In today's fast-evolving threat landscape, phishing remains one of the most prevalent methods for attackers to gain unauthorized access to sensitive information. To counter this, organizations need efficient and scalable ways to analyze and respond to phishing emails. Using n8n, an open-source workflow automation tool, we can streamline the process of phishing email analysis and build an automated pipeline.
I’ll walk through a real-world phishing analysis workflow built using n8n that automates key tasks such as extracting email details, analyzing attachments, performing SPF, DKIM, and DMARC checks, and gathering reputation data on IPs and domains.
Why Automate Phishing Email Analysis?
Phishing email analysis can be a time-consuming task that involves multiple steps:
Gathering and parsing the email's metadata.
Analyzing attachments for malicious content.
Checking the sender’s authenticity using SPF, DKIM, and DMARC.
Investigating IP addresses and URLs found in the email for suspicious activity.
By automating these tasks, we reduce manual efforts, increase response time, and ensure consistent analysis across all reported phishing emails.
Workflow Breakdown
This n8n workflow focuses on automating the key tasks in phishing mail analysis, such as extracting email details, attachment analysis, SPF/DKIM/DMARC authentication checks, and reputation analysis using tools like VirusTotal.
1. Triggering the Workflow from Microsoft Outlook
The workflow starts by retrieving phishing emails from Microsoft Outlook. The Microsoft Outlook Trigger node polls the mailbox for any new phishing emails reported by users.
Node: Microsoft Outlook Trigger
Function: Fetch emails flagged as phishing from the user-reported mailbox.
2. Extracting Email Attachments
Once the email is retrieved, we need to download any attachments for further analysis. Malicious attachments are common vectors for phishing attacks.
Node: Get attachments & Download attachments
Function: Download all attachments associated with the phishing email for further investigation.
3. Extracting Key Email Metadata
Next, we extract essential email metadata, such as:
Sender’s Address
Subject
Email Body
Attachments
SPF, DKIM, and DMARC results
Node: Extract from File
Function: Parse the .eml file format to extract relevant fields for analysis.
4. Analyzing SPF, DKIM, and DMARC Authentication Results
Phishing attacks often spoof legitimate domains. SPF, DKIM, and DMARC help verify the authenticity of the email sender. The workflow checks if these authentication mechanisms pass or fail.
SPF (Sender Policy Framework): Ensures that the email is sent from an authorized server.
DKIM (DomainKeys Identified Mail): Confirms that the email has not been altered during transit.
DMARC (Domain-based Message Authentication, Reporting, and Conformance): Helps in identifying and preventing email spoofing.
Node: Split Out Authentication Result
Function: Splits and analyzes SPF, DKIM, and DMARC results from the email header.
5. Checking IP Reputation
The client IP, extracted from the email headers, is checked for reputation using VirusTotal. This helps identify if the IP has been flagged for any malicious activities in the past.
Node: Client IP
Function: Check the reputation of the client IP using VirusTotal.
Integration: VirusTotal API is used to check the reputation of both IP addresses and any URLs in the email.
6. X-Header Analysis
The workflow also checks for any suspicious non-standard headers (X-Headers) in the email. These headers may contain indicators of email manipulation or phishing attempts.
Node: X-Header Analysis
Function: Analyzes and validates the X-Headers to identify any anomalies.
7. Email Body Content and URL Analysis
Once the metadata is extracted, URLs in the email body are also checked using VirusTotal to determine if they point to malicious domains.
Node: Extracting Email Details
Function: Extract URLs and email body content for analysis using VirusTotal.
9. Reply-To and Return-Path Verification
Phishing attacks often attempt to spoof legitimate email addresses. One key defense mechanism is to check the Reply-To and Return-Path fields to ensure the sender's identity is legitimate.
Reply-To Address: This field can sometimes be used by attackers to redirect replies to a different address, even if the From address seems legitimate.
Return-Path: The Return-Path header is used to handle bounced messages and can give clues about email authenticity.
Node: Reply to and return-path verification details
Function: Verifies if the Reply-To and Return-Path addresses align with the original sender, ensuring that spoofing is not occurring. Any mismatches are flagged for further investigation.
8. Generating a Phishing Analysis Report
All the gathered information is compiled into a comprehensive phishing analysis report. The workflow converts the results into a readable report format, which can be sent for review or logged into a ticketing system.
Node: Converting phishing Analysis report to txt file
Function: Converts the extracted phishing analysis details into a text file report.
9. Automating Ticket Creation in Jira
The final step in the workflow involves creating a ticket in Jira for the security team, attaching the phishing report for further action.
Node: Generating ticket in Jira of phishing Report
Function: Automatically create a Jira ticket with the phishing report attached.
Complete phishing Email Analysis workflow using n8n
Automated phishing Email Analysis Report
Benefits of Automating Phishing Email Analysis
Efficiency: Automation reduces manual effort and speeds up the analysis process.
Consistency: Every email is analyzed systematically using the same process, ensuring no critical details are missed.
Seamless Integration: n8n allows integration with external tools like VirusTotal for reputation checks and Jira for ticketing.
Scalability: The workflow can handle an increasing volume of phishing emails without requiring additional manual resources.
Conclusion
Automating phishing email analysis with n8n improves your security team's response time and ensures thorough analysis of every phishing email. From extracting email details, verifying sender authenticity with SPF/DKIM/DMARC, and checking IP and domain reputations to generating comprehensive reports and automating ticket creation, this workflow simplifies phishing incident response and improves overall security posture.
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