Egress Filtering
Egress filtering is the practice of controlling outbound traffic from a system, allowing connections only to approved destinations and blocking the rest. It is a standard network security control against data exfiltration and command-and-control channels. Applied to AI, egress filtering governs which model endpoints and external services an application or agent is allowed to call. Restricting an AI agent to a specific list of approved LLM endpoints, rather than the open internet, limits both where it can send data and which unvetted models it can reach.
How egress filtering applies to AI traffic
A default AI deployment can often reach any model API on the internet. That openness is the same property an attacker relies on to route stolen data to an endpoint they control, or to swap a sanctioned model for an unvetted one. Egress filtering narrows that to an allowlist: the set of model endpoints and services the workload is permitted to contact. Network-layer egress rules can restrict destinations by address, but they cannot read what is inside the encrypted AI request.
Where identity-aware egress control adds precision
Filtering by destination alone treats every caller the same. Identity-aware egress control decides based on who is calling and what the request contains, alongside where it is headed. DeepInspect sits on the AI request path and evaluates the identity, the payload, and the destination together, so one role may reach a model endpoint that another may not, and a request carrying sensitive content can be blocked even to an otherwise approved destination. Each decision is recorded, giving a defensible log of what egress was permitted and what was refused.
Related reading
- AI Egress Control Implementation: Allowlisting the Destination Does Not Govern the Payload
Teams implement AI egress control with DNS filtering, SNI inspection, forward proxies, Kubernetes NetworkPolicy, and Cilium FQDN rules. Each governs the destination of AI traffic without reading the prompt, and Kubernetes NetworkPolicy cannot express FQDNs at all. This article gives working Cilium and Envoy egress config, explains why each layer stops at the destination, and shows why reading the payload requires sitting on the decrypted HTTP path.
- LLM Egress Control: The Per-Request Identity, Classification, and Audit Layer for AI Provider Traffic
LLM egress control is the request-time enforcement layer between corporate applications (and agents) and the external LLM endpoints they call. The layer reads the identity the request carries, classifies the prompt body, evaluates per-route policy, applies a pass, modify, redact, or block decision, and commits a per-decision audit record. This piece walks through the egress surface the layer covers, the policy decisions the layer commits, the audit record format, and the deployment topology that handles single-region and multi-region traffic.
- AI Agent Egress Control: The Destination Allowlist That Survives Prompt Injection
AI agent egress control bounds the destinations an agent can reach on its outbound calls. A correct implementation binds the destination policy to the agent identity, evaluates the decision at the HTTP layer outside the agent process, and records the per-decision result for audit. This walkthrough covers the three classes of egress an agent makes, the destination-allowlist patterns that hold under prompt injection, and the audit-record fields a regulator expects.