Flask-Vault – Securely store and manage credentials in Flask

Hacker News

After months away from programming and especially Python, I decided to develop a new project inspired by Rails secure credential management. This new project is a library for Flask that allows you to securely manage an application's credentials and easily encrypt/decrypt sensitive data using AES-GCM with a 128-bit key. Key Features: - Effortless CLI Commands: Flask-Vault offers a set of intuitive CLI commands that make it easy to securely store secrets, such as API keys, database credentials, and more. - Simplified Encryption and Decryption of text and files. Check out Flask-Vault on GitHub and let me know what you think. Your feedback is invaluable! https://github.com/multiversecoder/Flask-Vault

Visit product View on Hacker NewsSep 14, 2023

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

64%64% 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 · Strong signals: intuitive · Missing: plus, platform, reviews

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, 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.

TrustMRRLess likely to generate early MRR · Strong signals: month, way · Missing: mobile apps, ios, personal

37%37% 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

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

1%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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