Lilly Tech Systems
API Security for AI Services
Protect your AI-powered APIs from abuse, unauthorized access, and novel attack vectors. Master authentication, rate limiting, input validation, prompt injection defense, and cost attack prevention.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Why AI APIs face unique security challenges, the threat landscape for AI services, and the OWASP Top 10 for LLM applications.
2. Authentication
API key management, OAuth2 for AI services, JWT tokens, key rotation, and zero-trust authentication patterns.
3. Rate Limiting
Token-based rate limiting, abuse prevention, cost controls, usage quotas, and DDoS protection for AI endpoints.
4. Input Validation
Prompt injection via API, schema validation, content filtering, payload size limits, and malicious input detection.
5. Output Security
Response sanitization, PII filtering, content safety classifiers, output validation, and preventing data leakage.
6. Best Practices
API gateway configuration, monitoring and alerting, cost attack prevention, compliance, and security testing.
What You'll Learn
By the end of this course, you'll be able to:
Secure Authentication
Implement robust API key management, OAuth2 flows, and zero-trust authentication for AI service endpoints.
Prevent Abuse
Design rate limiting, usage quotas, and cost controls that protect against abuse without impacting legitimate users.
Validate Inputs
Detect and block prompt injection attacks, malicious payloads, and adversarial inputs at the API layer.
Control Costs
Prevent cost attacks that exploit expensive AI inference to rack up massive bills through API abuse.