This article provides a complete, practical walkthrough of the Limit Webhook Automation 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:
   Automating Email Header Analysis with n8n: Uncovering Sender Reputation, IP Origin, and Authentication Status
   
   Meta Description:
   Discover how to build an automated email header analysis workflow using n8n. Learn how it extracts email authentication results (SPF, DKIM, DMARC), checks IP reputation, and integrates with third-party APIs for secure email intelligence.
   
   Keywords:
   n8n, email header analysis, SPF, DKIM, DMARC, IPQualityScore, IP geolocation API, email security, Gmail webhook, email authentication, email automation, IP reputation, anti-phishing, spam detection, automate email analysis
   
   Third-Party APIs Used:
   
   1. IPQualityScore API
      - Used to assess the sender IP’s fraud score and determine spam, proxy use, and overall reputation.
      - Endpoint: https://ipqualityscore.com/api/json/ip/
   
   2. IP-API
      - Used to retrieve geographic and organizational data of the sender's IP address.
      - Endpoint: http://ip-api.com/json/
   
   Article:
   
   🛡️ Automated Email Header Analysis & IP Reputation Scoring Using n8n
   
   In a world increasingly plagued by phishing scams and email spoofing, understanding the source and authenticity of incoming emails is vital. Whether you're an individual wanting peace of mind from unsolicited emails or an enterprise developer building API systems to analyze inbound email data, automating email header analysis should be part of your toolkit. 
   
   This is where n8n, an open-source automation platform, shines. Leveraging its visual, no-code workflow environment, you can automate the extraction and interpretation of email headers, validate sender reputation, and analyze key security indicators like SPF, DKIM, and DMARC. This article walks you through an advanced n8n workflow built exactly for that purpose: a complete email inspection pipeline – from inbox to webhook.
   
   🔍 Workflow Overview
   
   The email analysis workflow has two entry points:
   
   1. Gmail Trigger Node (Test Mode) – Periodically polls Gmail for new messages.
   2. Webhook Node (Production Mode) – Accepts HTTP POST requests from third-party systems.
   
   Both trigger paths initiate the same core logic: processing email headers to extract relevant security details and IP reputation insights.
   
   📨 Extracting Email Headers
   
   The kickoff involves isolating email headers via custom n8n Set nodes like Set Gmail Headers and Set Gmail Webhook Headers. These headers are then funneled through the Extract Received Headers node—a JavaScript node that targets "Received" headers in the email’s metadata.
   
   The workflow features an important optimization stage. Multiple "Received" headers are common in emails due to server hops. To pinpoint the true origin, we strip private/internal IP entries and focus exclusively on the last meaningful public IP, ensuring we examine the true sender using regex patterns in Extract Original From IP.
   
   🌍 Scanning IP Reputation and Geo-Location
   
   Once the originating IP is found (if available):
   
   - 📡 IPQualityScore API is called to determine the sender's fraud score. This service checks whether the IP is known for sending spam, using proxies, or engaging in malicious activities. Based on the fraud score, the script classifies sender reputation as Good, OK, Suspicious, Poor, or Bad.
     
   - 🗺️ IP-API is queried next to append geographic intelligence, like the sender's country, city, and organization.
   
   This combination of reputation and location data builds a clearer picture of the sender's trustworthiness.
   
   🔐 Authentication Analysis: SPF, DKIM, DMARC
   
   Authentication headers are essential to email integrity. The workflow scans three main indicators:
   
   1. ✅ SPF (Sender Policy Framework)
      - Evaluated from either the Authentication-Results or the Received-SPF header.
      - Status determined as pass, fail, neutral, or unknown.
   
   2. ✅ DKIM (DomainKeys Identified Mail)
      - Identified through the "DKIM-Signature" header detection.
      - Confirmed as present, missing, or categorized by pass/fail in Authentication-Results.
   
   3. ✅ DMARC (Domain-based Message Authentication Reporting & Conformance)
      - Parsed from the "Authentication-Results" header (and, if necessary, custom “dmarc” headers).
      - Outcome set as pass, fail, or not found.
   
   All authentication results undergo parsing using Set and Code nodes that ensure uniform categorical output, which can be easily interpreted further or used by connected applications.
   
   🧠 Data Aggregation & Response Structuring
   
   To neatly conclude the workflow:
   
   - Outputs from SPF, DKIM, and DMARC sections are merged using n8n's Merge and Aggregate nodes.
   - These are formatted with metadata — including IP, geographic location, sender organization, and spam status — using Format Individual Auth Outputs1 and Format Combined Auth Output1 nodes.
   - Finally, Format Output ensures the final JSON matches expectations for consumption by client apps.
   - Respond to Webhook node triggers the response, completing the REST API loop.
   
   Core Data Points Delivered:
   
   - SPF / DKIM / DMARC status
   - Sender’s initial IP
   - IP reputation
   - Recent spam activity
   - Location (Country, City)
   - Organization
   
   🌐 Real-World Application Scenarios
   
   - ✅ SaaS platforms integrating email verification in onboarding workflows.
   - ✅ Helpdesk systems tagging and flagging suspicious sender sources.
   - ✅ Cybersecurity analysts automating header forensics.
   - ✅ Developers embedding mail authenticity analysis into APIs.
   
   🛠️ Final Thoughts
   
   This n8n workflow flawlessly combines third-party security APIs with Gmail's rich header data, delivering a powerful email scrutiny engine. Whether used for internal security or exposed as a public webhook-driven API, this system helps businesses and individuals sidestep email spoofing, identify harmful sender origins, and maintain inbox trust.
   
   By building on an open-source automation platform, you also retain flexibility and full visibility—a must in today’s privacy-aware world.
   
   Activate, integrate, and stay ahead of malicious senders. Email analysis just got smarter with n8n.
   
   — End of Article —

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.