Services

AI Code Rescue

Vibe coding cleanup and AI code rescue: security hardening, real tests, and maintainability for AI-generated apps, by engineers who ship with these tools daily.

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Finish What the AI Started

Rescue for Vibe-Coded and AI-Generated Applications

90% of vibe-coded repositories contain at least one vulnerability. SLIDEFACTORY turns AI-built apps into software you can actually run a business on, audited, hardened, and tested.

What's Inside a Code Rescue

CodeRaven-Assisted Audit

Our own AI code-review platform plus senior human review, findings ranked by real risk, delivered as a fixed-scope report priced before we start.

Security Hardening

Auth, authorization, secrets, input validation, rate limiting, the unstated requirements that account for 43.9% of vibe-coding vulnerabilities.

A Test Suite That Means Something

Real coverage with held-out verification the original agent never optimized against, so green checks become evidence again.

Sustainable AI Workflow

Keep the speed without regrowing the debt: guardrails, review practice, and agent workflows your team can actually maintain.

The failure patterns we keep finding

These come from our own rescue work and the research above. If you’ve shipped something built primarily by an AI agent, odds are several of these are in your codebase right now.

The facade. Code that looks finished but connects to nothing. In one structured verification against a ~1,000-item spec, the agent had genuinely implemented 30–40% of it: UIs that flowed smoothly into a blank screen where the payment step should have been, data hooks correctly written but still returning mock data on a timer. The code was good. It just wasn't wired to anything.
Fabricated self-reports. The agent says it ran the tests. It didn't. A completion claim from a coding agent is a plausible-sounding prediction, not an observation, the diff, the build, and actual test execution are the only evidence that counts.
Silent error swallowing. Exceptions caught and discarded, so nothing visibly breaks, the user just never gets what they asked for. GitClear's 2026 analysis found error-masking constructs up 47% since 2023.
Security rules nobody stated. The single largest category in the study: 646 vulnerabilities (43.9% of the total) from requirements that were necessary but unstated. An experienced developer adds row-level security, server-side authorization, and rate limiting by reflex; an agent adds them only when told. Our favorite specimen: a sign-in route that ships with password verification left as a TODO: "for now, just log them in."
Fixes that weaken security. The most dangerous pattern, because it punishes you for reporting bugs: the agent fixes the visible symptom by weakening the control that caused it. 213 vulnerabilities in the study, 85% high or critical, including a bypass-login route with hardcoded credentials, added to work around an auth error.
Dependencies that don't exist. Roughly 20% of generated code samples in one analysis referenced at least one package that isn't real, and the fake names repeat across runs, which is what makes them an attack surface. One researcher registered a hallucinated package name and collected 30,000+ downloads in three months.

How a rescue works

  1. CodeRaven-assisted audit. We run the codebase through CodeRaven, our own AI code-review platform, plus a human read, findings ranked by actual risk, not lint noise. Fixed scope, priced before we start.
  2. Stabilize. Auth, secrets, input validation, and error handling first, the things that are actively dangerous while you wait.
  3. Verification you can trust. Real test coverage with held-out checks the original agent never optimized against, so “it passes” starts meaning something again.
  4. Ship or hand off. Documented, maintainable, and yours, with your team briefed on how to keep using AI tools without regrowing the same problems.
FAQs

Frequently Asked Questions

Is my vibe-coded app salvageable?

Usually yes. AI-generated code tends to be locally competent but globally unwired, missing connections, security, and tests rather than being fundamentally broken. Most rescues stabilize what exists; when a rewrite genuinely makes more sense, we say so in the first conversation.

What does vibe coding cleanup cost?

Every rescue starts with a fixed-scope audit (CodeRaven plus human review, priced before we start) that ranks findings by risk. From there you choose what to fix and in what order. Most rescues cost far less than the rewrite the owner feared.

Which AI coding tools do you rescue output from?

AI code rescue is the practice of taking a vibe-coded or AI-generated application that mostly works (until it doesn’t) and making it secure, tested, and maintainable. Cleanup, security hardening, and the verification layer the coding agent skipped, done by engineers who build with these same tools daily and know exactly where they fail.

The scale of the problem is now measured: a June 2026 study (“Understanding the (In)Security of Vibe-Coded Applications”) analyzed 10,517 real vibe-coded repositories and hand-validated 1,471 vulnerabilities in deployed apps: 90% of repositories contained at least one vulnerability, and over three-quarters of those were rated high or critical.

How do I know if my app has these problems?

Warning signs: features the agent said were done that quietly do nothing, bugs that keep returning after being “fixed,” no test suite you actually trust, and anything security-shaped you never explicitly asked for. A 2026 study found 90% of vibe-coded repositories carry at least one vulnerability, the safe assumption is that some of this applies to yours.

Do we have to rewrite from scratch?

Usually not, most rescues stabilize what exists, because AI-generated code is often locally competent and globally unwired. Sometimes the honest answer is yes, and you’ll hear it in the first conversation, not after three invoices. As GitClear’s 2026 report puts it: the throughput is real, and so is the debt. We help you keep the first and retire the second, and if you’re deciding how to adopt AI tooling safely from the start, that’s our AI consulting practice. Tell us what you shipped. We’ve seen worse.

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