Guardrails in n8n – finally an easy way to keep your AI workflows safe

As someone who uses n8n daily for AI workflows and automation, I really like the direction they’re taking with the new Guardrails node introduced in version v1.119.

Until now, if you wanted to protect your LLM workflows from prompt injection, NSFW content, or sensitive data leaks, you had to manually build complex checks and filters.
Now, it’s just one node away.

💡 What it does

The Guardrails node helps keep your AI flows clean, compliant, and under control by letting you:

Check Text for Violations → flag unsafe or unwanted input/output (like NSFW content, prompt injections, or policy breaches).
Sanitize Text → automatically remove PII, secrets, or URLs and replace them with placeholders such as <EMAIL> or <SECRET>.

It’s basically like having a safety layer wrapped around your LLM — and it just works.

⚙️ How I’m using it in my setup

In my Bondo and content-generation flows, I’m adding Guardrails in two places:

Before the LLM node – to check user input for policy or prompt violations.
After the LLM node – to sanitize model output before storing or displaying it.

This makes the workflow safer without slowing it down.
It also gives me more confidence to let AI handle real user content, knowing that nothing risky or private will leak through.

🚀 Why this matters

When you build AI-powered tools, safety can’t just be an afterthought.
This new node removes friction — no more reinventing filters, regex checks, or moderation logic.
Just drop the Guardrails node in, connect it, and you’re good.

It’s a small feature, but it really changes how easy it is to keep your flows reliable and secure.

📘 Documentation

You can find the node under:
n8n-nodes-langchain → Guardrails

Official docs: n8n.io → Guardrails Node