Test WAF security interactively with an AI agent and WAFtester MCP

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1. Workflow Overview

What it does A conversational AI agent that connects to WAFtester via MCP (Model Context Protocol) for interactive Web Application Firewall security testing. Type natural l...

Best for

SecOps automation workflows
AI Chatbot automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.mcpclienttool, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.stickynote

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Qandil.

Original n8n.io source

1.1 Workflow description

Title: Test WAF security interactively with an AI agent and WAFtester MCP
Workflow name: Test WAF security interactively with an AI agent and WAFtester MCP

What it does

A conversational AI agent that connects to WAFtester via MCP (Model Context Protocol) for interactive Web Application Firewall security testing. Type natural language requests — the agent picks the right tools, runs the tests, and explains the results.

About WAFtester

WAFtester is an open-source CLI for testing Web Application Firewalls. It ships 27 MCP tools, 2,800+ attack payloads across 18 categories (SQLi, XSS, SSRF, SSTI, command injection, XXE, and more), detection signatures for 26 WAF vendors and 9 CDNs, and enterprise-grade assessment with F1/MCC scoring and letter grades (A+ through F).

GitHub: github.com/waftester/waftester
Docs: Installation | Examples | Commands

Who it's for

Security engineers running ad-hoc WAF assessments
Penetration testers who want AI-assisted reconnaissance and bypass discovery
DevSecOps teams validating WAF coverage before and after deployments
API security teams testing OpenAPI/Swagger specs against WAF rules

How it works

The workflow has four nodes:

Chat Trigger — Opens an n8n chat interface where you type requests in plain English
AI Agent — Receives your message, reasons about which tools to call, and orchestrates the testing workflow
OpenAI Chat Model — Provides the LLM reasoning layer (GPT-4o recommended; swappable for Anthropic, Ollama, etc.)
WAFtester MCP — Connects to the WAFtester server via SSE and exposes all 27 tools to the agent

The agent follows a standard WAF testing workflow:

detect_waf — Fingerprint the WAF vendor and CDN protecting the target
discover — Map the attack surface (endpoints, parameters, technologies) from robots.txt, sitemaps, JavaScript, and Wayback Machine
learn — Generate a prioritized test plan based on discovery results
scan — Fire 2,800+ attack payloads and measure detection vs. bypass rates
bypass — Systematic mutation matrix testing to find WAF evasion techniques
assess — Generate a formal security grade with F1, precision, MCC, and false positive rate

Long-running operations (scan, assess, bypass, discover, discover_bypasses, event_crawl, scan_spec) run asynchronously — the agent polls for results automatically.

Key capabilities

Capability	Details
WAF detection	Fingerprint 26 WAF vendors and 9 CDNs from response headers, cookies, and error pages
Payload scanning	2,800+ payloads across 18 attack categories
Bypass discovery	Mutation matrix with 40+ tamper techniques to find WAF evasions
Enterprise assessment	F1 score, precision, MCC, false positive rate, and A+ through F grading
API spec testing	Validate, plan, and scan OpenAPI/Swagger/Postman specs
Headless crawling	Click-driven DOM crawling via headless browser for JS-rendered endpoints
Knowledge resources	12 built-in resources covering WAF signatures, evasion techniques, OWASP mappings, and config defaults

Example prompts

"What WAF is protecting https://example.com?"
"Scan https://example.com for SQLi and XSS"
"Find WAF bypasses for https://example.com"
"Run a full security assessment of https://example.com"
"Validate my API spec at https://example.com/openapi.json"
"Discover the attack surface of https://example.com"

How to set up

Start WAFtester MCP server: docker run -p 8080:8080 ghcr.io/waftester/waftester:latest mcp --http :8080
Add OpenAI credentials in n8n: Settings → Credentials → New → OpenAI API
Select the credential in the OpenAI Chat Model node
Activate the workflow and open the chat interface

Alternatively, use the included docker-compose.yml to run both n8n and WAFtester together with docker compose up -d.

Requirements

Requirement	Details
WAFtester MCP server	Docker image (`ghcr.io/waftester/waftester:latest`) or binary install for macOS, Linux, Windows
LLM API key	OpenAI (default), or swap the model node for Anthropic, Ollama, Azure OpenAI, or any LangChain-compatible provider
Authorization	Only test targets you have explicit written permission to test

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Chat Trigger

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 2 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2

Block 3 - WAFtester MCP

Type / Role: @n8n/n8n-nodes-langchain.mcpClientTool - mcpClientTool
Config choices: Version 1

Block 4 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

Block 5 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 6 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

3. Summary Table

Workflow	Test WAF security interactively with an AI agent and WAFtester MCP
Complexity	intermediate
Nodes	6
Categories	SecOps, AI Chatbot
Author	Qandil
Published	16 Feb 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/13443/13443.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source SecOps workflows AI Chatbot workflows

Frequently asked questions

What does Test WAF security interactively with an AI agent and WAFtester MCP do?

What it does A conversational AI agent that connects to WAFtester via MCP (Model Context Protocol) for interactive Web Application Firewall security testing. Type natural l...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your SecOps, AI Chatbot use case.

Qandil

3 workflows

Nodes

@n8n/n8n-nodes-langchain.chattrigger @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.mcpclienttool @n8n/n8n-nodes-langchain.lmchatopenai n8n-nodes-base.stickynote

Complexity

intermediate

Published 16 Feb 2026

Likes 0

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Install path: /data/workflows/13443/13443.json

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Test WAF security interactively with an AI agent and WAFtester MCP

Workflow preview

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

What it does

About WAFtester

Who it's for

How it works

Key capabilities

Example prompts

How to set up

Requirements

Links

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Chat Trigger

Block 2 - AI Agent

Block 3 - WAFtester MCP

Block 4 - OpenAI Chat Model

Block 5 - Sticky Note

Block 6 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions