I

I made an app to stop spammy form submissions with custom filters

Hacker News

I made an app to stop spammy form submissions with custom filters

Hey HN! Tired of dealing with spam form submissions? I sure am! That is why I built FormSanitizer: a straightforward solution for blocking unwanted noise. It's easy to integrate with existing website form and offers features like custom keyword filters and random string detection. My goal was to create a simple, effective tool that saves developers and website owners time and frustration. Check it out at https://www.formsanitizer.com/ I'd love to hear your thoughts and any feedback you might have! Have you faced similar spam issues, and what solutions have you tried? Caleb,

Visit product View on Hacker NewsMar 31, 2025

Actual performance

1points

1comments

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, io · Missing: https docs, excited, just released

66%66% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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

35%35% 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

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

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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