Infringement
Data Loss
Disruption of Business Operations
Excessive Personal Use
Exfiltration via Email
Exfiltration via Media Capture
Exfiltration via Messaging Applications
Exfiltration via Other Network Medium
Exfiltration via Physical Medium
- Exfiltration via Bring Your Own Device (BYOD)
- Exfiltration via Disk Media
- Exfiltration via Floppy Disk
- Exfiltration via New Internal Drive
- Exfiltration via Physical Access to System Drive
- Exfiltration via Physical Documents
- Exfiltration via Target Disk Mode
- Exfiltration via USB Mass Storage Device
- Exfiltration via USB to Mobile Device
- Exfiltration via USB to USB Data Transfer
Exfiltration via Web Service
Harassment and Discrimination
Inappropriate Web Browsing
Installing Unapproved Software
Misappropriation of Funds
Non-Corporate Device
Providing Access to a Unauthorized Third Party
Public Statements Resulting in Brand Damage
Regulatory Non-Compliance
Sharing on AI Chatbot Platforms
Theft
Unauthorized Changes to IT Systems
Unauthorized Printing of Documents
Unauthorized VPN Client
Unlawfully Accessing Copyrighted Material
- 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 |
---|---|---|
IF001.001 | Exfiltration 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):
|
IF001.002 | Exfiltration 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):
|
IF001.005 | Exfiltration 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):
|
IF001.003 | Exfiltration 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):
|
IF001.004 | Exfiltration via Webhook | A subject may use an existing, legitimate external Web service to exfiltrate data |
Prevention
ID | Name | Description |
---|---|---|
PV021 | DNS 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 |
PV006 | Install 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 |
---|---|---|
DT046 | Agent 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). |
DT045 | Agent 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. |
DT047 | Agent 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. |
DT019 | Chrome 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:
On macOS:
On Linux:
Where 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. |
DT051 | DNS Logging | Logging DNS requests made by corporate devices can assist with identifying what web resources a system has attempted to or successfully accessed. |
DT096 | DNS 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. |
DT018 | Edge 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:
On macOS:
On Linux:
Where 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. |
DT017 | Firefox Browser History | Mozilla's Firefox browser stores the history of accessed websites.
On Windows, this information is stored in the following location:
On macOS:
On Linux:
In this location two database files are relevant, These database files can be opened in software such as DB Browser For SQLite. |