Dan Finneran outlines how eBPF socket hooks can intercept and control AI API traffic within Kubernetes clusters without altering application code. This approach enables transparent prompt filtering, dynamic model swapping, token limits, and syscall restrictions at the kernel level. The method addresses risks associated with unowned AI-generated code by securing agents transparently and without container restarts.
- eBPF kernel hooks allow transparent interception of AI API traffic in Kubernetes.
- Secure AI agents without modifying source code or restarting containers.
- Enable prompt filtering and token limits at the network layer.
- Implement dynamic model swapping and syscall restrictions via eBPF.
- Mitigates risks from unowned AI-generated code in production.