AI Hacking
AI Security Resources

LLM API Security

Best practices for securing LLM API endpoints - authentication, rate limiting, key management, and cost control

Updated: March 2026

LLM API Threat Landscape

API Key Exposure

Hardcoded keys in source code, client-side exposure, or leaked credentials

Rate Limit Abuse

Automated attacks consuming API quotas or causing denial of service

Cost Attacks

Prompt manipulation causing excessive token usage and unexpected costs

Data Leakage

Sensitive data in prompts or responses exposed through logs

Authentication Methods

API Keys

  • Generate unique keys per user/application
  • Use environment variables for storage
  • Rotate keys regularly (30-90 days)
  • Implement key revocation

OAuth 2.0

  • Implement for user-facing applications
  • Use short-lived access tokens
  • Implement refresh tokens
  • Proper scope definitions

JWT Tokens

  • Short expiration times
  • Strong signing algorithms
  • Proper claim validation
  • Token revocation support

Rate Limiting & Throttling

Token-Based Limits

  • Track input + output tokens
  • Set per-minute/per-day limits
  • Use sliding windows
  • Implement burst allowance

Cost Controls

  • Budget alerts (various thresholds)
  • Per-user quotas
  • Token estimation before requests
  • Hard caps with circuit breakers

Tiered Approaches

  • Free tier: strict limits
  • Basic: moderate limits
  • Pro: higher limits
  • Enterprise: custom agreements

Provider Security Comparison

Provider Key Features Rate Limits Security
OpenAI GPT models, Assistants API Tier-based RPM SOC 2, API key management
Anthropic Claude, tool use Token-based SOC 2, HIPAA available
Google Gemini, Vertex AI Project quotas SOC 2, HIPAA, ISO
AWS Bedrock Multiple models Account-based AWS IAM, VPC, encryption

Self-Hosted LLM Security

Network Isolation

  • Deploy in VPC/private network
  • Use firewall rules
  • No public internet access
  • VPN for management

API Security

  • Enable authentication
  • Use TLS/SSL
  • Implement API keys
  • Rate limiting

Model Protection

  • Model files encrypted at rest
  • Secure model loading
  • No model export
  • Access logging

Cost Attacks & Abuse Prevention

LLM APIs present unique cost attack vectors that traditional API security doesn't address.

Prompt Padding

Attacker adds invisible text to prompts to increase token count without user awareness.

User: [100KB invisible text] Tell me about AI

Repeated Requests

Automated tools making excessive API calls to drain budget quotas.

Context Window Overflow

Sending extremely long inputs to maximize per-request costs.

Model Selection Abuse

Switching to more expensive models through parameter manipulation.

Mitigations

Recent LLM API CVEs

CVE ID Description Severity
CVE-2025-61260 OpenAI Codex CLI command injection via project-local .env config Critical
CVE-2025-53767 Azure OpenAI privilege escalation flaw High
CVE-2025-14980 BetterDocs WordPress plugin exposes OpenAI API key to contributors High

Best Practices Checklist

  • Use environment variables for API keys
  • Rotate keys regularly
  • Implement rate limiting
  • Set cost alerts
  • Log API usage
  • Use HTTPS
  • Validate input
  • Sanitize output
  • Related Topics

    Secure Development Prompt Injection Security Tools