The OWASP LLM Protocol: 100% Automated Coverage for Vercel AI
A complete mapping of OWASP LLM Top 10 to static analysis rules. The engineering standard for governance in the Vercel AI ecosystem.
Governance for AI agents is the new frontier for CTOs. Here is the engineering standard for mapping the Vercel AI SDK to the OWASP LLM Top 10 through 100% automated static analysis rules.
The OWASP LLM Top 10 2025 is here. And your Vercel AI SDK application probably violates half of it.
I know because I built a plugin to check. One ESLint config. Full OWASP coverage. 60 seconds to install.
This plugin is designed specifically for the Vercel AI SDK. It understands
generateText,streamText,tool(), and other SDK functions—not just pattern-matching on strings.
The 10 Categories (And How to Automate Them)
| # | OWASP Category | What It Means | ESLint Rule |
|---|---|---|---|
| LLM01 | Prompt Injection | User input manipulates AI behavior | require-validated-prompt |
| LLM02 | Sensitive Information Disclosure | Secrets/PII leaked to LLM | no-sensitive-in-prompt |
| LLM03 | Supply Chain Vulnerabilities | Compromised models/libraries | no-training-data-exposure |
| LLM04 | Data and Model Poisoning | Malicious data in fine-tuning | require-request-timeout |
| LLM05 | Improper Output Handling | AI output executed as code | no-unsafe-output-handling |
| LLM06 | Excessive Agency | AI invokes tools without consent | require-tool-confirmation |
| LLM07 | System Prompt Leakage | AI reveals system instructions | no-system-prompt-leak |
| LLM08 | Vector and Embedding Weaknesses | Malicious embeddings in RAG | require-embedding-validation |
| LLM09 | Misinformation | AI output displayed without checks | require-output-validation |
| LLM10 | Unbounded Consumption | Token/step exhaustion | require-max-tokens, require-max-steps |
Why This Matters
OWASP isn't just a checklist for security audits. It's becoming a compliance requirement.
If you're building AI features for enterprise customers, they will ask: "How do you address the OWASP LLM Top 10?"
Having an automated, auditable answer makes the difference between a closed deal and a 6-month security review.
Before & After
Before (silent vulnerability):
await generateText({
prompt: userInput, // No validation, no warning
});
After (with the linter):
🔒 CWE-74 OWASP:LLM01 CVSS:9.0 | Unvalidated prompt input | CRITICAL
Fix: Validate/sanitize user input before use
No more finding these in production.
The Implementation
eslint-plugin-vercel-ai-security provides SDK-aware rules for the Vercel AI SDK. It's not pattern-matching on strings—it understands generateText, streamText, tool(), and other SDK functions.
// eslint.config.js
import vercelAISecurity from "eslint-plugin-vercel-ai-security";
export default [
vercelAISecurity.configs.recommended, // Balanced security
// vercelAISecurity.configs.strict, // Maximum security
];
CI Integration
Every PR now gets automatic OWASP validation:
# .github/workflows/security.yml
- name: Lint AI Security
run: npx eslint 'src/**/*.ts' --max-warnings 0
The Punch Line
100% OWASP LLM coverage sounds impressive in a sales deck. But more importantly, it means your AI application is protected against the most common attack patterns.
The plugin is free. The compliance is automatic. The alternative is manual pen-testing at $500/hour.
Your call.
The Interlace ESLint Ecosystem Interlace is a high-fidelity suite of static code analyzers designed to automate security, performance, and reliability for the modern Node.js stack. With over 330 rules across 18 specialized plugins, it provides 100% coverage for OWASP Top 10, LLM Security, and Database Hardening.
Explore the full Documentation
© 2026 Ofri Peretz. All rights reserved.
Build Securely. I'm Ofri Peretz, a Security Engineering Leader and the architect of the Interlace Ecosystem. I build static analysis standards that automate security and performance for Node.js fleets at scale.