This article provides a complete, practical walkthrough of the Code Webhook Send 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: Detecting IP Reputation and Spoofing Threats
   
   Meta Description:
   Discover how this n8n workflow automates the analysis of email headers to detect IP reputation issues, assess spoofing risks using SPF, DKIM, and DMARC, and perform real-time scoring with external APIs.
   
   Keywords:
   email security automation, n8n email analysis, IP reputation check, SPF DKIM DMARC analysis, spoofing detection, header analysis, fraud score API, IP geolocation API, cyber threat mitigation, email authentication workflow, IP Quality Score, IP-API, email spoof prevention
   
   Third-Party APIs Used:
   
   - IPQualityScore API (https://www.ipqualityscore.com)
     Used to retrieve fraud scores, assess whether an IP is involved in spam or abuse, determine TOR usage, and understand sender reputation.
   
   - IP-API (http://ip-api.com)
     Used to gather ISP and geolocation data of each IP address found in email headers.
   
   Article:
   
   Strengthening Email Security Through Automated Header Analysis in n8n
   
   In today's threat-laden email landscape, identifying spoofed messages and preventing malicious actors from infiltrating inboxes is more critical than ever. Security Operations (SecOps) teams increasingly rely on automation to identify threats buried within emails. Enter n8n, a powerful low-code workflow automation tool, which can be configured to automatically analyze email headers, validate sender authenticity, and assess the reputation of IP addresses. This article explores a comprehensive n8n workflow titled "Analyze_email_headers_for_IPs_and_spoofing__3", designed specifically to automate these investigative tasks.
   
   Overview of the Workflow
   
   The workflow triggers when email headers are received via a webhook. From there, it splits into two parallel investigative branches:
   
   1. IP Address Reputation Analysis
   2. Email Authentication Checks (SPF, DKIM, and DMARC)
   
   By the end of the workflow, both data sets are merged and presented in a clean JSON format, providing a clear verdict on the origin and trustworthiness of an email.
   
   IP-Based Threat Detection
   
   The process begins by extracting IP addresses from Received headers using a custom JavaScript node. A regular expression is used to capture all IPv4 addresses mentioned during the email's routing journey. These IPs are then analyzed individually using external APIs.
   
   - IPQualityScore: This API determines the "fraud_score" of an IP address along with its history in spam, abuse, or TOR usage. Based on the fraud score, the custom Fraud Score node in the workflow assigns a sender reputation such as “Good,” “Suspicious,” or “Bad.” For example, an IP with a fraud_score over 85 is flagged as having recent spam activity and marked as high risk.
   
   - IP-API: Each IP is then sent to IP-API to gather ISP and organization data, increasing visibility into the source of the email. This also helps identify shady hosting services or proxies often used in phishing campaigns.
   
   Once the data is gathered and scored, it’s consolidated into insightful IP profiles featuring attributes like organization, fraud_score, recent abuse activity, sender reputation, and more.
   
   Email Authentication Mechanism Checks
   
   While IP analysis is valuable, verifying that an email’s sender is who they claim to be is equally important. The second part of the workflow focuses on standard email authentication techniques:
   
   - SPF (Sender Policy Framework): Validates whether the sending IP is authorized to send emails on behalf of the claimed domain. It does this by analyzing both the “received-spf” and “authentication-results” headers.
     
   - DKIM (DomainKeys Identified Mail): Checks that the email’s contents have not been altered in-transit and verifies the digital signature using the "dkim-signature" header.
     
   - DMARC (Domain-based Message Authentication, Reporting & Conformance): Acts as an enforcement mechanism once SPF and DKIM are validated, providing policies for handling failed authentication.
   
   If these records are missing or fail validation, the system categorizes the email accordingly, tagging it with a "fail," "pass," "neutral," or "unknown" status for each record type.
   
   Data Aggregation and Output
   
   After IP-based and authentication-based analyses complete independently, the workflow aggregates the results. Using a combination of n8n’s "merge" and "itemLists" nodes, the outputs from both branches are combined into one cohesive JSON object.
   
   Example Output:
   
   [
     {
       "ipAnalysis": [
         {
           "IP": "104.245.209.248",
           "fraud_score": 87,
           "recent_abuse": true,
           "Organization": "Deft Hosting",
           "tor": false,
           "ISP": "Server Central Network",
           "recent_spam_activity": "Identified spam in the past 24-48 hours",
           "ip_sender_reputation": "Bad"
         }
       ]
     },
     {
       "spf": "fail",
       "dkim": "not-found",
       "dmarc": "fail"
     }
   ]
   
   This output provides immediate insight into whether an email can be trusted based on sender IP reputation and domain-level authentication.
   
   Highlights of the Workflow:
   
   - Fully automated analysis of email headers via webhook input
   - IP extraction and validation using regex and external APIs
   - Real-time assessment of spam risk and IP fraud likelihood
   - Validation of SPF, DKIM, and DMARC records to determine sender authenticity
   - Consolidated response including readable metadata for human or machine consumption
   
   Usage and Deployment Considerations
   
   Security professionals or IT teams can deploy this workflow as a standalone threat analysis tool or integrate it into larger systems using n8n’s Execute Workflow node. Free API tiers exist for both IPQualityScore and IP-API, making this solution accessible even for individuals or small organizations.
   
   Final Thoughts
   
   This n8n workflow elegantly combines real-time threat intelligence with email authentication analysis to provide a powerful security automation pipeline. In an era of rampant email fraud and phishing attempts, automating header analysis not only saves time but significantly strengthens your defenses. Whether you are building a SecOps toolkit or just want more insight into your incoming emails, this open-source solution exemplifies how low-code automation platforms can democratize cybersecurity.

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.