Envware – E2EE CLI to manage environment variables across devices

Hacker News

Hi HN, I built Envware because I was tired of manually syncing .env files via Slack/DM or insecure notes when switching between my laptop and workstation. Envware is a CLI tool that simplifies environment variable management with a focus on security and developer experience. Key features: - End-to-End Encryption (E2EE): Secrets are encrypted locally on your machine before being pushed to the cloud. We never see your plain-text values. - SSH Key Verification: Device authorization is tied to your SSH keys. - Multi-device Sync: Seamlessly pull your project environments on any authorized machine. - Project Collaboration: Share projects with team members securely. It’s currently in version 1.1.9, and I’m working on scaling it further. I’d love to hear your feedback on the security model and the CLI workflow. Website: https://www.envware.dev Docs: https://www.envware.dev/docs Thanks!

Visit product View on Hacker NewsJan 31, 2026

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

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% 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

38%38% 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

32%32% predicted probability of success on AppSumo, 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

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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