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Guardrails catalogue

The gateway ships the guardrails below. Each one validates, filters, or transforms content in the request or response pipeline, and you attach it to an LlmProvider, an LlmProxy, or an Mcp proxy. For what guardrails do as a class, and how a chain of them executes, see Guardrails.

Available guardrails

Guardrail policies are documented in the Policy Hub, the versioned reference for every API Platform policy. For policy categories and how policies chain, see the Policy Hub overview.

Guardrail What it checks
Regex Guardrail Validates content against a regular expression
JSON Schema Guardrail Enforces a JSON Schema on request or response payloads
Word Count Guardrail Enforces word-count limits on payloads
Sentence Count Guardrail Enforces sentence-count limits on payloads
Content Length Guardrail Enforces byte-length limits on payloads
URL Guardrail Validates URLs found in request or response bodies
PII Masking Masks or redacts PII from request/response bodies using configurable regex patterns
Semantic Prompt Guard Blocks or allows prompts based on semantic similarity to configured allow/deny phrases
Azure Content Safety Screens content against Azure Content Safety API
AWS Bedrock Guardrail Validates content against AWS Bedrock Guardrails
Granite Guardian Prompt Injection Detects prompt injection and jailbreak attempts in LLM API requests using IBM Granite Guardian 3.3 8B
NeMo Guard Content Safety Validates request and/or response content using NVIDIA NeMo Guard (llama-3.1-nemoguard-8b-content-safety)

Custom guardrails

You can extend the AI Gateway with custom guardrail policies by building a custom gateway image using the ap CLI. See Customizing the Gateway by Adding and Removing Policies.

  • Guardrail execution order — the order a chain of these policies runs in, and how the proxy and provider chains combine.
  • Prompt management — the policies that reshape a prompt rather than judging it.
  • MCP governance — the policies that govern MCP traffic, including semantic tool filtering.