Tabnine
Security Guide

How to Secure Your Tabnine App

Last updated: January 12, 2026

Tabnine provides AI code completions with local and cloud options. This guide covers securing applications built with Tabnine assistance.

Step-by-Step Security Guide

1. Choose Appropriate Model

Use local models for sensitive codebases. Cloud models send context to Tabnine servers.

2. Configure File Exclusions

Exclude .env files and secrets directories from Tabnine's context.

3. Review Completions Carefully

Tabnine optimizes for code that compiles, not security. Review all completions.

4. Watch for Credential Completions

If Tabnine suggests what looks like a real credential, it may have learned from your codebase. Investigate.

5. Use Security Linters

Run static analysis on all code, including AI-generated completions.

6. Scan Before Launch

Use VAS to verify your deployed application is secure.

Common Security Mistakes

Avoid these common Tabnine security pitfalls:

Cloud model for sensitive projects
Auto-accepting credential-like completions
Sensitive files in completion context
Missing security review of completions
No static analysis on AI-generated code

Recommended Security Tools

Use these tools to maintain security throughout development:

VAS Security Scanner
npm audit / yarn audit
Git-secrets
Snyk

Ready to Secure Your App?

Security is an ongoing process, not a one-time checklist. After implementing these steps, use VAS to verify your Tabnine app is secure before launch, and consider regular scans as you add new features.

Frequently Asked Questions

What's the difference between local and cloud Tabnine?

Local models run entirely on your machine with no data leaving your system. Cloud models send code context to Tabnine servers for better suggestions. Use local for sensitive projects.

Can Tabnine leak my secrets?

If secrets are in files Tabnine reads, they're part of the context. Cloud models send this context externally. Exclude sensitive files and use local models for maximum privacy.