Jw

Jwt.is – JSON Web Token Debugger

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Jwt.is – JSON Web Token Debugger

The team at Rownd is excited to announce https://jwt.is , an updated take on JSON Web Token debugging. Like most developers, we've used jwt.io for years, but it lacks a number of useful features that would make it even more convenient. We're building on the shoulders of those who've come before us. :-) In addition to the basic JWT decoding and signature verification, we've added things like: - Verification using JWK endpoints - Locally stored history of tokens and keys - Verification for EdDSA signatures - Detection of common token providers (e.g., Google, Apple, etc) - Dark mode! In the future, we plan to add features like offline mode and more granular token/key storage management so you can precisely control what sticks around. Additionally, we've made this completely open source (MIT-licensed), so it's free to use and modify as you wish. And of course, contributions are always welcomed! Let us know what you think!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, open source, ide · Missing: https docs, just released, exist
79%79% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: apple, google, using · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: google, way · Missing: mobile apps, ios, personal
55%55% 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
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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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