How I Would Fix database rules leaking customer data in a GoHighLevel subscription dashboard Using Launch Ready.

How I Would Fix database rules leaking customer data in a GoHighLevel subscription dashboard Using Launch Ready

The symptom is usually blunt: one user logs into a subscription dashboard and sees another customer's name, email, plan, invoices, or usage data. In business terms, this is a trust and compliance problem, not just a bug.

The most likely root cause is broken authorization at the database layer or in the API that reads from it. The first thing I would inspect is every query path that returns customer records, then I would verify whether the request is actually scoped to the signed-in account and not just "any authenticated user".

Triage in the First Hour

1. Confirm the leak with two separate test accounts.

• Use one internal test account and one sandbox customer account.
• Check whether the dashboard shows cross-account data in lists, detail pages, exports, and search results.
• Record exactly which fields leak: names, emails, billing status, subscription tier, notes, or metadata.

2. Check the auth context on the server side.

• Verify whether each request includes a tenant ID, account ID, org ID, or location ID.
• Confirm the API does not trust a client-supplied ID without server-side validation.

3. Inspect logs for access patterns.

• Look for repeated requests returning multiple customer IDs from one session.
• Check whether any admin token, service token, or shared integration key is being reused across tenants.

4. Review the database rules or row-level access controls.

• If this is Supabase-like behavior or a backend with row filtering rules, inspect policies first.
• If data comes through GoHighLevel webhooks or custom endpoints, check whether filtering happens before or after persistence.

5. Check recent deploys and config changes.

• Review the last 24 to 72 hours of changes in environment variables, webhook handlers, and API routes.
• Look for schema changes that removed a tenant filter or changed an index/key used in queries.

6. Inspect dashboard screens that render customer lists.

• Open list views, profile pages, invoices, and "recent activity" panels.
• Confirm whether data is fetched client-side with broad queries instead of server-scoped endpoints.

7. Verify integrations and automation accounts.

• Check GoHighLevel sub-accounts, snapshots, workflows, triggers, and API keys.
• Confirm there are no shared credentials across clients or environments.

8. Freeze risky writes if needed.

• If leakage is active and repeatable, pause exports, bulk sync jobs, and background jobs until access control is fixed.

A quick diagnostic pattern I often use looks like this:

## Compare responses for two different test users
curl -H "Authorization: Bearer TOKEN_A" https://api.example.com/customers | jq '.[].id'
curl -H "Authorization: Bearer TOKEN_B" https://api.example.com/customers | jq '.[].id'

If both tokens return overlapping customer IDs when they should not, you have an authorization boundary problem.

Root Causes

| Likely cause | What it looks like | How I confirm it | |---|---|---| | Missing tenant filter in queries | One user can load another user's records | Inspect SQL/query builder for missing `account_id`, `org_id`, or `location_id` constraint | | Broken row-level security rules | Database returns rows outside the current tenant | Review policies and test with direct queries under different roles | | Shared integration token | All sub-accounts read from one broad credential | Audit GoHighLevel API keys and service accounts for reuse across customers | | Client-side filtering only | UI hides data visually but backend still sends everything | Open network tab and inspect raw API responses | | Weak object-level authorization | Detail pages accept an ID and return any matching record | Try alternate IDs in safe internal testing and confirm server checks ownership | | Cached cross-tenant responses | One user's data appears from cache after another login | Check CDN/app cache keys and session scoping |

The highest-risk pattern here is client-side filtering pretending to be security. If the browser receives all customer rows first and filters them afterward, you already lost control of the data.

The Fix Plan

First I would stop the bleed. That means narrowing read access immediately before touching UI polish or nonessential features.

1. Put the app into a controlled maintenance mode if leakage is broad.

• Keep sign-in available if possible.
• Disable exports, admin bulk views, and any page that exposes mixed-tenant data until fixed.

2. Move authorization enforcement to the server or database layer.

• Every read query must include tenant scoping based on the authenticated session.
• Do not accept tenant IDs from hidden form fields or query strings unless they are verified against the session on the server.

3. Tighten database rules.

• Add row-level policies so records can only be read by their owning account.
• If your stack cannot support true row-level security cleanly, add a service-layer guard that blocks unscoped reads before they hit the client.

4. Rework dangerous endpoints first.

• Customer list endpoints
• Subscription detail endpoints
• Invoice/payment history endpoints
• Search endpoints
• Export CSV/PDF endpoints

5. Separate admin access from customer access.

• Admins should use explicit elevated roles with audit logging.
• Customers should never inherit broad permissions because they are logged in through a shared frontend route.

6. Rotate secrets if any token exposure is possible.

• Regenerate API keys used by GoHighLevel integrations if logs suggest compromise risk.
• Replace any hardcoded secrets with environment variables immediately.

7. Add caching boundaries carefully.

• Cache only public assets or explicitly tenant-scoped responses.
• Include tenant ID in cache keys where private content must be cached at all.

8. Add audit logging for sensitive reads.

• Log who accessed what record and when.
• Keep logs useful but avoid dumping full personal data into logs.

9. Deploy in a staged way.

• Test on staging with production-like records masked where needed.
• Roll out to production behind a feature flag if possible.

My rule here is simple: fix authorization before fixing presentation. A beautiful dashboard that leaks customer records is still a failed product.

Regression Tests Before Redeploy

I would not redeploy until these checks pass:

1. Tenant isolation tests

• User A cannot list User B's customers.
• User A cannot fetch User B's invoice by direct URL or API call.
• User A cannot search across other tenants' records.

2. Role-based access tests

• Customer role sees only their own data.
• Admin role sees expected broader scope with audit logging enabled.
• Support role sees only assigned accounts if that is your policy.

3. Negative authorization tests

• Missing token returns 401.
• Valid token without permission returns 403.
• Tampered tenant ID does not change returned records.

4. Cache tests

• Logging out clears private state correctly.
• Switching accounts does not show stale personal data from previous sessions.

5. Integration tests around GoHighLevel flows

• Webhooks create records under the correct account only.
• Automation-triggered updates do not overwrite another tenant's subscription status.

6. Manual QA on real screens

• Dashboard home
• Subscription details

billing history support tickets export buttons search results

Acceptance criteria I would use:

• 0 cross-tenant records visible in test runs across 10 attempts per role pair
• 100 percent of sensitive read routes enforce server-side ownership checks
• No private customer fields appear in client network payloads unless authorized
• p95 dashboard response time stays under 500 ms after adding authorization checks

Prevention

To stop this coming back, I would put guardrails around security review, deployment discipline, and observability.

• Code review gate:

Every query touching customer data must show its ownership filter in review comments before merge.

• Security checklist:

Review authn/authz separately from UI behavior. If the backend does not enforce ownership correctly, do not ship it.

• Monitoring:

Alert on unusual spikes in cross-account read attempts, repeated 403s on sensitive routes, and unexpected export activity.

• Logging:

Track actor ID, tenant ID, route name, and result code for sensitive reads without storing full personal payloads in logs.

• UX guardrails:

Show clear account context at all times so users know which workspace they are viewing. This reduces accidental admin confusion but does not replace real security.

• Performance guardrails:

Add indexes on tenant-scoped columns such as `account_id` or `location_id` so secure queries do not become slow enough that someone removes them later to "fix performance".

Here is the decision path I want every team to follow:

When to Use Launch Ready

I built Launch Ready for exactly this kind of rescue work when founders need production safety fast without dragging out discovery for weeks.

Use it when you need:

• Domain setup cleaned up before launch
• Email authentication fixed so transactional mail lands properly
• Cloudflare configured for SSL,

caching, DDoS protection, redirects, and subdomains

• Secrets moved out of code and into proper environment variables
• Production deployment verified end to end
• Uptime monitoring added before traffic starts paying for ads

It includes DNS, redirects, subdomains, Cloudflare, SSL, caching, DDoS protection, SPF/DKIM/DMARC, production deployment, environment variables, secrets, uptime monitoring, and a handover checklist.

What I need from you before I start:

• Access to your hosting provider
• Domain registrar access
• Cloudflare access if already connected
• GoHighLevel sub-account details or snapshot info
• Current deployment repo or build tool access
• Any known incident examples showing leaked records

If your dashboard already leaked customer data once, do not wait until launch day to fix it. The cost of one exposed subscription record can be support load, refunds, lost conversions, and damage you will feel long after deployment succeeds.

References

1. Roadmap.sh API Security Best Practices: https://roadmap.sh/api-security-best-practices 2. Roadmap.sh Code Review Best Practices: https://roadmap.sh/code-review-best-practices 3. Roadmap.sh QA: https://roadmap.sh/qa 4. OWASP Access Control Cheat Sheet: https://cheatsheetseries.owasp.org/cheatsheets/Access_Control_Cheat_Sheet.html 5. GoHighLevel Help Center: https://help.gohighlevel.com/

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Take the next step

If this is a problem in your product right now, here is what to do next:

• [Use the free Cyprian tools](/tools) - estimate cost, score app risk, check launch readiness, or pick the right service sprint.

• [Book a discovery call](/contact) - I will tell you honestly whether you need a sprint or if you can DIY the next step.

*Written by Cyprian Tinashe Aarons - senior full-stack and AI engineer helping founders rescue, launch, automate, and scale AI-built products.*