain situations. It's a very simple and free "do one thing and do it well" online service with exactly one feature: you upload a file, and it tells you — based on a ClamAV check — if that file contains a virus or not. I'm not having any ambitious plans with this project, but thanks to very low operational costs, I thought I can as well put it out there and keep it alive — maybe it's even useful for some people every now and then (just today, one of my coworkers forwarded me a fishy-looking email with an attachment, and using virusaas.com turned out to be the least painful way to do this kind of one-off check for a virus). I've also released the source code of the web app under GPLv3 at https://github.com/hygieia-saas/hygieia-webapp , although it's not as polished as it could be (no tests, for example — but see above, no ambitious plans). The main reason to do the project was to follow through with my own tutorial at https://manuel.kiessling.net/2021/05/02/tutorial-react-singl... , which worked out quite nicely.

Visit product View on Hacker NewsSep 14, 2022

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

87%87% 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: email, using, code · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: way · 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

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

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

16%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, 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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