5 Real Issues With LiteLLM That Are Pushing Teams Away in 2026

The LiteLLM supply chain attack on March 24, 2026 was the trigger for this post, but not the only reason I wrote it. Two backdoored versions (1.82.7 and 1.82.8) were published to PyPI using stolen credentials. The malware stole SSH keys, cloud credentials, and K8s secrets. DSPy, MLflow, CrewAI, and OpenHands all pulled the compromised package. If you missed it, Snyk's full breakdown is worth reading. I've been using LiteLLM in various projects for over a year. After the incident, I spent a few days auditing my own stack and evaluating alternatives. What I found wasn't just a security problem. It was a pattern of issues that compound at scale. If you're evaluating LLM gateways right now, Bifrost is worth putting on your shortlist. It's a Go-based open-source LLM gateway that sidesteps most of the problems I'm about to describe. TL;DR The supply chain attack exploited a Python-specific persistence mechanism that doesn't exist in compiled binaries. LiteLLM adds ~8ms of latency per request