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PassVault – A secure, lightweight, and offline Android password manager

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PassVault – A secure, lightweight, and offline Android password manager

PassVault is a lightweight password manager that allows users to securely store credentials on their device. All data is stored locally and sensitive information is encrypted using the Android Keystore system. The application does not require internet permissions. User data never leaves the device. Core Features Secure PIN Authentication Biometric (Fingerprint) Login Encrypted Database (AES-256) Argon2Kt for file encryption Add, View, Edit, & Delete Passwords In-app Password Generator Encrypted Import/Export (for backups and transfer) Encrypted Automatic Backups Import from KeePass (using kotpass)/Bitwarden

Visit productView on Hacker NewsNov 25, 2025
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Actual performance

2points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, using · Missing: mac, agents, macos
63%63% predicted probability of success on Product Hunt, 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: io · Missing: https docs, excited, just released
50%50% 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 · Strong signals: users · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
31%31% 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
15%15% 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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