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iOS app to learn about RSA cryptography
Hacker NewsiOS app to learn about RSA cryptography
I've created an educational app to help people learn about how RSA cryptography works. Right now it's iPhone only (though the iPhone version will run on iPads), and it requires iOS 16. Any feedback, positive or negative, would be greatly appreciated. I'm happy to answer any questions if you comment here or email me at LearnRSAApp@gmail.com Link: https://apps.apple.com/us/app/learn-rsa-cryptography/id16714... Thanks!
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Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios · Missing: supports, reddit linkedin, podcasting88%88% 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.
TrustMRRFits verified-revenue profile · Strong signals: ios, apps, education · Missing: mobile apps, personal, entrepreneurs73%73% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, email · Missing: mac, agents, macos68%68% 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: io · Missing: https docs, excited, just released31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · 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, revenue20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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