Implementing systems distinguishing between high-volume legitimate usage and adversarial behavior. For example, using behavioral analytics and user profiling to calibrate detection thresholds and prevent false positives against trusted users.
Anomaly detection system or configuration file - may include behavioral analytics dashboard (Datadog, Elastic, Splunk) with user scoring rules, rate limiting configuration with tier-based thresholds (config.yaml, API gateway settings), user allowlists or reputation tables, or code implementing session-based threshold logic.
Implementing rate limiting and query restrictions. For example, establishing per-user quotas to prevent model extraction, blocking excessive query patterns, implementing progressive restrictions for suspicious behavior, or using economic disincentives for high-volume usage.
Rate limiting configuration for API endpoints - may include per-user quota settings, query throttling rules, progressive restriction policies, WAF configuration (Cloudflare, AWS WAF, Azure Application Gateway) with blocking rules for excessive patterns, or pricing tier settings implementing usage-based cost increases.
Conducting simulated external attack testing of AI endpoints. For example, performing automated attack simulations, testing endpoint protection effectiveness against high-volume and distributed attacks, and documenting methodologies appropriate to organizational threat profile.
Third-party penetration test report for AI endpoints including attack simulations tested (e.g. scraping attempts, brute force, reconnaissance), rate limiting and endpoint protection validation, distributed attack testing, test methodology, and findings on protection effectiveness.
Maintaining endpoint security through remediation. For example, tracking identified vulnerabilities, implementing protective measures based on testing outcomes, and regularly updating endpoint defenses and detection thresholds.
Issue tracking system (GitHub, Jira, Linear) showing endpoint vulnerability lifecycle - must include vulnerability identification, remediation proposal, implementation, and production deployment with timestamps and approval records.
Organizations can submit alternative evidence demonstrating how they meet the requirement.