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AI Generated Code Audit and Cleanup

n8n, Make.com and Zapier automation with AI steps and a human approval check — fixed price, documented on handover.

What Does an AI Code Audit Cover?

An AI generated code audit is an independent read of a codebase an AI coding tool wrote, before you ship it or hand it to a buyer. EICRA reads the repository at a commit you name, records every structural, security and reliability issue with the file it lives in, reproduces each one, and returns the findings to your developers in fix order.

Audited on your own repository, at a commit you name
Read by an engineer, not a scanner report alone
Every finding reproduced before it reaches the report
Findings and scripts handed over to your own team
Request a code audit Send one repository
Read-only 01 Access · your repository, your keys
Findings 02 Each issue named with its file path
Reproduction 03 Steps that make the failure repeat
Fix order 04 Ranked by risk, not a flat list
Handover 05 Report, scripts and the fix order

Which Code Audit Services Do We Run?

EICRA runs six code audit services: codebase structure, security and secrets, dependency and supply chain, test coverage, production readiness, and remediation of what you approve. Each one answers a different question about the repository, and each can be bought on its own or combined into a single pass over one branch. The first five produce findings. Only the sixth changes your code, and only after you have read the findings and said which ones to act on.

Codebase Structure Audit

You learn where the repository will resist change. We map how a request travels from entry point to data, then name the duplicated logic, the dead paths, the files that do too much, and the abstractions an AI tool invented and never reused. Each one is recorded with the file it lives in.

Security and Secrets Review

You learn what a stranger could reach. We look for credentials committed to the repository, routes that serve data without an authorisation check, database rules left open to anonymous callers, and input that reaches a query unescaped. Findings are grouped by what an attacker would have to do first.

Dependency and Supply Chain Check

You learn what your application inherits. We read the lockfile, name packages that are unpinned, abandoned or duplicated at conflicting versions, and flag any that an AI tool added for a single call. Where a package carries a known advisory, the advisory is named alongside the file that imports it.

Test Coverage Assessment

You learn what is untested and what that costs you. We record which paths have no test at all, which tests assert nothing useful, and which of the untested paths touch money, personal data or authentication. The output is a ranked list of the tests worth writing first, not a coverage percentage.

Production Readiness Review

You learn what happens when something breaks at two in the morning. We check error handling, logging, configuration and secrets separation between environments, the rollback path, and whether a failed deploy leaves the application in a state anyone can diagnose. Gaps are named with the change that closes them.

Remediation and Cleanup

You get the approved findings fixed. Each change is tied to a numbered finding from the audit report, kept in its own commit, and verified against the reproduction script that demonstrated the problem. Nothing is refactored because it offended us. Scope is agreed in writing after you have read the findings.

Not included: rebuilding the product or changing what it does · redesigning the architecture inside an audit · certification or conformity assessment, because EICRA is not a certification body · third-party scanning licences, paid by you to the vendor.

How Does AI Generated Code Fail?

AI coding tools write code that runs, and that is exactly why the gaps survive to production: the application works, so nobody looks. The failures below are the ones that reach a launch or a security review, and each maps to a check in the audit. The security categories follow the OWASP Top 10, so a finding can be matched against the list your reviewer already uses.

  • Credentials and API keys committed into the repository
  • Routes that return data with no authorisation check
  • Database rules left open to anonymous callers
  • Paths that work only because one record happens to exist

Failure Types Mapped to Audit Checks

Failure type What it looks like Audit check
Exposed secrets A live key sitting in the repository history History sweep across every branch and commit
Broken access control An endpoint that trusts whatever the client sends Entry point read against the data it can reach
Open data rules A table readable by any anonymous caller Policy read against the queries that use it
Untested critical path Payment or login code no test ever exercises Path list ranked by what the failure would cost
Silent failure An error swallowed, so nothing is logged Error handling read from throw site to log sink

What Happens After You Send a Repo?

An audit moves through five stages, and you decide at the end of each one whether to continue. No code is read before the confidentiality terms are signed, and no finding reaches the report before it has been reproduced from a clean checkout. You keep every artefact produced along the way, whether or not you continue to the next stage.

Start at 01 if the application is live. Start at 02 if it is still in build.

Five Stages From Repo to Report

Stage You give us You get Decide at the end
01 Scope The repository, branch and commit A written scope and an audit plan Grant access, or stop
02 Access Read-only credentials for named reviewers Signed confidentiality and data terms Begin the sweep, or stop
03 Sweep Nothing new A narrowed surface of flagged code Approve the read, or revise scope
04 Read and reproduce One person who can answer intent questions Findings read in context and reproduced Receive the report, or extend
05 Handover Nothing new Report, reproduction scripts and fix order Fix it yourself, or scope remediation

Repeat Audits After Every AI Sprint

An audit describes one commit. The next sprint of AI generated pull requests can undo it, which is why the reproduction scripts are yours to re-run rather than ours to rent back to you. Industry research from DORA links faster AI assisted delivery with less stable releases, and the control that closes that gap is review that keeps pace with the code. For the build side of the same work, see our AI services; for checking what an AI system outputs rather than how it was written, see AI model testing.

Repositories Web apps, APIs, mobile, scripts
Access Read-only, in your environment
Contracts NDA and DPA before any access
Handover Report, scripts, fix order

Why Choose EICRA for Your Code Audit?

Five reasons, and each one is something you can check rather than a claim you have to trust. An engineer reads every flagged file, not a scanner alone. The reproduction scripts are yours at the end, so the work is never bought twice. We audit repositories we did not write. Scope starts at one repository, not a full due diligence. And every report names the parts of the codebase it did not read. Open a tab for the detail behind each.

Reason one

An Engineer Reads Every Finding

A scanner tells you a pattern matched. It cannot tell you the query is safe here and unsafe two files away, or that a route works today only because one record happens to exist. On every audit a senior engineer reads the flagged code in its own context before it reaches the report. Tools do the sweeping. The judgement stays human.

Every flag read in context
Scanner noise dropped, not forwarded
False positives removed by hand
Two reviewers on critical findings
Tools sweep, people judge
Disagreements logged, not buried
Reason two

The Findings Stay With You

Most vendors keep the tooling, so your next release means buying the same sweep again. We hand over the findings report, the reproduction scripts and the fix order at close. Your own developers can re-run the checks after any AI generated pull request, with us or without us. It is the one decision that stops this becoming a subscription.

Reproduction scripts handed over
Fix order included, not summarised
Re-run the checks without calling us
No licence, no lock in
Repeat audits cost less
Capability stays in your team
Reason three

We Audit What We Did Not Build

A builder marking its own work has an interest in a clean result, and an investor or enterprise reviewer spots that before reading a single finding. EICRA audits repositories built by your team, by an AI coding tool or by another vendor. Where we did build the thing, the report says so on its first page and calls itself internal review rather than independent audit.

Audited by people who did not build
Stated in the report either way
Survives a due diligence question
Internal review labelled as such
No stake in a clean result
Findings reported whoever wrote them
Reason four

Scoped to One Repository

A full engineering due diligence is the right shape for an acquisition and the wrong shape for a founder who needs to know whether one app is safe to launch. An audit here starts at one repository and one branch, and you can stop when it ends. Nothing is bundled that you did not ask for.

Start with one repository
Fixed scope agreed in writing
Scoping conversation costs nothing
No minimum retainer
Stop after any stage
Remediation is a separate decision
Reason five

Every Report Names What It Missed

Every report names what the audit did not cover: paths nobody exercised, branches not read, behaviour it cannot promise. That paragraph is what makes the rest believable. A reviewer who finds no limits section assumes something was hidden, and a finding you cannot defend in a meeting is worth nothing to the person holding it.

Not covered section in every report
Commit and branch named exactly
No promise on unread paths
Limits written before findings
Defensible in a review meeting
What we cannot do, said early
Human1Yours2Independent3One Repo4Limits5Why ChooseEICRA
Where we are not the answer: if you need a signed certificate rather than evidence, a certification body or a large assurance firm is the honest route and we will say so on the first call. If the decision is really whether to rebuild from scratch, an audit will tell you that but will not do the rebuild. EICRA is a small team working remotely from Bangladesh, we hold no certification we have not been awarded, and we have no client case studies to publish yet. What we can show you is the method and a scoped audit plan for your own repository.

Proof You See Before You Pay

We publish method rather than promises: a written audit plan from the first conversation, findings drawn from your own repository, and every issue traceable to a reproduction script anyone on your team can run. Nothing in a report rests on our word alone, because a finding you cannot reproduce is a finding you cannot act on. Client case studies will be added here as engagements complete, with each client permission.

Your repo Findings come from the repository and commit you name, not from a general list of things that go wrong with AI code. Included in every audit
Every finding Named with the file it lives in and the steps that make it repeat from a clean checkout, so your developer can verify before fixing. Included in every audit
Three files Findings report, reproduction scripts and the fix order, handed over at close so your own engineers can re-run the checks. Included in every engagement
Send one repository Tell us what the application does and which AI tool built it. You get a written note on what an audit of it would cover and what it would not tell you, whether or not you hire us.

Send one repository

Is It Safe to Share Your Repository?

Your source code stays where it already is. Reviewers work with read-only credentials you issue and can revoke, inside the environment you nominate, and no copy is retained after handover. The sensitive artefact in a code audit is not the application, it is the repository history, because commits, environment files and logs routinely hold live credentials and real customer records. That is where the controls sit, and it is why the processor terms required by Article 28(3) of Regulation (EU) 2016/679 are signed before anyone reads a line.

Contracts and access

What do we sign before access?

NDA mutual, signed before the repository, its history or its logs are opened.
DPA processor terms wherever personal data appears in the code, fixtures or logs.
Transfers the transfer agreement your own regulator requires, signed before personal data moves.
Certifications we hold none we have not been awarded, which is why the controls above are contractual rather than badge based.
Handling during an audit

Where does your source code sit?

Location Reviewers work in the environment you nominate, using credentials you control and can revoke.
Minimisation Fixtures and sample records can be masked or synthesised where real data must not be read.
Retention Any local checkout, scan output and note is kept for the period in the engagement letter, then deleted on confirmation.
Access Read-only rights, named reviewers only, and our credentials revoked by you at handover.

Six Signs Your Codebase Needs an Audit

Most founders do not go looking for a code audit. They run into one of these six situations and then start looking. Find the row that sounds like your week, and the last column names the service that answers it, so you can start there rather than buying a full engineering due diligence you do not need yet.

Signs and the Right Starting Point

No. The sign Where to start
01 The app works but nobody dares change it Codebase structure audit
02 An investor or enterprise buyer asked for a review Security and secrets review
03 A developer quit after one week in the codebase Codebase structure audit
04 Every new feature breaks something unrelated Test coverage assessment
05 You are about to open the app to real users Production readiness review
06 Your AI tool added packages nobody has reviewed Dependency and supply chain check
None of these yet? Then you probably do not need us this quarter. The cheapest useful step is to run your own repository through a secrets scanner and read what it finds, because that is the one class of problem where a single miss is enough to matter.

Code Audit Questions Buyers Ask

Ten questions founders and engineering leads ask before they hand over a repository, answered without hedging. Where the honest answer is no, it says no.

What is an AI generated code audit?

An AI generated code audit is an independent read of a codebase written wholly or partly by an AI coding tool. An engineer reads the repository at a commit you name, records each structural, security and reliability issue with the file and line it lives in, reproduces it, and returns the findings in fix order. It is a review, not a rewrite.

Is AI generated code safe for production?

It depends on what nobody has checked yet. AI coding tools produce code that runs, and the common gaps are the ones no test exercises: secrets committed to the repository, routes with no authorisation check, database rules left open, and dependencies nobody pinned. An audit finds which of those are present in your repository rather than in the general case.

How do you audit an unknown codebase?

We start from the entry points rather than the file tree: how a request enters, how it reaches data, and what stands between the two. Automated sweeps run first to narrow the surface, then an engineer reads the code the sweep flagged, in context. Nothing enters the report until it has been reproduced from a clean checkout.

What do you need from us?

Four things, in this order:

1. Read-only access to the repository, at a branch and commit you name.
2. A short note on what the application does and who uses it.
3. Any environment the app needs to run, or permission to run it locally.
4. The name of one person on your side who can answer questions about intent.

Can you audit a Lovable build?

Yes, and also builds from Cursor, Replit, Bolt, v0, Claude Code and GitHub Copilot. The audit is tool agnostic because it reads the code that was produced rather than the prompts that produced it. What changes between tools is where the common gaps sit, and the report names which tool patterns it found.

Who owns code that an AI wrote?

Ownership sits with you under the terms of the tool you used, and the audit does not change that. What an audit can surface is code in your repository that appears to originate from a third party licence, so your own counsel can decide what to do about it. We report what we find and do not give a legal opinion.

Do you keep a copy of our repository?

No copy is retained after handover. Work happens in the environment you nominate wherever possible, with read-only credentials for named reviewers. Where a local checkout is needed, it is deleted on your confirmation at close, and the engagement letter names the retention period in writing before any access is granted.

Can you work alongside our developers?

Yes, and that is the usual shape. Your developers keep ownership of the codebase and make the changes. We hand findings over with reproduction steps so a fix can be verified rather than assumed. Where you would rather we implement the fixes, remediation is scoped and agreed separately after you have read the findings.

What is inside the audit report?

Three files. The findings report names each issue, the file and line it sits in, why it matters and where it sits in fix order. The reproduction scripts make each finding repeat from a clean checkout. The scope note names the commit, the branch and, in its own section, what the audit did not cover.

What will you not fix?

We do not rewrite your product, change what it does, or redesign the architecture inside an audit. We do not certify anything, because EICRA is not a certification body. And we do not promise behaviour on paths nobody exercised, which is why every report names the parts of the repository it did not read.

Reviewed by Mohammed Nazrul Islam
Tell us which repository, which branch and what the application does. You get a written scope and an audit plan back before anything is agreed.
Request a code audit Send one repository