resource-exhaustion-dos-ai-generated-code

Resource exhaustion attacks exploit unbounded operations in code to crash servers or inflate costs. Implement rate limiting, request timeouts, input size validation, and job queues to control concurrent processing. This Skill identifies vulnerabilities in AI-generated endpoints and applies these protections automatically.

AI-generated image processing often lacks rate limits, input validation, and cost controls, creating denial-of-service and API abuse risks. This Skill detects missing timeouts, unbounded concurrency, SSRF vulnerabilities in downloads, and uncontrolled API calls that can cost hundreds of thousands of dollars.

Rate limiting and input validation block abusive traffic and control costs. This Skill analyzes AI-generated web endpoints for missing quotas, size limits, and timeout configurations, then suggests secure implementations with job queues, URL validation, and concurrency controls.

Yes. Denial-of-service via concurrent requests exhausts memory and CPU. This Skill identifies missing job queues, unbounded concurrency, and absent request timeouts in AI code, then applies controls to queue processing and limit simultaneous operations.

Rate limiting throttles request frequency; input size validation blocks oversized payloads. Both prevent API abuse. This Skill implements both strategies—quotas per user, maximum request sizes, and processing timeouts—to stop $200,000+ scenarios of unchecked AI operations.

SSRF occurs when code downloads from user-supplied URLs without validation, exposing internal services. This Skill scans AI-generated endpoints for unsafe URL handling in downloads and suggests secure validation patterns and URL allowlisting.