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Description

This search is to detect a gsuite email contains suspicious subject having known file type used in spear phishing. This technique is a common and effective entry vector of attacker to compromise a network by luring the user to click or execute the suspicious attachment send from external email account because of the effective social engineering of subject related to delivery, bank and so on. On the other hand this detection may catch a normal email traffic related to legitimate transaction so better to check the email sender, spelling and etc. avoid click link or opening the attachment if you are not expecting this type of e-mail.

  • Type: Anomaly

  • Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud

  • Last Updated: 2021-08-19
  • Author: Teoderick Contreras, Splunk
  • ID: 8ef3971e-00f2-11ec-b54f-acde48001122

Annotations

ATT&CK

ATT&CK

ID Technique Tactic
T1566.001 Spearphishing Attachment Initial Access
T1566 Phishing Initial Access
Kill Chain Phase
  • Delivery
NIST
  • DE.AE
CIS20
  • CIS 10
CVE 


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`gsuite_gmail` num_message_attachments > 0 subject IN ("*dhl*", "* ups *", "*delivery*", "*parcel*", "*label*", "*invoice*", "*postal*", "* fedex *", "* usps *", "* express *", "*shipment*", "*Banking/Tax*","*shipment*", "*new order*") attachment{}.file_extension_type IN ("doc", "docx", "xls", "xlsx", "ppt", "pptx", "pdf", "zip", "rar", "html","htm","hta") 
| rex field=source.from_header_address "[^@]+@(?<source_domain>[^@]+)" 
| rex field=destination{}.address "[^@]+@(?<dest_domain>[^@]+)" 
| where not source_domain="internal_test_email.com" and dest_domain="internal_test_email.com" 
| eval phase="plan" 
| eval severity="medium" 
| stats count min(_time) as firstTime max(_time) as lastTime values(attachment{}.file_extension_type) as email_attachments, values(attachment{}.sha256) as attachment_sha256, values(payload_size) as payload_size by destination{}.service num_message_attachments  subject destination{}.address source.address phase severity 
| `security_content_ctime(firstTime)` 
| `security_content_ctime(lastTime)` 
| `gsuite_email_suspicious_subject_with_attachment_filter`

Macros

The SPL above uses the following Macros:

:information_source: gsuite_email_suspicious_subject_with_attachment_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Required fields

List of fields required to use this analytic.

  • _time

How To Implement

To successfully implement this search, you need to be ingesting logs related to gsuite having the file attachment metadata like file type, file extension, source email, destination email, num of attachment and etc.

Known False Positives

normal user or normal transaction may contain the subject and file type attachment that this detection try to search.

Associated Analytic Story

RBA

Risk Score Impact Confidence Message
25.0 50 50 suspicious email from $source.address$ to $destination{}.address$

:information_source: The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

Reference

Test Dataset

Replay any dataset to Splunk Enterprise by using our replay.py tool or the UI. Alternatively you can replay a dataset into a Splunk Attack Range

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