Trae
Security FAQ

What security issues do Trae AI apps have?

Get instant answers about your app's security.

Short Answer

The security issues specific to Trae AI apps are hardcoded secrets in generated code, missing database access controls, data privacy — code sent to bytedance. These aren't generic — they map to how Trae AI deploys and what stack it leans on.

Detailed Answer

The specific issues we find in Trae AI apps

  1. **Hardcoded Secrets in Generated Code** — Trae's code generation often includes placeholder API keys that make it to production.

2. **Missing Database Access Controls** — Generated database queries lack RLS or Security Rules by default.

3. **Data Privacy — Code Sent to ByteDance** — All code passes through ByteDance's cloud AI infrastructure for processing.

4. **Weak Authentication Patterns** — AI-generated auth may skip email verification and rate limiting.

Why these are the issues specific to Trae AI

Trae AI 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 Trae AI scan

  • **Secrets Scan** — Find API keys and credentials in generated code.
  • **Database Security** — Check RLS and access controls on data layer.
  • **Auth Testing** — Verify authentication and authorization flows.
  • **Headers & Config** — Test security headers and deployment config.

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 Trae AI security issue is most dangerous?

Hardcoded Secrets in Generated Code. Trae's code generation often includes placeholder API keys that make it to production. 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 Trae AI, or do they appear across platforms?

The patterns overlap with cursor, windsurf, bolt — 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 Trae AI app has?

Run a VAS scan against your deployed Trae AI 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 Trae AI app scans return results in 2–3 minutes.