What the checklist covers:
21
Testable security controls for LLM, MCP, and agent traffic through a gateway
3
Control areas: identity and secrets, runtime guardrails, and audit and deployment
18
Must-have controls, flagged so you know what has to pass before rollout
4
Deployment models compared: VPC, on-premises, hybrid, and air-gapped
Inside the checklist
Download the checklist to get:
A working framework your security and platform teams can use to evaluate any LLM gateway, or to run your own gateway through a security review.
Download the Checklist✓
The full 21-point LLM gateway security framework
Every control grouped by area, with the question to ask and a must-have or should-have priority.
✓
A three-step security review plan
Map access across apps, models, MCP servers, credentials, and data classes, enforce policy, then verify audit evidence.
✓
Guardrail and abuse-control criteria
What to test for PII redaction, prompt injection, content moderation, custom rules, rate limits, and budgets.
✓
Compliance and deployment requirements
The attestations, log ownership, tenant isolation, and deployment options to require for SOC 2, HIPAA, GDPR, and ITAR workloads.
Why it matters
The LLM Gateway Is Your New Security Boundary
LLM traffic now carries prompts, responses, tool calls, secrets, user context, and policy decisions across a new enterprise boundary. Every application that calls a model is sending potentially sensitive data to a third party, and every agent that calls a tool is acting with some level of privilege.
Without a gateway, each team wires up providers on its own. Raw API keys end up in environment variables and code repos. Nobody can say which user sent which data to which model. Guardrails are applied in some apps and not others, and a runaway script can burn through a month's budget overnight.
Every request passes the same checks in the same order. The checklist turns each stage into controls you can test.
An LLM gateway fixes this by putting one policy enforcement point in front of every model and tool. But not every gateway is built for security. Some are routing layers with authentication bolted on. Others run only as a hosted service, so your prompts and logs pass through someone else's infrastructure. Security reviews stall when nobody can show which controls are enforced and how.
What a secure LLM gateway looks like
Every request is authenticated through SSO, workload identity, or a scoped virtual key, and RBAC limits which models, tools, environments, and logs each user, team, and app can reach. Provider keys stay in the gateway or your secret manager, and rotate without redeploying apps.
PII, prompt injection, and unsafe content are caught inline, with custom and third-party guardrails for your own policies. Rate limits and budgets block requests predictably when they're exhausted. Every request is logged with identity, route, cost, and guardrail outcome, kept in your cloud, and exported to your SIEM. Teams are isolated from each other, and MCP servers and tools follow the same policy model as models.
Make the security review testable
"Do you support guardrails?" gets a yes from every vendor. "Is prompt injection blocked inline before the tool layer, with the outcome logged?" can be tested. The LLM Gateway Security Checklist turns gateway security into 21 controls like that, so your review produces evidence instead of assurances.
Preview
The three control areas in the LLM gateway security checklist
A sample of the controls in each area. The full checklist includes all 21, with priorities and evaluation questions.
Area 1 · 6 checks
Identity, access control, and secret protection
Every model and tool request goes through SSO, workload identity, or scoped gateway keys
RBAC restricts models, providers, tools, environments, and logs
Provider keys rotate without app redeploys
+3 more checks
Area 2 · 7 checks
Runtime guardrails and abuse controls
PII is detected and redacted inline in prompts and responses
Prompt injection is blocked before the model or tool layer
Budgets block requests automatically when exhausted
+4 more checks
Area 3 · 8 checks
Audit, compliance, and deployment ownership
Request logs capture identity, route, cost, guardrail outcomes, and errors
Logs stay in customer-controlled storage
Teams and business units are isolated at the gateway
+5 more checks
4.7
★★★★★
Gartner Peer Insights
Rated 4.7 on Gartner Peer Insights
Platform and security teams run TrueFoundry's AI Gateway for LLM, MCP, and agent traffic in production, with centralized access control, scoped keys, guardrails, budgets, rate limits, request logging, and customer-controlled deployment.
96%
of reviewers likely to recommend
4.9
ease of deployment and admin
3–4 ms
added gateway latency
