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CyberVault – A Local-Only Password Manager in C#"

Hacker News

CyberVault – A Local-Only Password Manager in C#"

Hi HN, My friend and I built CyberVault, a lightweight password manager written in C#. It's designed for people who want full local control — no cloud sync, no accounts, and no third-party dependencies. It runs as a standalone Windows app and stores everything in an encrypted vault on your machine. We built it out of frustration with cloud-based managers and a desire for simplicity and transparency. Features: - Fully local storage (encrypted AES-256 vault file) - No remote sync or cloud - WPF GUI, no server setup needed - Experimental Chrome extension for autofill - Open source (MIT-licensed) It's still in active development, and we’re looking for feedback on: - Encryption/security model - UX/UI suggestions - Feature ideas - Help with browser extension GitHub: https://github.com/CyberNilsen/CyberVault Would love your thoughts or ideas!

Visit productView on Hacker NewsMay 28, 2025
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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, open · Missing: agents, macos, agent
78%78% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide, 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
44%44% 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
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
17%17% 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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