Trae
Security FAQ

What vulnerabilities are found in Trae AI apps?

Get instant answers about your app's security.

Short Answer

Trae AI app scans surface the same cluster of vulnerabilities repeatedly: hardcoded secrets in generated code, missing database access controls, data privacy — code sent to bytedance. The pattern is stable across Trae AI versions.

Detailed Answer

The vulnerabilities actually found in Trae AI apps

Not theoretical OWASP categories — specifically what appears when VAS, security researchers, and bug bounty hunters look at live Trae AI deployments:

  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.

Distribution by severity

Of the findings above, 0 sit at critical impact (full data exposure), 0 at high (significant data or account compromise), and the rest are medium-or-lower (attack surface expansion). A first-scan Trae AI app typically has 2–4 findings from this list live at any moment.

How to know which ones are in your app

Run a VAS scan. Each finding above is tested directly — we query your database to verify access controls are active, scan bundles for key patterns, probe auth endpoints for rate limiting, and check security headers in live responses. Output is a per-finding report with evidence and fix.

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

How severe are the vulnerabilities typically found in Trae AI apps?

Trae AI apps lean critical: Hardcoded Secrets in Generated Code alone can expose the full user dataset in one query. Compare to e.g. missing security headers (medium) which require additional exploitation. Triage accordingly: critical findings are measured in minutes-to-breach, mediums in weeks.

How do I fix vulnerabilities once they're found in my Trae AI app?

Start with critical impact findings, apply the remediation guidance per finding, and re-scan. Never "fix and hope" — confirm with a second scan. Many fixes (e.g., enabling RLS) are one-line; others (e.g., moving a secret server-side) require structural changes to where the value is used.

Can vulnerabilities in Trae AI apps be exploited by a non-expert attacker?

Most can. Extracting an exposed API key is a single "view source" operation. Querying a table without RLS is a `curl` command. Exploiting missing rate limiting requires scripting skills equivalent to "follow a tutorial." Only a handful of the findings above (e.g., chained auth bypass) require specialist knowledge — the rest are routinely exploited by automated scanners with zero human involvement.