Building Secure LLM Applications: OWASP Top-10 in Practice
A comprehensive guide to implementing OWASP LLM Top-10 security guidelines in production AI systems, with real-world examples and code snippets.
15 · xii · 20258 min read
- AI Security
- OWASP
- LLMs
- Best Practices
Security in LLM applications isn't optional—it's essential. Here's how I implement OWASP LLM Top-10 compliance in production systems.
Key Security Measures
1. Prompt Injection Mitigation
- Input validation and sanitization
- Output filtering
- Structured prompts with clear boundaries
2. Secure API Design
- Authentication and authorization
- Rate limiting
- Request validation
3. Data Privacy
- PII detection and redaction
- Secure data handling
- Compliance with regulations
Implementation Example
def validate_input(user_input: str) -> str:
# Sanitize input
sanitized = sanitize_text(user_input)
# Check for injection patterns
if detect_injection(sanitized):
raise SecurityError("Potential injection detected")
return sanitized
Conclusion
Security should be built into every layer of your LLM application, from input validation to output filtering.
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