Audit AI-generated apps before launch
An AI coding agent can ship a working app in an afternoon, and it can also ship a missing security header, a leaked API key, and a checkout flow that errors on the second click. To audit an AI-generated app, point AuditWard at the deployed URL. One pass QA-tests the real browser flows and security-scans the target, then returns triaged findings.
What AI builders tend to skip.
Code generated by an LLM compiles and demos well, but it rarely gets the boring security and edge-case work right. The model optimizes for the happy path it was prompted with. A security check for an AI-built app catches the parts no one reviewed: response headers, transport settings, exposed files, and the flows that only break when a real user clicks through them.
AuditWard runs the same audit a human would start with. It drives the live site in a real Chromium browser and probes the host with pentest tooling, so you find the gaps before your users do. The point is to launch with eyes open, not to assume the agent handled it.
From deployed URL to a report, step by step.
You give AuditWard the URL of the deployed app and any context that helps, such as "this is a checkout flow, here is a test login". From there the pipeline runs on its own. Five stages take you from a bare URL to a triaged, compliance-tagged report you can hand to whoever owns the fix.
Point it at the deployed URL
Paste the public URL of the app your agent shipped, whether that is a preview deployment or production. Add a sentence or two of instructions if you want the run to focus on a signup flow, a purchase path, or a specific page. You start it from the dashboard or, on Starter and above, with one qa_test call over MCP from your coding agent.
The Planner builds a checklist
An LLM Planner reads the URL and your instructions and writes a test checklist for this specific app. It maps the flows worth exercising, like registration, login, and form submission, and queues the security checks the host calls for. You can watch the checklist fill in on the live dashboard.
The Explorer drives the browser
An Explorer agent works through the checklist in a real Chromium browser. It clicks buttons, fills forms, and follows links the way a person would, taking screenshots as it goes. If the app sits behind a login, the scan pauses and asks for credentials, which you provide in the dashboard or with qa_provide_context. Answers are KMS-encrypted.
Security tools probe the target
In the same run, real pentest tooling examines the host. curl and testssl.sh inspect headers and TLS, Nuclei runs templated vulnerability checks, Nmap and WhatWeb enumerate ports and the tech stack, Gobuster looks for exposed paths, and nslookup checks DNS. This is the half an AI builder almost never produces on its own.
The Analyst returns triaged findings
An Analyst agent turns the raw evidence into findings. Each one is triaged, given a confidence score, tagged to the frameworks it touches (PCI DSS 4.0, SOC 2, GDPR, OWASP Top 10, HIPAA, ISO 27001), and backed by an annotated screenshot or tool output. You read them in the dashboard and export a pentest-style PDF, or pull the report with qa_report. On the free Basic plan the first three findings per scan are visible.
Findings that show up in AI-generated apps.
These are the issues an audit of an AI-built app surfaces most often. The two columns split them by source: the security tooling that probes the host, and the browser session that exercises the app like a user. None of this is exotic. It is the work the generator skipped.
| Finding type | What it looks like in an AI-built app | Found by |
|---|---|---|
| Missing security headers | No Content-Security-Policy, missing HSTS, or absent X-Frame-Options on the deployed app, because the boilerplate never set them. | curl, Nuclei |
| Weak TLS configuration | Outdated protocol versions or weak ciphers on a custom domain that was wired up by hand after the agent finished. | testssl.sh |
| Exposed files and paths | A readable .env, a source map, a stray .git directory, or an admin route shipped to production by accident. | Gobuster, curl |
| Leaked secrets in responses | An API key or token hardcoded into the client bundle, where the model put it to make a call work. | Explorer agent, Nuclei |
| Weak cookie flags and CORS | Session cookies without Secure or HttpOnly, or a permissive CORS policy left wide for local testing. | curl, Nuclei |
| Broken user flows | A signup form that submits to nothing, a checkout that 500s on retry, or a button wired to a route that does not exist. | Explorer agent |
| Placeholder and stub content | Lorem ipsum left in the footer, dead links, fake testimonials, or a "Coming soon" page the generator forgot to replace. | Explorer agent |
| Outdated or fingerprinted components | A known-vulnerable library version or a framework banner the stack leaks, pinned by the model from stale training data. | WhatWeb, Nmap, Nuclei |
Where this audit stops.
AuditWard finds and evidences issues fast, and it is genuinely useful before a launch. It is not a certified penetration test and it does not replace one. It tests the running app from the outside, so anything that needs source review or deep manual testing is out of scope. Read these limits before you treat a clean scan as a sign-off.
Not a manual pentest
AuditWard complements a manual penetration test, it does not stand in for one. For a high-stakes or regulated launch you still want a human pentester. AuditWard clears the obvious issues first so that engagement spends its time on the hard ones.
Tags are an aid, not a certificate
Framework tags are attached per finding to help you triage. They support your SOC 2, PCI, or GDPR work. They do not make the app compliant, and AuditWard is not a PCI Approved Scanning Vendor.
No destructive testing
The scanner respects rate limits and robots.txt, runs no denial-of-service tests, and reports takeover weaknesses without exploiting them. You scan only domains you are authorized to test, verified by DNS TXT record.
Outside-in, on the deployed app
AuditWard tests the live URL, not your repository. It sees what is actually exposed, which is the point for an AI-built app, but it does not read the source or trace business logic the browser cannot reach.
Related reading.
For the full detail on what AuditWard probes and how findings are triaged, read the website security scanning pillar. If your app came out of a builder like Lovable, v0, or Bolt, the Lovable, v0, and Bolt apps page is more specific. To see how a pre-launch scan supports a framework you care about, read the OWASP Top 10 page, or head back to the use cases overview.
Questions about auditing AI-built apps.
What do I need to audit an AI-generated app?
Just the deployed URL of an app you are authorized to test. Paste it into the dashboard, add optional instructions, and the scan runs. You do not need to upload code or install anything. If the app sits behind a login, you supply credentials when the scan pauses to ask.
Does AuditWard read my source code?
No. It tests the running app from the outside, the way an attacker or a real user would reach it. That is what surfaces the exposures an AI builder leaves in a deployment. For source-level review you would use a different kind of tool alongside it.
Is one scan enough before launch?
It is a strong first pass that clears the common gaps AI generators miss, with evidence and remediation steps. It is not a certified penetration test and does not replace one. For a regulated or high-stakes launch, run AuditWard first, then bring in a human pentester for the deeper work.
Can I run this from my coding agent?
Yes, on Starter and above. AuditWard ships an MCP server, so your agent can start a scan with qa_test, check progress with qa_status, answer login questions with qa_provide_context, and pull the PDF with qa_report, all without leaving the agent.
Will it test a flow behind a login?
Yes. When the scan reaches a login wall it pauses and asks for credentials with structured questions. You answer in the dashboard or over MCP and the scan resumes into the authenticated parts of the app. Your answers are KMS-encrypted before storage. This is available on Starter and above.