AI coding assistants are astonishingly good at producing code that runs. Whether that code is safe is a separate question — and the honest answer is often “not yet.” Here are the five findings we see most frequently, in plain language.
1. Secrets committed to the repo
A live API key hard-coded into a config file is the single most common critical finding. Anyone with repo access — or anyone who digs through your git history — can use it.
Fix: move the value to an environment variable, and rotate the leaked key so the old one stops working.
2. Endpoints with no authentication
Admin routes that accept requests with no session or token check are surprisingly common in generated code, because the assistant scaffolds the handler but not the guard in front of it.
Fix: require an authenticated session and verify the caller’s role on the server before the handler runs.
3. User input rendered as raw HTML
If profile bios or comments are inserted into the page without escaping, a user can store a script that runs in everyone else’s browser (stored XSS).
Fix: render user content as text, or escape it on output.
4. Dependencies with known advisories
Generated package.json files often pin older, vulnerable versions of transitive dependencies — easy to miss because you never added them directly.
Fix: upgrade to patched releases and turn on automated dependency alerts.
5. Error responses that leak stack traces
Returning full stack traces to the client hands an attacker a map of your file paths and libraries.
Fix: return generic error messages in production and log the detail server-side only.
None of these are exotic. They’re the basics — and the basics are exactly what a fast-moving, AI-assisted workflow tends to skip. A LaunchSure check names each one in plain language and pairs it with a concrete fix.
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