Sample AI Code Rescue Audit Report
A sample AI Code Rescue audit report showing how Aatvi ranks launch blockers, important fixes, cleanup work, and rescue-vs-rewrite recommendations.
This is a sample report format for an AI-generated app audit. It is not a report on a real customer system. It shows the level of specificity a founder, CTO, investor, or product owner should expect before trusting an AI-built app with customers.
The point of the audit is not to shame AI-assisted development. The point is to separate a fast prototype from a production system.
Executive verdict
The sample app is not launch-ready. It can likely be rescued without a full rewrite, but the team should fix authorization, secrets, database rules, error handling, and deployment controls before onboarding real customers.
Recommended path: two-week rescue sprint, followed by a smaller hardening sprint after customer beta.
App context
Product: B2B workflow SaaS generated with an AI coding assistant.
Stack: Next.js frontend, serverless API routes, managed Postgres, hosted authentication, Stripe subscriptions, email notifications, analytics, and a basic admin dashboard.
Current stage: demo complete, first beta customers waiting, no security review yet.
Audit goal: decide whether to launch, rescue, or rewrite.
Summary by severity
Launch blockers:
- Tenant data can be accessed by changing an account ID in an API request.
- Admin routes are hidden in the UI but not enforced on the server.
- A production API key appears in the repository history.
- Subscription state is trusted from client-side data.
- Database migration state differs between local, preview, and production.
Important fixes:
- Tests cover rendering but not core workflows.
- Webhook handler does not verify signatures.
- Error reporting captures full request payloads.
- Rate limits are missing on auth-adjacent forms.
- File upload path does not enforce type and size consistently.
Cleanup:
- Three generated data-access patterns exist for the same tables.
- Several components include duplicated validation logic.
- Dead demo routes remain crawlable.
- README does not document setup, environment variables, or deployment.
Finding 1: Cross-tenant data access
Severity: launch blocker.
The API accepts an accountId parameter from the request body and uses it directly in database queries. A logged-in user can change that value and read another account's records.
Why this matters: this is the kind of vulnerability that turns a beta into a breach. It is also common in generated SaaS code because demos usually test with a single account.
Recommended fix:
- Derive account membership from the authenticated server session.
- Enforce account access in a shared server-side helper.
- Add integration tests for same-account access, cross-account denial, deleted users, and role changes.
- Review every route that reads or writes account-scoped data.
Evidence needed before close:
- Failing test that reproduces the cross-account read.
- Passing test after the fix.
- Manual request showing direct API calls cannot bypass the UI.
Finding 2: Admin authorization exists only in navigation
Severity: launch blocker.
The admin link is hidden for non-admin users, but the underlying route and API handlers do not enforce the admin role.
Why this matters: UI hiding is not authorization. Anyone who discovers the route can call it directly.
Recommended fix:
- Add server-side role enforcement to every admin page and API route.
- Centralize role checks instead of repeating inline conditions.
- Add tests for non-admin, admin, expired session, and deleted admin user cases.
Finding 3: Production secret in repository history
Severity: launch blocker.
A payment provider key was committed during prototype development. Removing it from the latest file is not sufficient because the value remains in Git history.
Why this matters: secrets pasted into prompts, commits, screenshots, logs, or tickets should be treated as compromised.
Recommended fix:
- Revoke and rotate the exposed secret.
- Search the repository, logs, deployment settings, and prompt exports for related credentials.
- Move secrets to environment-specific configuration.
- Document who can access production secrets.
Finding 4: Webhook handler does not verify signatures
Severity: important.
The subscription webhook accepts JSON and updates account status without verifying that the provider signed the request.
Why this matters: forged webhook requests can unlock paid features, close accounts, or corrupt billing state.
Recommended fix:
- Verify the webhook signature using the provider's SDK.
- Store webhook event IDs to prevent replay.
- Add tests for valid signature, invalid signature, replay, and unknown event type.
Finding 5: Error reporting captures sensitive request data
Severity: important.
The error reporting setup sends full request bodies and headers for failed API calls.
Why this matters: logs often become an accidental data store. They should not contain passwords, tokens, private documents, payment data, or customer records.
Recommended fix:
- Add allowlisted structured logging.
- Redact authorization headers, cookies, tokens, passwords, payment fields, and uploaded content.
- Set retention policies for logs and error events.
- Add a test or smoke check for redaction.
Rescue-vs-rewrite recommendation
Rescue is appropriate when the core product idea is clear, the codebase builds reliably, the data model is understandable, and the riskiest gaps are concentrated in auth, data access, configuration, and tests.
Rewrite is appropriate when the product rules are unclear, generated code is tangled across every layer, the database model is wrong for the business, or nobody can safely change the app without causing regressions.
For this sample, rescue wins. The architecture is imperfect but recoverable. The team should avoid feature work until the launch blockers are closed.
Proposed rescue sprint
Week 1:
- Lock down tenant authorization.
- Rotate secrets and clean environment setup.
- Fix admin server checks.
- Verify webhooks.
- Add regression tests for every launch blocker.
Week 2:
- Normalize database migrations.
- Add observability and redaction.
- Add deployment and rollback documentation.
- Remove dead demo routes.
- Run a final production-readiness pass.
Post-beta:
- Consolidate duplicated data-access patterns.
- Improve component boundaries.
- Add deeper product analytics.
- Expand end-to-end coverage around paid workflows.
What the customer should receive
- Ranked findings with evidence.
- Clear launch/no-launch verdict.
- Rescue-vs-rewrite recommendation.
- Fixed-scope remediation plan.
- Test and verification requirements.
- Residual-risk list for post-launch tracking.
An audit without a decision is just a long note. A useful audit tells the team exactly what blocks launch and what can wait.
When Aatvi helps
Aatvi's AI Code Rescue service produces this kind of ranked audit and, when useful, implements the rescue sprint. If the app needs deeper product rebuilding, pair it with AI product development.
Source notes
- Veracode reports that AI-generated code introduced risky security flaws in 45% of tests.
- OWASP's LLM Top 10 includes prompt injection, insecure output handling, supply-chain vulnerabilities, sensitive information disclosure, excessive agency, and overreliance.
- TechTarget warns that AI coding tools produce what they are asked for; if security practices are missing from the prompt, generated code may omit them.
- Several adjacent offers in the AI-app remediation space emphasize speed of turnaround. The durable advantage in this category is evidence-backed engineering judgment, not turnaround time.