Security and privacy
Auth, permissions, secrets, client/server trust boundaries, data exposure, and dependency risk.
For founders shipping AI-built software
Get a practical technical review before customers, investors, or production traffic find the weak spots. vibeCleaners identifies fragile code, security gaps, scaling risks, and the fixes that matter first.
The problem
Generated software often passes the demo path while hiding weak auth boundaries, missing validation, brittle deployment setup, duplicated business rules, and unclear data risk. The review gives you a clear fix order before launch pressure makes every decision more expensive.
What gets reviewed
Auth, permissions, secrets, client/server trust boundaries, data exposure, and dependency risk.
Validation, schema design, migrations, critical writes, business rules, and edge cases.
Generated code sprawl, module boundaries, duplicated logic, coupling, and maintainability.
Expensive queries, background work, caching, bottlenecks, and paths from MVP to real usage.
Environment setup, deploys, rollbacks, logs, error monitoring, CI, and production readiness.
Critical user flows, launch blockers, user-visible failure modes, and what can safely wait.
Packages
Best first step
$500
Risk-ranked findings, evidence, launch blocker list, improvement roadmap, and async email follow-up.
Request reviewFirst 2 customers
$250
A discounted launch readiness review in exchange for permission to use an anonymized testimonial or case study.
Ask about pilotFollow-on work
$1,200+
Implementation support for the highest-priority findings: tests, hardening, refactors, deployment, or scaling work.
Scope a sprintPrices are starting points, not the final number. After a quick look at the app's size and stack, you get a fixed quote confirmed in writing before any payment — no open-ended billing, no surprises.
Deliverable
The report separates confirmed risks from assumptions, explains customer impact, and turns findings into a roadmap for launch, the next 30 days, and later scaling.
View sample reportProcess
Share the app, repo access, goals, stack, deadlines, and known concerns.
I inspect critical flows, code structure, security boundaries, data, deployment, and operations.
You receive prioritized findings with evidence, impact, effort, confidence, and recommended fixes.
If useful, the highest-priority findings become a focused implementation sprint.
Who reviews this
About the reviewer
I've spent roughly 15 years building and operating production software — most recently designing real-time data systems that move 200TB+ at sub-millisecond latency, and as a senior infrastructure engineer hardening Kubernetes platforms, CI/CD, and observability. Earlier I was Lead DevOps at NowSecure, a mobile app-security company, and have implemented the OAuth2/OIDC auth systems that apps most often get wrong.
The review is the same pass I'd run on my own code before handing it to real users: where the trust boundaries leak, what falls over under load, and what's quietly unmaintainable. I write about exactly this — the gap between "it works" and "it's ready" — at blog.argakiig.xyz.
Access is scoped to the minimum needed — read-only repo access or a shared snapshot. No write access, no production credentials.
Your code is used only to perform your review. It is not shared, published, or reused. Access is revoked once the report is delivered.
Happy to sign your NDA before you share anything, or use a mutual one. Just say so in the request and we sort it before access.
Writing
The demo is the easy 80%. Where AI-built apps actually break before launch — and why it becomes a trust problem, not a code problem.
AI made obvious bugs rare and expensive ones invisible. Review moved up the stack, from implementation to judgment.
The five-step triage I actually work through, hardest-hitting risk first, when I review an AI-built app.
FAQ
A practical technical review before real users rely on the app. You get risk-ranked findings, evidence, launch blockers, and a prioritized fix roadmap.
It includes security and privacy review, but it is not a formal penetration test or compliance certification.
No. The default flow is async: request form, email clarification, scope confirmation, review, and written report.
Apps built with AI-assisted tools like Cursor, Lovable, Bolt, Replit, Claude, ChatGPT, or similar workflows are a strong fit.
A written report covering security, data, architecture, operations, scalability, maintainability, launch blockers, and what to fix first.
Yes. If the review identifies high-priority fixes, those can become a separate stabilization sprint.
Request a review
This form is intentionally short. After you send it, the next step is confirming scope, access, timing, and whether a launch review or stabilization sprint is the right fit by email.
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