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JWT-to-RLS Debugger for Backend Teams
Build a developer tool that traces a single authenticated request from token issuance through verification, role extraction, and row-level security context. The value is faster root-cause analysis when auth appears valid but data-layer authorization fails, especially around key rotation and algorithm changes.
Pourquoi c'est important
You ship an app with JWT auth and row-level security, then a routine security change causes a confusing outage. Login still works, user identity checks look healthy, but real API requests hit the database as if nobody is signed in. You bounce between auth responses, API logs, SQL role tests, and support threads, yet none of those prove what happened on the live request path. The biggest frustration is not just the failure itself, but the wasted hours spent proving whether the token was missing, mistrusted, or mapped to the wrong role. A focused debugger that shows the exact break point would remove a painful class of production incidents.
- · Conçu pour Small engineering teams and solo developers running production apps on managed Postgres backends with JWT-based auth and row-level security..
- · Monétisation la plus probable : SaaS subscription.
La douleur · Récit
You ship an app with JWT auth and row-level security, then a routine security change causes a confusing outage. Login still works, user identity checks look healthy, but real API requests hit the database as if nobody is signed in. You bounce between auth responses, API logs, SQL role tests, and support threads, yet none of those prove what happened on the live request path. The biggest frustration is not just the failure itself, but the wasted hours spent proving whether the token was missing, mistrusted, or mapped to the wrong role. A focused debugger that shows the exact break point would remove a painful class of production incidents.
Détail du score
Signal du marché
Mise sur le marché
Indie hackers and startup backend engineers using managed Postgres with JWT auth and row-level security in production.
~50K-150K highly relevant early adopters globally
SEO long-tail
$49/month
20 teams install the tool and 5 become paying customers after resolving a real auth incident within 30 days
Périmètre MVP · 1–2 semaines
- Build a token inspection UI that decodes JWT headers, claims, algorithm, and issuer details
- Implement JWKS fetch and signature verification checks for common signing algorithms
- Create a request replay endpoint that validates Authorization headers against configured backend settings
- Design a result screen that highlights auth service success versus data-layer failure states
- Publish a landing page targeting search terms around RLS auth mismatch and JWT rotation bugs
- Add connectors for managed backend config inputs such as project URL, anon key, and JWKS endpoint
- Implement a diagnostic decision tree for stale keys, missing bearer headers, and role-claim issues
- Add secure redaction for tokens, claims, and logs before storage
- Create a shareable incident report summarizing findings for engineering teams
- Run outreach to developers discussing JWT and RLS debugging issues to recruit first users
Différenciation
Pourquoi cela pourrait échouer
Auto-contre-argument — le signal de confiance le plus important
- 1Platform-native logs and docs may improve enough that developers prefer free built-in debugging paths.
- 2Without deep integration into backend internals, the product may diagnose symptoms but not confidently prove root cause in all cases.
- 3Security-sensitive buyers may avoid a third-party debugging service unless self-hosting or strict redaction is available.
Résumé des preuves
Comment l'IA a synthétisé cet aperçu — pas de citations textuelles
The discussion repeatedly points to a mismatch between successful identity validation and failed row-level security behavior. Multiple participants focus on whether the live request is actually carrying a trusted JWT and correct role context, and they recommend manual debugging across SQL, gateway logs, and token claims. That combination suggests a real and recurring need for software that unifies these checks into a single diagnosis flow.
Plan d'Action
Validez cette opportunité avant d'écrire du code
Prochaine Étape Recommandée
Construire
Signaux de demande forts. Vraie douleur et volonté de payer détectées — commencez à construire un MVP.
Kit de Textes pour Landing Page
Textes prêts à coller, basés sur le langage réel de la communauté Reddit
Titre Principal
JWT-to-RLS Debugger for Backend Teams
Sous-titre
Build a developer tool that traces a single authenticated request from token issuance through verification, role extraction, and row-level security context. The value is faster root-cause analysis when auth appears valid but data-layer authorization fails, especially around key rotation and algorithm changes.
Pour Qui
Pour Small engineering teams and solo developers running production apps on managed Postgres backends with JWT-based auth and row-level security.
Liste des Fonctionnalités
✓ Single-request auth trace from bearer token to database role context ✓ Automatic comparison of auth-service validation versus data API verification results ✓ Root-cause suggestions for missing token, stale JWKS, role-claim mismatch, or propagation lag
Où Valider
Partagez votre landing page sur r/GitHub · supabase/supabase — c'est exactement là que ces points de douleur ont été découverts.
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