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Insider Threat Matrix™

  • ID: IF001
  • Created: 31st May 2024
  • Updated: 07th April 2025
  • Contributor: The ITM Team

Exfiltration via Web Service

A subject uses an existing, legitimate external Web service to exfiltrate data

Subsections

ID Name Description
IF001.001Exfiltration via Cloud Storage

A subject uses a cloud storage service, such as Dropbox, OneDrive, or Google Drive to exfiltrate data. They will then access that service again on another device to retrieve the data. Examples include (URLs have been sanitized):

  • hxxps://www.dropbox[.]com
  • hxxps://drive.google[.]com
  • hxxps://onedrive.live[.]com
  • hxxps://mega[.]nz
  • hxxps://www.icloud[.]com/iclouddrive
  • hxxps://www.pcloud[.]com
IF001.002Exfiltration via Code Repository

A subject uses a code repository service, such as GitHub, to exfiltrate data. They will then access that service again on another device to retrieve the data. Examples include (URLs have been sanitized):

  • hxxps://github[.]com
  • hxxps://gitlab[.]com
  • hxxps://bitbucket[.]org
  • hxxps://sourceforge[.]net
  • hxxps://aws.amazon[.]com/codecommit
IF001.005Exfiltration via Note-Taking Web Services

A subject uploads confidential organization data to a note-taking web service, such as Evernote. The subject can then access the confidential data outside of the organization from another device. Examples include (URLs have been sanitized):

  • hxxps://www.evernote[.]com
  • hxxps://keep.google[.]com
  • hxxps://www.notion[.]so
  • hxxps://www.onenote[.]com
  • hxxps://notebook.zoho[.]com
IF001.003Exfiltration via Text Storage Sites

A subject uses a text storage service, such as Pastebin, to exfiltrate data. They will then access that service again on another device to retrieve the data. Examples include (URLs have been sanitized):

  • hxxps://pastebin[.]com
  • hxxps://hastebin[.]com
  • hxxps://privatebin[.]net
  • hxxps://controlc[.]com
  • hxxps://rentry[.]co
  • hxxps://dpaste[.]org
IF001.004Exfiltration via Webhook

A subject may use an existing, legitimate external Web service to exfiltrate data

Prevention

ID Name Description
PV021DNS Filtering

Domain Name System (DNS) filtering allows the blocking of domain resolution for specific domains or automatically categorized classes of domains (depending on the functionality of the software or appliance being used). DNS filtering prevents users from accessing blocked domains, regardless of the IP address the domains resolve to.

 

Examples of automatically categorized classes of domains are ‘gambling’ or ‘social networking’ domains. Automatic categorizations of domains are typically conducted by the software or appliance being used, whereas specific domains can be blocked manually. Most DNS filtering software or appliances will provide the ability to use Regular Expressions (RegEx) to (for example) also filter all subdomains on a specified domain.

DNS filtering can be applied on an individual host, such as with the hosts file, or for multiple hosts via a DNS server or firewall.

PV006Install a Web Proxy Solution

A web proxy can allow for specific web resources to be blocked, preventing clients from successfully connecting to them.

Detection

ID Name Description
DT046Agent Capable of Endpoint Detection and Response

An agent capable of Endpoint Detection and Response (EDR) is a software agent installed on organization endpoints (such as laptops and servers) that (at a minimum) records the Operating System, application, and network activity on an endpoint.

 

Typically EDR operates in an agent/server model, where agents automatically send logs to a server, where the server correlates those logs based on a rule set. This rule set is then used to surface potential security-related events, that can then be analyzed.

 

An EDR agent typically also has some form of remote shell capability, where a user of the EDR platform can gain a remote shell session on a target endpoint, for incident response purposes. An EDR agent will typically have the ability to remotely isolate an endpoint, where all network activity is blocked on the target endpoint (other than the network activity required for the EDR platform to operate).

DT045Agent Capable of User Activity Monitoring

An agent capable of User Activity Monitoring (UAM) is a software agent installed on organization endpoints (such as laptops); typically, User Activity Monitoring agents are only deployed on endpoints where a human user Is expected to conduct the activity.

 

The User Activity Monitoring agent will typically record Operating System, application, and network activity occurring on an endpoint, with a focus on activity that is or can be conducted by a human user. The purpose of this monitoring is to identify undesirable and/or malicious activity being conducted by a human user (in this context, an Insider Threat).

 

Typical User Activity Monitoring platforms operate in an agent/server model where activity logs are sent to a server for automatic correlation against a rule set. This rule set is used to surface activity that may represent Insider Threat related activity such as capturing screenshots, copying data, compressing files or installing risky software.

 

Other platforms providing related functionality are frequently referred to as User Behaviour Analytics (UBA) platforms.

DT047Agent Capable of User Behaviour Analytics

An agent capable of User Behaviour Analytics (UBA) is a software agent installed on organizational endpoints (such as laptops). Typically, User Activity Monitoring agents are only deployed on endpoints where a human user is expected to conduct the activity.

 

The User Behaviour Analytics agent will typically record Operating System, application, and network activity occurring on an endpoint, focusing on activity that is or can be conducted by a human user. Typically, User Behaviour Analytics platforms operate in an agent/server model where activity logs are sent to a server for automatic analysis. In the case of User Behaviour Analytics, this analysis will typically be conducted against a baseline that has previously been established.

 

A User Behaviour Analytic platform will typically conduct a period of ‘baselining’ when the platform is first installed. This baselining period establishes the normal behavior parameters for an organization’s users, which are used to train a Machine Learning (ML) model. This ML model can then be later used to automatically identify activity that is predicted to be an anomaly, which is hoped to surface user behavior that is undesirable, risky, or malicious.

 

Other platforms providing related functionality are frequently referred to as User Activity Monitoring (UAM) platforms.

DT019Chrome Browser History

Google's Chrome browser stores the history of accessed websites and files downloaded.

 

On Windows, this information is stored in the following location:

C:/Users/<Username>/AppData/Local/Google/Chrome/User Data/Default/

On macOS:

/Users/<Username>/Library/Application Support/Google/Chrome/Default/

On Linux:

/home/<Username>/.config/google-chrome/Default/

 

Where /Default/ is referenced in the paths above, this is the default profile for Chrome, and can be replaced if a custom profile is used. In this location one database file is relevant, history.sqlite.
 

This database file can be opened in software such as DB Browser For SQLite. The ‘downloads’ and ‘urls’ tables are of immediate interest to understand recent activity within Chrome.

DT051DNS Logging

Logging DNS requests made by corporate devices can assist with identifying what web resources a system has attempted to or successfully accessed.

DT096DNS Monitoring

Monitor outbound DNS traffic for unusual or suspicious queries that may indicate DNS tunneling. DNS monitoring entails observing and analyzing Domain Name System (DNS) queries and responses to identify abnormal or malicious activities. This can be achieved using various security platforms and network appliances, including Network Intrusion Detection Systems (NIDS), specialized DNS services, and Security Information and Event Management (SIEM) systems that process DNS logs.

DT018Edge Browser History

Microsoft's Edge browser stores the history of accessed websites and files downloaded.

 

On Windows, this information is stored in the following location:

C:\Users\<Username>\AppData\Local\Microsoft\Edge\User Data\Default\

On macOS:

/Users/<Username>/Library/Application Support/Microsoft Edge/Default/

On Linux:

/home/<Username>/.config/microsoft-edge/Default/

 

Where /Default/ is referenced in the paths above, this is the default profile for Edge, and can be replaced if a custom profile is used. In this location one database file is relevant, history.sqlite.
 

This database file can be opened in software such as DB Browser For SQLite. The ‘downloads’ and ‘urls’ tables are of immediate interest to understand recent activity within Chrome.

DT017Firefox Browser History

Mozilla's Firefox browser stores the history of accessed websites.

 

On Windows, this information is stored in the following location:

C:\Users\<Username>\AppData\Roaming\Mozilla\Firefox\Profiles\<Profile Name>\

On macOS:

/Users/<Username>/Library/Application Support/Firefox/Profiles/<Profile Name>/

On Linux:

/home/<Username>/.mozilla/firefox/<Profile Name>/

 

In this location two database files are relevant, places.sqlite (browser history and bookmarks) and favicons.sqlite (favicons for visited websites and bookmarks).
 

These database files can be opened in software such as DB Browser For SQLite.