How much does an AI codebase audit cost?

Fixed-price from $2,499. The figure depends on the size and complexity of the codebase and is agreed in writing before we start, so the audit itself never runs over.

How long does the audit take?

Most audits are delivered within one to two weeks of getting access, depending on the size of the codebase. You get a firm timeline in the written scope before any work begins.

Do you need access to our source code?

Yes — this is the inside-out read, so we work from the repository under a signed agreement. If you want the outside-in view with no source access, that's the external exposure report instead, and the two pair well.

What if you find serious problems?

You get them ranked by severity with a concrete remediation step for each. You can hand the report to your own team or have us carry out the fixes on a follow-on engagement or a care retainer — your call.

Which AI coding tools do you audit code from?

All of them — the audit reads the code, not the tool that wrote it. Cursor, Copilot, Claude, Lovable, Bolt, Replit, hand-written, or any mix. What matters is what shipped.

Fixed-price auditSoftware Development

AI-built codebase rescue & audit

You shipped fast with an AI coding tool and now the app runs the business. We read every line: a fixed-price audit of security, auth, dependencies, and secrets.

Book a codebase audit Software Development

AI coding tools are extraordinary at getting an app to work. They are far less reliable at getting it right. The gap between the two is where businesses get hurt: an application that demos perfectly, ships in a weekend, quietly starts running real operations and real customer data — and that nobody has actually read end to end.

This is a fixed-price, written audit of an AI-generated or vibe-coded codebase. We read every line the way an attacker and a maintainer both would, and hand you a report you can act on: what is exposed, what is fragile, what to fix first, and what it will take.

From $2,499 · fixed-price audit

Why AI-generated code needs a second read

A coding assistant optimizes for the thing you asked for — a working feature — not for the things you didn't think to ask about: whether the endpoint checks who is calling it, whether the database row is protected when the API is hit directly, whether a secret ended up in the frontend bundle, whether a dependency it pulled in has a known vulnerability. Those omissions are invisible in a demo and expensive in production.

The pattern we see repeatedly: an app that grew feature by feature through prompts, with no single person holding the whole picture, no consistent authorization model, and a dependency tree nobody has audited. It runs. It also has holes a stranger can find from the outside in an afternoon.

What the audit covers

Security posture: authentication and access-control coverage across every route and mutation, session handling, and whether server-side authorization is actually enforced or just assumed by the UI. Data protection: how customer data is stored, whether row-level security or its equivalent is real, and where personally identifiable information flows.

Supply chain and secrets: every dependency checked against known-vulnerability databases and pinned-version hygiene, plus a sweep for API keys, tokens, and credentials committed to the repository or shipped to the browser. And a prioritized map of the technical debt underneath — the shortcuts the assistant took that will cost you the most as the app grows.

What you receive

A written report, structured for action rather than for show: findings ranked by severity and exploitability, each with a plain-language explanation of the risk and a concrete remediation step. Not a scanner dump — a senior engineer's read, with the false positives already removed and the real issues explained in terms your team can act on.

The audit is inside-out: we have the source. Its natural counterpart is the external exposure report, which assesses the same app outside-in, as a stranger on the public internet sees it. Many clients run both.

Fix it yourself, or have us do it

The report is yours to hand to your own team. If you would rather we carry out the remediation, we scope that as a follow-on engagement or fold the codebase into a care retainer — the same senior engineers who read it do the fixing, so nothing is lost in translation.

Either way there is no lock-in and no theatre. The deliverable is a clear picture of what you actually shipped and a defensible plan for making it safe to keep running.

FAQ

Common questions.

How much does an AI codebase audit cost?: Fixed-price from $2,499. The figure depends on the size and complexity of the codebase and is agreed in writing before we start, so the audit itself never runs over.
How long does the audit take?: Most audits are delivered within one to two weeks of getting access, depending on the size of the codebase. You get a firm timeline in the written scope before any work begins.
Do you need access to our source code?: Yes — this is the inside-out read, so we work from the repository under a signed agreement. If you want the outside-in view with no source access, that's the external exposure report instead, and the two pair well.
What if you find serious problems?: You get them ranked by severity with a concrete remediation step for each. You can hand the report to your own team or have us carry out the fixes on a follow-on engagement or a care retainer — your call.
Which AI coding tools do you audit code from?: All of them — the audit reads the code, not the tool that wrote it. Cursor, Copilot, Claude, Lovable, Bolt, Replit, hand-written, or any mix. What matters is what shipped.

Book a codebase auditAll software development

External exposure report — black-box security testThe exact assessment an outside attacker would run against your live site — no source code, no credentials. We map what you expose before someone else does.