Exfiltration via Target Disk Mode

First stage bootloaders such as BIOS (Basic Input/Output System) and UEFI (Unified Extensible Firmware Interface) or second stage bootloaders such as GNU GRUB (GNU GRand Unified Bootloader) and iBoot, generally provide the ability to configure a bootloader password as a security measure. This password restricts access to the computer’s firmware settings and, in some cases, the boot process.

When a bootloader password is set, it is stored in a non-volatile memory within the firmware. Upon powering on the system (and the bootloader settings being selected) the bootloader prompts the user to enter the password before allowing access to the firmware settings, thereby preventing unauthorized users from altering system settings or booting from unauthorized devices.

Full Disk Encryption (FDE) involves encrypting all data on a device's hard disk or solid-state drive (SSD), including the Operating System (OS), third party applications and user data. This helps to ensure that data on the disk remains inaccessible if the laptop is lost or stolen, as the data cannot be accessed without the correct decryption key.

Typically a user decrypts a FDE disk during the boot process. The user is prompted to enter a password or provide a hardware token to unlock the encryption key. Only after successful authentication can the disk be decrypted and subsequently the Operating System loaded and the data accessed.

The Principle of Least Privilege should be enforced, and period reviews of permissions conducted to ensure that accounts have the minimum level of access required to complete duties as per their role.

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).

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.

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.

A Data Loss Prevention (DLP) solution refers to policies, technologies, and controls that prevent the accidental and/or deliberate loss, misuse, or theft of data by members of an organization. Typically, DLP technology would take the form of a software agent installed on organization endpoints (such as laptops and servers).

Typical DLP technology will alert on the potential loss of data, or activity which might indicate the potential for data loss. A DLP technology may also provide automated responses to prevent data loss on a device.