+8
Analyze Email Headers for IP Reputation and Spoofing Detection - Outlook
Published 6 days ago
Created by
Angel Menendez
Categories
Template description
Analyze Emails for Security Insights
Who is this for?
This workflow is ideal for security teams, IT Ops professionals, and managed service providers (MSPs) responsible for monitoring and validating email traffic. It’s especially useful for organizations that need to identify potential phishing attempts, spam, or compromised accounts by analyzing email headers and IP reputation.
What problem is this workflow solving?
This workflow helps identify malicious or suspicious emails by verifying email authentication headers (SPF, DKIM, DMARC) and analyzing the reputation of the originating IP address. By automating these checks, it reduces manual analysis time and flags potential threats efficiently.
What this workflow does
- Email Monitoring: Polls a specified Microsoft Outlook folder for new emails in real-time.
- Header Analysis: Retrieves and processes email headers to extract critical information such as authentication results and the sender’s IP address.
- IP Reputation Check: Leverages external APIs (IP Quality Score and IP-API) to analyze the originating IP for potential spam or malicious activity.
- Authentication Validation: Validates SPF, DKIM, and DMARC headers, determining if the email passes industry-standard authentication protocols.
- Data Aggregation and Reporting: Combines all analyzed data into a unified format, ready for reporting or integration into downstream systems.
- Webhook Integration: Outputs the findings via a webhook, enabling integration with alerting tools or security information and event management (SIEM) platforms.
Setup
-
Connect to Outlook:
- Configure the Microsoft Outlook trigger node with valid OAuth2 credentials.
- Specify the email folder to monitor for new messages.
-
API Keys (Optional):
- Obtain an API key for IP Quality Score (https://ipqualityscore.com).
- Ensure the IP-API endpoint is accessible.
- This step is optional as ipqualityscore.com will provide a limited number of free lookups each month. See more details here.
-
Webhook Configuration:
- Set up a webhook endpoint to receive the output of the workflow.
-
Optional Adjustments:
- Customize polling intervals in the trigger node.
- Modify header filters or extend the validation logic as needed.
How to customize this workflow to your needs
- Add Alerts: Use the
Respond to Webhooknode to trigger notifications in Slack, email, or any other communication channel. - Integrate with SIEM: Forward the workflow output to SIEM tools like Splunk or ELK Stack for further analysis.
- Modify Validation Rules: Update SPF, DKIM, or DMARC logic in the
Setnodes to align with your organization’s security policies. - Expand IP Analysis: Add more APIs or services to enrich IP reputation data, such as VirusTotal or AbuseIPDB.
This workflow provides a robust foundation for email security monitoring and can be tailored to fit your organization's unique requirements. With its modular design and integration options, it’s a versatile tool to enhance your cybersecurity operations.
Share Template
More SecOps workflow templates
+4
Phishing Analysis - URLScan.io and VirusTotal
This n8n workflow automates the analysis of email messages received in a Microsoft Outlook inbox to identify indicators of compromise (IOCs), specifically suspicious URLs. It can be triggered manually or scheduled to run daily at midnight.
The workflow begins by retrieving up to 100 read email messages from the Outlook inbox. However, there seems to be a configuration issue as it should retrieve unread messages, not read ones. It then marks these messages as read to avoid processing them again in the future.
The messages are then split into individual items using the Split In Batches node for sequential processing. For each email, the workflow analyzes its content to find URLs, which are considered potential IOCs. If URLs are found, the workflow proceeds to check these URLs for potential threats using two services, URLScan.io and VirusTotal, in parallel.
In the first path, URLScan.io scans each URL, and if there are no errors, the results from URLScan.io and VirusTotal are merged. If there are errors, the workflow waits 1 minute before attempting to retrieve the URLScan results again. The loop then continues for the next email. In the second path, VirusTotal is used to scan the URLs, and the results are retrieved.
Finally, the workflow checks if the data field is not empty, filtering out items where no data was found. It then sends a summarized Slack message to report details about the analyzed email, including the subject, sender, date, URLScan report URL, and VirusTotal verdict for URLs that were reported as malicious.
Potential issues during setup include configuring the Outlook node to retrieve unread messages, resolving a configuration issue in the VirusTotal node, and handling authentication and API keys for both URLScan.io and VirusTotal nodes. Additionally, proper error handling and testing with various email content types and URLs are essential to ensure the workflow accurately identifies IOCs and reports them to the Slack channel.
n8n Team
+4
Automate Image Validation Tasks using AI Vision
This n8n workflow shows how using multimodal LLMs with AI vision can tackle tricky image validation tasks which are near impossible to achieve with code and often impractical to be done by humans at scale.
You may need image validation when users submitted photos or images are required to meet certain criteria before being accepted. A wine review website may require users only submit photos of wine with labels, a bank may require account holders to submit scanned documents for verification etc.
In this demonstration, our scenario will be to analyse a set of portraits to verify if they meet the criteria for valid passport photos according to the UK government website (https://www.gov.uk/photos-for-passports).
How it works
Our set of portaits are jpg files downloaded from our Google Drive using the Google Drive node.
Each image is resized using the Edit Image node to ensure a balance between resolution and processing speed.
Using the Basic LLM node, we'll define a "user message" option with the type of binary (data). This will allow us to pass our portrait to the LLM as an input.
With our prompt containing the criteria pulled off the passport photo requirements webpage, the LLM is able to validate the photo does or doesn't meet its criteria.
A structured output parser is used to structure the LLM's response to a JSON object which has the "is_valid" boolean property. This can be useful to further extend the workflow.
Requirements
Google Gemini API key
Google Drive account
Customising this workflow
Not using Gemini? n8n's LLM node works with any compatible multimodal LLM so feel free to swap Gemini out for OpenAI's GPT4o or Antrophic's Claude Sonnet.
Don't need to validate portraits? Try other use cases such as document classification, security footage analysis, people tagging in photos and more.
Jimleuk
Analyze emails with S1EM
With workflow, you analyze Email with TheHive/Cortex
https://github.com/V1D1AN/S1EM/wiki/Soar-guide
v1d1an
+7
URL and IP lookups through Greynoise and VirusTotal
This n8n workflow serves as a powerful cybersecurity and threat intelligence tool to look up URLs or IP addresses through industry standard threat intelligence vendors. It starts with either a form submission or a webhook trigger, allowing users to input data, URLs or IPs that require analysis. The workflow then splits into two paths depending on whether the input data is an IP or URL. If an IP was given, it sets the ip variable to the IP; however if a URL was given the workflow will perform a DNS lookup using Google Public DNS and sets the ip variable based on the results from Google.
The workflow then checks the obtained IP addresses against GreyNoise services, with one branch utilizing GreyNoise RIOT IP Lookup to assess IP reputation and association with known benign services, and the other using GreyNoise IP Context to evaluate potential threats. The results from both GreyNoise services are merged to create a comprehensive analysis which includes the IP, classification (benign, malicious, or unknown), IP location, tags to identify activity or malware, category, and trust level.
In parallel, a VirusTotal scan is initiated for the URL/IP to identify if it is malicious. A 5-second wait ensures proper processing, and the workflow subsequently polls the scan result to determine when the analysis is complete. The workflow then summarizes the analysis including the overall security vendor analysis results, blockList analysis, OpenPhish analysis, the URL, and the IP.
Finally, the workflow combines the summarized intelligence from both GreyNoise and VirusTotal to provide a thorough analysis of the URL/IP. This summarized intelligence can then be emailed to the user that filled out the form via Gmail or it can be sent to the user via a Slack message.
Setting up this workflow may require proper configuration of the form submission or webhook trigger, and ensuring that the GreyNoise and VirusTotal API credentials are correctly integrated. Users should also consider the potential volume of data and API rate limits, as excessive requests could lead to issues. Proper documentation and validation of input data are crucial to ensure accurate and meaningful results in the final report.
n8n Team
+3
Authenticate a user in a workflow with openid connect
Intro
This workflow needs a user to authenticate by using an openid connect provider in order to call the webhook.
If the user is not authenticated, it starts a login process by using an Authorization Code with PKCE https://datatracker.ietf.org/doc/html/rfc7636, a standard way to authenticate users with openid connect.
Then, after the user logs in, the webhook is refreshed and gets the user's token from a cookie. With this token, all details about the user are requested through the userinfo endpoint on the identity provider.
How to set up with Keycloak
Keycloak Keycloak is an open source identity and access management solution.
Feel free to get a demo realm at https://please-open.it or get your own Keycloak server up and running.
After creating a realm, go to "Realm Settings" and click on "OpenID Endpoint Configuration"
Retrieve authorization_endpoint, token_endpoint and userinfo_endpoint values. Set those variables in the "Set variables" node.
In Keycloak, create a new client (name it as you want)
Disable the client authentication, check only "standard flow" :
At the third step, put the webhook url in "valid redirect URIs", fill "Web origins" with a "+".
You're done, open the webhook and it asks you to authenticate.
Usage
User informations
The userinfo node returns this structure about the user has logged in :
[
{
"sub":"73a6543f-f420-4fa6-9811-209e903c348b",
"email_verified":true,
"preferred_username": "[email protected]",
"email": "[email protected]"
}
]
I can use those infos in my workflow for custom operations.
APIs calls
the "code" node returns me a cookie named "n8n-custom-auth" which is the access_token returned by the identity provider. This access_token can be used to call APIs connected to this identity provider (for example, we call userinfo API with this token).
Example : asks a user to log in with his Google account then call an API (Gmail, drive...) with his own token.
How it works
We published a blog post about this flow, how it works and how you can use it :
https://blog.please-open.it/n8n-openid-client/
please-open.it
+3
Analyze Email Headers for IPs and Spoofing
This n8n workflow is designed to analyze email headers received via a webhook. The workflow splits into two main paths based on the presence of the received and authentication results headers.
In the first path, if received headers are present, the workflow extracts IP addresses from these headers and then queries the IP Quality Score API to gather information about the IP addresses, including fraud score, abuse history, organization, and more. Geolocation data is also obtained from the IP-API API. The workflow collects and aggregates this information for each IP address.
In the second path, if authentication-results headers are present, the workflow extracts SPF, DKIM, and DMARC authentication results. It then evaluates these results and sets fields accordingly (e.g., SPF pass/fail/neutral).
The paths merge their results, and the workflow responds to the original webhook with the aggregated analysis, including IP information and authentication results.
Potential issues during setup include ensuring proper configuration of the webhook calls with header authentication, handling authentication and API keys for the IP Quality Score API, and addressing any discrepancies or errors in the logic nodes, such as handling SPF, DKIM, and DMARC results correctly. Additionally, thorough testing with various email header formats is essential to ensure accurate analysis and response.
n8n Team
