Desktop‑2FA – offline, encrypted 2FA authenticator for your desktop

Hacker News

I’ve released desktop‑2fa v0.4.0 — an offline, encrypted TOTP authenticator designed for desktops, VMs, and air‑gapped environments. Features: - AES‑GCM encrypted vault with Argon2 key derivation - No cloud, no phone, no telemetry - RFC‑compliant TOTP (SHA1/SHA256/SHA512) - Full CLI (add/list/generate/rename/remove/export/import/backup) - 99% test coverage - Zero external dependencies GitHub: https://github.com/wrogistefan/desktop-2fa I built this because I needed a reproducible, open-source 2FA tool for secure workstations and virtualized environments. Feedback welcome.

Visit product View on Hacker NewsDec 28, 2025

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3points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos

75%75% 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.

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.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

44%44% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

35%35% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

28%28% 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

14%14% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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