Anti-Forensics
Clear Browser Artifacts
Clear Command History
Clear Operating System Logs
Delete User Account
Disk Wiping
File Deletion
File Encryption
Hide Artifacts
Log Tampering
Modify Windows Registry
Physical Destruction of Storage Media
Physical Removal of Disk Storage
Steganography
System Shutdown
Timestomping
Tripwires
Uninstalling Software
Use of a Virtual Machine
- ID: AF004.001
- Created: 25th May 2024
- Updated: 27th July 2024
- Platforms: Windows, Linux, MacOS
- Contributor: The ITM Team
Clear Chrome Artifacts
A subject clears Google Chrome browser artifacts to hide evidence of their activities, such as visited websites, cache, cookies, and download history.
Prevention
ID | Name | Description |
---|---|---|
PV001 | No Ready System-Level Mitigation | This section cannot be readily mitigated at a system level with preventive controls since it is based on the abuse of fundamental features of the system. |
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. |
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. |
DT039 | Web Proxy Logs | Depending on the solution used, web proxies can provide a wealth of information about web-based activity. This can include the IP address of the system making the web request, the URL requested, the response code, and timestamps. An organization must perform SSL/TLS interception to receive the most complete information about these connections. |
DT038 | Windows Recycle Bin | On Windows 10, we can find the Recycle Bin directory for all users located at Files that begin with Files that begin with If the user has emptied the Recycle Bin, we lose this artifact and cannot analyze it. Instead, we would need to carve these files from a disk image. |