This article provides a complete, practical walkthrough of the Code Microsoftoutlook 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:
   Automating Phishing Email Detection and Reporting with n8n, ChatGPT, and Jira
   
   Meta Description:
   Discover how to build a powerful, automated phishing detection and reporting workflow using n8n, Gmail, Outlook, hcti.io, ChatGPT-4, and Jira. Learn how this integration analyzes suspicious emails and creates incident tickets with screenshots and AI insights.
   
   Keywords:
   n8n workflow, phishing detection, email automation, Gmail integration, Outlook integration, ChatGPT email analysis, hcti.io screenshot API, Jira automation, cybersecurity workflow, AI phishing analysis
   
   Third-Party APIs Used:
   
   1. Gmail (via Gmail Trigger node)
   2. Microsoft Outlook (via Microsoft Outlook Trigger and Graph API)
   3. hcti.io API (HTML/CSS to Image Screenshot API)
   4. OpenAI ChatGPT API (AI-based phishing analysis)
   5. Jira Software Cloud API (Ticket creation and attachment upload)
   
   Short Article:
   
   Automating Phishing Detection and Reporting with n8n, ChatGPT, and Jira
   
   In the modern digital workplace, phishing emails remain one of the most common cyber threats. Detecting and responding to them quickly is critical for organizational security—but doing this manually is slow and error-prone. That’s where n8n, an open-source workflow automation platform, shines. With n8n, you can orchestrate a fully automated phishing email detection and reporting process using a combination of real-time email monitoring, AI analysis, screenshot visualization, and Jira ticket creation. Let’s break down how this sophisticated yet streamlined automation works.
   
   Step 1: Real-Time Email Monitoring via Gmail and Outlook
   
   The workflow begins with email monitoring triggers. Both Gmail and Microsoft Outlook are supported, allowing the automation to watch for incoming emails on either platform every minute. Although in this workflow, the Microsoft Outlook Trigger node is disabled, its setup remains available and functional.
   
   When an email is received via Gmail, the Gmail Trigger node captures vital components such as the HTML body, recipient, subject, headers, and plain text content. The Set Gmail Variables node processes and stores these details for downstream processing. If Outlook were active, a similar process would occur—headers are retrieved via the Microsoft Graph API and structured through a custom code block, then stored using the Set Outlook Variables node.
   
   Step 2: Visualizing Email Content with hcti.io
   
   Once the email details are parsed, the workflow creates a visual screenshot of the message. This is particularly useful for analyst reviews and documentation. The Screenshot HTML node sends the email’s HTML body to the hcti.io API, which returns a rendered image of the email. This image is then fetched by the Retrieve Screenshot node for later use.
   
   While using hcti.io offers convenience and quality rendering, it does send email content to an external service. For organizations with strict data privacy requirements, this step could be localized using CLI tools like Puppeteer if you’re self-hosting n8n.
   
   Step 3: AI-Powered Email Analysis with ChatGPT
   
   With a visual representation of the email and its headers, the workflow then leverages artificial intelligence through OpenAI’s ChatGPT-4. The ChatGPT Analysis node submits the screenshot and email headers to the AI model with a specific prompt: assess whether the email is a potential phishing attempt. The result is a human-readable diagnosis formatted explicitly for Jira’s wiki-style ticket renderer.
   
   AI analysis adds an intelligent layer to the workflow, increasing the reliability and speed of determining phishing risk—without involving your cybersecurity team in every email report.
   
   Step 4: Automated Incident Ticket Creation in Jira
   
   Upon receiving the AI analysis, the automation creates a new Jira ticket using the Create Jira Ticket node. The ticket includes:
   
   - The email subject line
   - The reporting recipient
   - The original text body of the email
   - ChatGPT’s phishing analysis
   
   To enrich the ticket further, a Rename Screenshot node ensures the email’s visual screenshot is labeled appropriately, and the Upload Screenshot of Email to Jira node attaches it to the issue. The result is a fully documented phishing report ready for your IT or security team to evaluate and resolve.
   
   Why This Workflow Matters
   
   By combining several powerful services, this n8n workflow saves time, reduces human error, and boosts your organization’s ability to respond to phishing threats proactively. Some of the key benefits include:
   
   - Real-time email monitoring across Gmail and Outlook
   - Visual documentation of emails through screenshots
   - AI-based phishing assessment via ChatGPT-4
   - Comprehensive and formatted Jira ticket creation
   - Scalable and customizable framework for cybersecurity defense
   
   Final Thoughts
   
   This workflow is a shining example of how automation and AI can improve cybersecurity operations. Whether you serve IT, InfoSec, or DevOps, integrating these technologies into your email infrastructure can significantly enhance your organization’s security posture. Best of all, with n8n's node-based logic and open-source flexibility, the entire system is transparent and extensible to your particular needs.
   
   If your organization isn’t yet automating email threat analysis, now’s the time to start—and this n8n template provides a powerful head start.

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.