Detection: Gsuite Email Suspicious Subject With Attachment

Updated Date: 2024-09-30 ID: 8ef3971e-00f2-11ec-b54f-acde48001122 Author: Teoderick Contreras, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

The following analytic identifies Gsuite emails with suspicious subjects and attachments commonly used in spear phishing attacks. It leverages Gsuite email logs, focusing on specific keywords in the subject line and known malicious file types in attachments. This activity is significant for a SOC as spear phishing is a prevalent method for initial compromise, often leading to further malicious actions. If confirmed malicious, this activity could result in unauthorized access, data exfiltration, or further malware deployment, posing a significant risk to the organization's security.

 1`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") 
 2| rex field=source.from_header_address "[^@]+@(?<source_domain>[^@]+)" 
 3| rex field=destination{}.address "[^@]+@(?<dest_domain>[^@]+)" 
 4| where not source_domain="internal_test_email.com" and dest_domain="internal_test_email.com" 
 5| eval phase="plan" 
 6| eval severity="medium" 
 7| 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 
 8| `security_content_ctime(firstTime)` 
 9| `security_content_ctime(lastTime)` 
10| `gsuite_email_suspicious_subject_with_attachment_filter`

Data Source

Name Platform Sourcetype Source
G Suite Gmail N/A 'gsuite:gmail:bigquery' 'http:gsuite'

Macros Used

Name Value
gsuite_gmail sourcetype=gsuite:gmail:bigquery
gsuite_email_suspicious_subject_with_attachment_filter search *
gsuite_email_suspicious_subject_with_attachment_filter is an empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.

Annotations

- MITRE ATT&CK
+ Kill Chain Phases
+ NIST
+ CIS
- Threat Actors
ID Technique Tactic
T1566.001 Spearphishing Attachment Initial Access
T1566 Phishing Initial Access
KillChainPhase.DELIVERY
NistCategory.DE_AE
Cis18Value.CIS_10
APT-C-36
APT1
APT12
APT19
APT28
APT29
APT30
APT32
APT33
APT37
APT38
APT39
APT41
Ajax Security Team
Andariel
BITTER
BRONZE BUTLER
BlackTech
CURIUM
Cobalt Group
Confucius
DarkHydrus
Darkhotel
Dragonfly
EXOTIC LILY
Elderwood
FIN4
FIN6
FIN7
FIN8
Ferocious Kitten
Gallmaker
Gamaredon Group
Gorgon Group
Higaisa
Inception
IndigoZebra
Kimsuky
Lazarus Group
LazyScripter
Leviathan
Machete
Malteiro
Mofang
Molerats
Moonstone Sleet
MuddyWater
Mustang Panda
Naikon
Nomadic Octopus
OilRig
PLATINUM
Patchwork
RTM
Rancor
RedCurl
Saint Bear
Sandworm Team
SideCopy
Sidewinder
Silence
Star Blizzard
TA2541
TA459
TA505
TA551
The White Company
Threat Group-3390
Tonto Team
Transparent Tribe
Tropic Trooper
WIRTE
Windshift
Winter Vivern
Wizard Spider
admin@338
menuPass
Axiom
GOLD SOUTHFIELD
INC Ransom

Default Configuration

This detection is configured by default in Splunk Enterprise Security to run with the following settings:

Setting Value
Disabled true
Cron Schedule 0 * * * *
Earliest Time -70m@m
Latest Time -10m@m
Schedule Window auto
Creates Risk Event True
This configuration file applies to all detections of type anomaly. These detections will use Risk Based Alerting.

Implementation

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

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
Suspicious email from $source.address$ to $destination{}.address$ 25 50 50
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.

References

Detection Testing

Test Type Status Dataset Source Sourcetype
Validation ✅ Passing N/A N/A N/A
Unit ✅ Passing Dataset http:gsuite gsuite:gmail:bigquery
Integration ✅ Passing Dataset http:gsuite gsuite:gmail:bigquery

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

Source: GitHub | Version: 3