Developer documentation

Integrate, configure, and deploy DFENS.

DFENS is a self-hosted application firewall for LLM traffic, the engine built in the ai-firewall repository. It inspects prompts, model responses, and tool-result content against declarative rules, and it runs entirely on your own hardware. This section is for the engineers who adopt it.

Private early access

DFENS is in private early access. The container image is distributed through a private registry to approved design partners. It is not on any public registry yet. Request access to be issued a registry credential and an image reference; the examples below use REGISTRY/ai-firewall:<tag> as a placeholder for it.

How it fits into your stack

There are two ways to put DFENS in the path of a model call, and they share one rule engine and one audit log:

Read this first

Secure the data plane on two layers. DFENS can require callers to present a client token (the X-AI-Firewall-Key header, see client authentication), and it's still meant to run on a trusted network segment (private network, or a Kubernetes NetworkPolicy). Treat these as defense-in-depth: turn on the client token and keep the listener off untrusted networks. Client auth is opt-in, so if you haven't configured a token the proxy accepts any caller that can reach it.

Start with API integration if you want to send your first blocked request, or jump to Deployment to get an instance running first.