A hands-on audit framework for verifying that an LLM gateway's model routing and prompt caching actually cut token spend before you trust the vendor's cost chart.
A hands-on audit walkthrough of a widely used LLM gateway's high-risk flaws—auth bypass, API-key exposure, and cross-tenant data leaks—set against fresh reports of AI-driven ransomware and AI agents breaching production systems.
LiteLLM CVE-2026-42208 shows how a pre-auth SQL injection in an AI gateway can expose provider keys, routing data, and other secrets, turning LLM proxies into high-value credential vaults.