Hackerrecon

Hackerrecon

TrustMRR

Browser-based cybersecurity toolkit for reconnaissance, security research, and penetration testing.20 browser-based security utilities, simulated terminal/cyber-operation environments, client-side pro

Browser-based cybersecurity toolkit for reconnaissance, security research, and penetration testing.20 browser-based security utilities, simulated terminal/cyber-operation environments, client-side processing, reconnaissance tools, JWT inspection, security-header auditing, cryptographic utilities, and network diagnostics

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Actual performance

Did not reach leaderboard

Launch Intel predictions

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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, 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 released
35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
34%34% 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
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Strong signals: crypto · Missing: web3, chat, cryptocurrency
24%24% predicted probability of success on BetaList, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
24%24% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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