services / vibe-code-rescue

AI-Built App Rescue for marketplace products: The API security Founder Playbook for an agency owner shipping a client portal quickly.

You have a client portal that mostly works, but the scary part is not the UI. It is the API layer behind it.

AI-Built App Rescue for marketplace products: The API security Founder Playbook for an agency owner shipping a client portal quickly

You have a client portal that mostly works, but the scary part is not the UI. It is the API layer behind it.

If you built it with Lovable, Bolt, Cursor, v0, Webflow, or a similar tool, I usually find the same pattern: endpoints are open wider than they should be, auth is inconsistent, secrets are exposed somewhere in the build history, and the database rules do not match the product logic. If you ignore that, the business cost is not theoretical. It turns into leaked customer data, broken onboarding, support tickets from confused users, failed app review if mobile is involved, and a launch delay that burns ad spend while you are still fixing access control.

What This Sprint Actually Fixes

I then fix the highest-risk items, redeploy the app safely, and hand you a clear report so your team knows what changed and what still needs attention.

This is built for an agency owner who needs to ship a client portal quickly and cannot afford a messy security incident after launch.

If you want me to assess whether your build is salvageable before you commit to a full rescue sprint, book a discovery call at https://cal.com/cyprian-aarons/discovery.

The Production Risks I Look For

1. Open endpoints with no real authorization

I often see APIs where any logged-in user can hit any record if they know or guess an ID. In marketplace products this becomes cross-account data exposure fast: invoices, bookings, messages, contracts, or private files leaking across tenants.

2. Exposed keys and weak secret handling

AI-built apps frequently leave API keys in frontend code, environment files committed too early, or deployment settings copied between staging and production. That creates account takeover risk for third-party services and can trigger unexpected billing spikes.

3. Broken auth middleware and role checks

A portal may look protected because there is a login screen, but the backend still trusts client-side state too much. I check whether admin routes actually verify role claims server-side and whether session expiry behaves correctly under refreshes and token reuse.

4. Input validation gaps that create bad data or abuse paths

Marketplace workflows are full of forms: listings, profile updates, uploads, payments metadata, messaging inputs. Without strict validation and normalization you get corrupted records at best and injection-style abuse at worst.

5. CORS mistakes that widen attack surface

Overly permissive CORS often shows up in prototype builds because it "makes things work." In production it can let untrusted origins call sensitive APIs from browsers when they should not be able to.

6. Slow queries and missing indexes

A portal can pass functional testing and still fail under real usage because list pages scan too much data or filters do not use indexes. That becomes p95 latency spikes above 800 ms on common actions like dashboard loads or search results.

7. Weak observability and no useful error trail

If errors are swallowed or logs are noisy nonsense messages with no request IDs, you cannot debug production issues quickly. That means longer downtime windows and more support hours wasted on "it does not work" tickets.

8. AI red-team blind spots in generated flows

If your product uses AI features inside the portal - for example drafting messages or summarizing tickets - I test for prompt injection and unsafe tool use. A malicious user should not be able to trick the model into exposing another tenant's data or calling privileged actions without human approval.

The Sprint Plan

Day 1: I audit the app like an attacker would.

I review routes, middleware, auth flows, environment variables, deployment settings, database policies, logging setup, third-party integrations, and any AI-generated endpoints. I map the highest business risks first: cross-tenant access, exposed secrets from Lovable or Cursor builds if relevant to your stack history (or similar tools), broken write paths in the client portal flow, and anything that could stop launch this week.

Day 2: I fix access control before anything cosmetic.

I tighten auth middleware so every sensitive endpoint checks identity and role on the server side. I also close obvious open routes around records like users,, orders,, bookings,, files,, messages,, or billing objects depending on your marketplace model.

Day 3: I repair input handling and browser security controls.

I add validation for payloads that create or update records,, lock down CORS to known origins,, separate dev/staging/prod environments,, and make sure secrets are loaded safely through deployment config rather than hardcoded into source files. If file uploads exist,, I check size limits,, content type checks,, storage permissions,, and public URL exposure.

Day 4: I fix database rules,, indexes,, and query performance.

I align row-level rules or equivalent database permissions with your product logic so one tenant cannot read another tenant's data. Then I add missing indexes,, inspect query plans where needed,, reduce expensive joins or repeated fetches,, and target p95 response times under 300 ms for core dashboard reads where the stack allows it.

Day 5: I harden errors,, logs,, monitoring,, and regression coverage.

I wire up Sentry or improve its current setup so errors include enough context to debug without exposing private data in logs. Then I run regression checks on sign-in,, signup,,, invitation acceptance,,, payment-related flows,,, search,,, message creation,,, profile edits,,, admin access,,, and any AI-assisted workflow used by your team or customers.

Day 6 to 7: I redeploy cleanly and hand over documentation.

I push the fixed build through staging into production with a rollback plan ready if something unexpected appears. After release,I deliver a handover report that explains what was found,,,, what was fixed,,,, what remains risky,,,,and what your next sprint should cover if you want me back on retainer later.

What You Get at Handover

You get more than "the app is fixed."

  • A security audit summary written in plain English
  • A list of exposed key findings with remediation status
  • Open endpoint review notes
  • Auth middleware fixes applied
  • Input validation updates
  • CORS policy tightened
  • Database rule review plus index recommendations
  • Query performance notes with specific slow paths called out
  • Error handling cleanup
  • Sentry configured or improved
  • Regression test checklist run against critical flows
  • Redeployed production build
  • Environment separation verified across dev/staging/prod
  • Monitoring checklist for alerts and error tracking
  • Documentation covering what changed and how to maintain it

If useful for your team,I will also leave short implementation notes your developer can follow without guessing what changed inside the rescue sprint.

When You Should Not Buy This

Do not buy this sprint if you still do not know what the product must do in production.

If your market fit is unclear,the portal changes every day,and you expect design-by-committee feedback after launch,this sprint will only stabilize chaos faster,it will not replace product strategy.

Do not buy this if you need a full architecture rebuild across multiple systems,mobile apps,and custom infrastructure in one shot. In that case,I would split it into separate phases instead of pretending one week can solve everything safely.

A better DIY alternative is this:

1. Freeze features for 48 hours. 2. List every authenticated route. 3. Check each route against role-based access. 4. Remove hardcoded secrets. 5. Lock CORS to known domains. 6. Add validation on all write endpoints. 7. Review logs for sensitive data leakage. 8. Test one full happy path plus one failure path per core workflow. 9. Measure dashboard response times. 10. Redeploy only after staging passes those checks.

That gets you safer fast,but it still leaves room for hidden bugs unless someone senior reviews it end-to-end.

Founder Decision Checklist

Answer yes or no:

1. Are we shipping a client portal within 7 days? 2. Was this built with Lovable,Bolt,Cursor,v0,Figma-to-code tooling,a low-code stack like Webflow/GoHighLevel/or something similarly fast? 3. Do we have any endpoints that might be accessible by guessing IDs? 4. Are secrets definitely out of frontend code,and out of old deployment environments? 5. Do we know which roles can read which records? 6. Have we tested CORS against non-approved domains? 7. Do we have Sentry,error logs,and request traces we can actually use? 8. Are there slow list pages,exports,dashboards,right now? 9.,Have we checked database rules,indexes,and query plans recently? 10.,Would a data leak,failing login flow,and support spike hurt launch revenue this month?

If you answered yes to three or more of those,you probably need rescue work before launch rather than after launch.

References

  • https://roadmap.sh/api-security-best-practices
  • https://roadmap.sh/code-review-best-practices
  • https://owasp.org/www-project-api-security/
  • https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS
  • https://docs.sentry.io/

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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.*

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About the author

Cyprian Tinashe AaronsSenior Full Stack & AI Engineer

Cyprian helps founders rescue, secure, deploy, and automate AI-built apps with production-grade engineering, launch systems, and AI integration.