Guardrail Catalog | NVIDIA NeMo Guardrails Library Developer Guide

The NeMo Guardrails library ships with a catalog of pre-built guardrails that you can activate out of the box. These guardrails span the most common safety and security concerns in LLM-powered applications from blocking harmful content and detecting jailbreak attempts to masking personally identifiable information and grounding responses in evidence.

Each guardrail is implemented as a configurable rail flow that you add to the input, output, or retrieval section of your config.yml. You can use NVIDIA-trained safety models, open-source community models, LLM self-check prompts, or third-party managed APIs, and combine multiple approaches for defense in depth.

Browse the catalog below to find the guardrail that fits your use case.

Content Safety

Reference for pre-built content safety guardrails for protecting against violence, criminal activity, hate speech, sexually explicit content, and similar areas.

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Jailbreak Protection

Reference for jailbreak protection guardrails that help prevent adversarial attempts from bypassing safety measures.

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Topic Control

Reference for topic control guardrails that ensure conversations stay within predefined subject boundaries.

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PII Detection

Reference for PII detection guardrails that protect user privacy by detecting and masking sensitive data.

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Agentic Security

Reference for agentic security guardrails that protect LLM-based agents using tools and interacting with external systems.

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Hallucinations & Fact-Checking

Reference for fact-checking and hallucination detection guardrails that ensure LLM output is grounded in evidence.

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LLM Self-Check

Reference for LLM self-checking guardrails that prompt the LLM to perform input checking, output checking, or fact-checking.

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Third-Party APIs

Reference for third-party API integrations that connect with managed services for guardrail use cases.

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