Detection: Web Fraud - Anomalous User Clickspeed

DEPRECATED DETECTION

This detection has been marked as deprecated by the Splunk Threat Research team. This means that it will no longer be maintained or supported. If you have any questions or concerns, please reach out to us at research@splunk.com.

Updated Date: 2024-08-16 ID: 31337bbb-bc22-4752-b599-ef192df2dc7a Author: Jim Apger, Splunk Type: Anomaly Product: Splunk Enterprise Security

Description

This search is used to examine web sessions to identify those where the clicks are occurring too quickly for a human or are occurring with a near-perfect cadence (high periodicity or low standard deviation), resembling a script driven session.

1`stream_http` http_content_type=text* 
2| rex field=cookie "form_key=(?<session_id>\w+)" 
3| streamstats window=2 current=1 range(_time) as TimeDelta by session_id 
4| where TimeDelta>0 
5|stats count stdev(TimeDelta) as ClickSpeedStdDev avg(TimeDelta) as ClickSpeedAvg by session_id 
6| where count>5 AND (ClickSpeedStdDev<.5 OR ClickSpeedAvg<.5) 
7| `web_fraud___anomalous_user_clickspeed_filter`

Data Source

Name Platform Sourcetype Source Supported App
N/A N/A N/A N/A N/A

Macros Used

Name Value
stream_http sourcetype=stream:http
web_fraud___anomalous_user_clickspeed_filter search *
web_fraud___anomalous_user_clickspeed_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
T1078 Valid Accounts Defense Evasion
KillChainPhase.DELIVERY
KillChainPhase.EXPLOITAITON
KillChainPhase.INSTALLATION
NistCategory.DE_AE
Cis18Value.CIS_10
APT18
APT28
APT29
APT33
APT39
APT41
Akira
Axiom
Carbanak
Chimera
Cinnamon Tempest
Dragonfly
FIN10
FIN4
FIN5
FIN6
FIN7
FIN8
Fox Kitten
GALLIUM
Ke3chang
LAPSUS$
Lazarus Group
Leviathan
OilRig
POLONIUM
PittyTiger
Sandworm Team
Silence
Silent Librarian
Suckfly
Threat Group-3390
Wizard Spider
menuPass

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

Start with a dataset that allows you to see clickstream data for each user click on the website. That data must have a time stamp and must contain a reference to the session identifier being used by the website. This ties the clicks together into clickstreams. This value is usually found in the http cookie. With a bit of tuning, a version of this search could be used in high-volume scenarios, such as scraping, crawling, application DDOS, credit-card testing, account takeover, etc. Common data sources used for this detection are customized Apache logs, customized IIS, and Splunk Stream.

Known False Positives

As is common with many fraud-related searches, we are usually looking to attribute risk or synthesize relevant context with loosly written detections that simply detect anamoluous behavior.

Associated Analytic Story

Risk Based Analytics (RBA)

Risk Message Risk Score Impact Confidence
tbd 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 Not Applicable N/A N/A N/A
Unit ❌ Failing N/A N/A N/A
Integration ❌ Failing N/A N/A N/A

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: 2