This article provides a complete, practical walkthrough of the Limit Code Create Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Automated Email Header Analysis with n8n: Validating Email Authenticity via SPF, DKIM, DMARC, and IP Reputation
   
   Meta Description:  
   Explore how an advanced n8n workflow automates the analysis of email headers to verify SPF, DKIM, and DMARC compliance, extract the sender's IP address, and check IP reputation using external APIs like Microsoft Graph, IP-API, and IPQualityScore.
   
   Keywords:  
   n8n email workflow, email header analysis, email authentication, SPF DKIM DMARC check, IP reputation lookup, n8n Microsoft Graph API, n8n IPQualityScore, verify email spoofing, email security automation, n8n webhook integration
   
   Third-Party APIs Used:
   
   1. Microsoft Graph API (Outlook)
      - Retrieves raw email headers for analysis.
   
   2. IPQualityScore API
      - Assesses the reputation and fraud likelihood of the sender’s IP address.
   
   3. IP-API
      - Provides geolocation and organization data for the sender’s IP address.
   
   Short Article:
   
   Automated Email Header Analysis with n8n: Ensuring Sender Legitimacy Through Authentication and IP Intelligence
   
   In the age of rampant email spoofing and phishing attacks, validating the authenticity of incoming emails is more critical than ever. A powerful way to automate this validation process is through n8n—a fair-code workflow automation platform. With this platform, users can design detailed flows to extract, process, and analyze email headers against SPF, DKIM, DMARC records, and assess the sender IP’s reputation. In this article, we break down an advanced n8n workflow designed to do exactly that.
   
   Understanding the Workflow
   
   The workflow operates in two primary modes: as a test tool using Microsoft Outlook integration, and in production via a webhook that accepts header data from third-party sources.
   
   The initial phase—appropriate for testing—uses the Outlook Nodes with Microsoft Graph API to monitor a specific folder. When a new email arrives, the workflow extracts the full set of headers and organizes them into a format suitable for automated parsing.
   
   Once live, the workflow features a webhook endpoint that receives headers in a standardized structure via HTTP POST. This enables seamless integration with external platforms such as ticketing systems, CRMs, or SIEM tools.
   
   Extracting the Originating IP
   
   One of the core components of this workflow is the ability to determine the original sender's IP address. The workflow achieves this by inspecting the Received headers—sequential metadata added by each email server the message went through. The n8n nodes isolate the most recent public IP address, excluding internal and private address ranges (e.g., 192.168.x.x), ensuring that a legitimate origin can be determined.
   
   Once isolated, this IP address becomes the key to unlocking additional layers of intelligence.
   
   IP Reputation & Geo-Intelligence
   
   After successfully extracting the sender’s IP, two key APIs are engaged:
   
   1. IPQualityScore: This API assesses the IP’s reputation against a variety of spam behavior signatures. It delivers a fraud score, indicating whether the IP has been linked to spam or suspicious activity in recent hours or days. This adds a behavioral context to the raw header data.
   
   2. IP-API: Adds geographical metadata by pulling the organization name and geolocation (country, city) tied to the IP. This can assist in anomaly detection—for instance, identifying if an email claiming to be from a corporate domain originated from an unrelated geography.
   
   Parsing Authentication Results: SPF, DKIM, and DMARC
   
   Next, the workflow evaluates if standard email authentication methods were applied and whether they passed:
   
   - SPF (Sender Policy Framework): Determines if the IP address is authorized to send on behalf of the sender’s domain.
   - DKIM (DomainKeys Identified Mail): Checks if the message includes a valid digital signature.
   - DMARC (Domain-based Message Authentication, Reporting, and Conformance): Tells the receiving server what to do if SPF or DKIM fails.
   
   The system searches for the presence of key headers: Authentication-Results, Received-SPF, DKIM-Signature, and dmarc. It dynamically evaluates their respective values—categorizing them as pass, fail, unknown, or not found.
   
   The workflow includes logic branches to handle each authentication path gracefully, ensuring that even when specific headers are missing, valid fallback paths and results are generated.
   
   Formatting and Responding with Results
   
   In the final segment of the workflow, results are merged and transformed into a unified JSON structure containing:
   
   - SPF, DKIM, and DMARC verdicts
   - Extracted original IP address
   - IP geolocation: country, city, and organization
   - Recent spam activity
   - IP sender reputation (Good, OK, Suspicious, Poor, or Bad)
   
   These insights are then returned via the webhook response, which can be consumed by downstream systems or security tools.
   
   Why This Matters
   
   This workflow offers a comprehensive, automated solution that transforms complex email metadata into digestible, actionable intelligence. It’s a low-code, scalable approach requiring minimal maintenance, yet it delivers enterprise-grade validation for potentially malicious or spoofed emails.
   
   With integrations to powerful APIs like Microsoft Graph, IPQualityScore, and IP-API, this n8n workflow gives infosec teams and email administrators a major edge in identifying and understanding suspicious messages without manual intervention.
   
   Final Thoughts
   
   Whether you're building an abuse detection tool, securing internal communications, or validating support emails in a helpdesk system, this email header analysis workflow with n8n can automate and scale your efforts. As email security continues to be a primary concern across industries, automated solutions like these illustrate just how accessible robust protections can be—thanks to modern tools and open APIs.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.