• Always enable provider content filters — they're free and catch most issues
• For user-facing outputs, add a secondary moderation layer
• Log flagged outputs for review
• Never display raw LLM output without some form of sanitization

4. Rate Limiting & Cost Protection

A single attacker can run up thousands of dollars in API bills overnight. Protect yourself.

Application-Level Rate Limits

• Per-user limits: 10-50 requests/hour per user for free tier, higher for paid
• Global limits: Set a hard cap on total daily/monthly spend
• Burst limits: Prevent rapid-fire requests (e.g., max 5 requests/second per user)

Spending Alerts

• Set up billing alerts at 50%, 80%, and 100% of your budget
• Most providers support email/SMS alerts for spending thresholds
• Implement a kill switch that disables API access when limits are hit

Cost-Aware Architecture

• Estimate cost before each request (check token count × model price)
• Reject requests that would exceed per-user budgets
• Use cheaper models for non-critical paths
• Implement token budgets per request and per day

5. Authentication & Authorization

Control who can access your AI features and what they can do.

• Require authentication for all AI API endpoints
• Use session tokens or JWTs — not API keys — for user authentication
• Role-based access: Differentiate between free and Pro users
• Audit logging: Record who made each request, what model was used, and how many tokens

6. Data Privacy

AI APIs process your users' data. Handle it responsibly.

• Don't send PII to APIs unless necessary — anonymize or pseudonymize first
• Check provider data policies: OpenAI and Anthropic don't train on API data by default; Google does for free tier
• Data retention: Understand how long providers store your requests
• Compliance: If you're in healthcare (HIPAA), finance (SOC 2), or EU (GDPR), verify the provider's compliance certifications
• Self-hosted alternatives: For sensitive data, consider self-hosting open-source models

7. Provider-Specific Security Features

OpenAI

• Content moderation API: Free, built-in safety system
• Organization scoping: Separate projects for different environments
• Admin API keys: Manage keys with restricted permissions
• Compliance: SOC 2 Type II, GDPR, CCPA

Anthropic

• Constitutional AI: Built-in safety training
• Team management: Role-based access for organizations
• Prompt caching: Reduces repeated data processing
• Compliance: SOC 2 Type II, GDPR

Google

• Safety settings: Adjustable content filter sensitivity
• VPC Service Controls: Network-level isolation for enterprise
• Cloud IAM: Fine-grained access control via Google Cloud
• Compliance: SOC 1/2/3, ISO 27001, HIPAA (with BAA)

Security Checklist

The Bottom Line

AI API security isn't fundamentally different from securing any other API integration — but the attack surface is unique. Prompt injection, cost attacks, and data leakage require specific mitigations. Start with the basics: proxy all calls through your backend, rate limit aggressively, and enable content filters. Then layer on output filtering, audit logging, and prompt injection defenses as you scale.

— See if you're overpaying for AI APIs