Codex
Security FAQ

What security issues do OpenAI Codex apps have?

Get instant answers about your app's security.

Short Answer

The security issues specific to OpenAI Codex apps are test credentials in production, missing input validation, weak auth defaults. These aren't generic — they map to how OpenAI Codex deploys and what stack it leans on.

Detailed Answer

The specific issues we find in OpenAI Codex apps

  1. **Test Credentials in Production** — Codex may generate working code with test API keys that persist to deployment.

2. **Missing Input Validation** — Generated endpoints may accept and process user input without sanitization.

3. **Weak Auth Defaults** — Authentication code may work but lack rate limiting, email verification, or CSRF protection.

4. **Database Access Without Authorization** — Queries may fetch data without checking if the user owns it.

Why these are the issues specific to OpenAI Codex

OpenAI Codex apps ship with a recognizable stack (supabase, firebase, postgres). The issue list above is what appears when you scan that specific combination. A Firebase-backed app would have a different top-5; a self-hosted Postgres deployment would have yet another. Context is everything.

What VAS checks in a OpenAI Codex scan

  • **Secrets Detection** — Find test credentials and API keys in generated code.
  • **Input Validation** — Check all endpoints for proper input sanitization.
  • **Auth Security** — Test authentication for rate limiting and session handling.
  • **Data Authorization** — Verify users can only access their own data.

Security Research & Statistics

10.3%

of Lovable applications (170 out of 1,645) had exposed user data in the CVE-2025-48757 incident

Source: CVE-2025-48757 security advisory

4.45 million USD

average cost of a data breach in 2023

Source: IBM Cost of a Data Breach Report 2023

500,000+

developers using vibe coding platforms like Lovable, Bolt, and Replit

Source: Combined platform statistics 2024-2025

Expert Perspectives

There's a new kind of coding I call 'vibe coding', where you fully give in to the vibes, embrace exponentials, and forget that the code even exists.

Andrej KarpathyFormer Tesla AI Director, OpenAI Co-founder

Vibe coding your way to a production codebase is clearly risky. Most of the work we do as software engineers involves evolving existing systems, where the quality and understandability of the underlying code is crucial.

Simon WillisonSecurity Researcher, Django Co-creator

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More Questions About This Topic

Which OpenAI Codex security issue is most dangerous?

Test Credentials in Production. Codex may generate working code with test API keys that persist to deployment. This is the highest-impact finding because it tends to expose the full dataset or grant lateral movement in one step.

Are these issues unique to OpenAI Codex, or do they appear across platforms?

The patterns overlap with devin, claude code, copilot — all vibe-coding platforms share the "AI-generated code prioritizes functionality over security" problem. But the *specific manifestation* differs per platform. An exposed Supabase anon key is structurally different from an exposed Firebase config, which is different from an exposed Postgres connection string. The right scan is platform-aware.

How do I see which of these issues my OpenAI Codex app has?

Run a VAS scan against your deployed OpenAI Codex app URL. It checks every issue in the list above, confirms each by actually probing (not just reading headers), and prioritizes by severity with copy-paste fixes. Most OpenAI Codex app scans return results in 2–3 minutes.