Motive
Coercion
Conflicts of Interest
Curiosity
Espionage
Fear of Reprisals
Hubris
Human Error
Ideology
Joiner
Lack of Awareness
Leaver
Misapprehension or Delusion
Mover
Personal Gain
Political or Philosophical Beliefs
Recklessness
Resentment
Rogue Nationalism
Self Sabotage
Third Party Collusion Motivated by Personal Gain
- ID: MT003
- Created: 22nd May 2024
- Updated: 25th April 2025
- Contributor: The ITM Team
Leaver
A subject leaving the organisation with access to sensitive data with the intent to access and exfiltrate sensitive data or otherwise contravene internal policies.
Prevention
ID | Name | Description |
---|---|---|
PV024 | Employee Off-boarding Process | When an employee leaves the organization, a formal process should be followed to ensure all equipment is returned, and any associated accounts or access is revoked. |
PV003 | Enforce an Acceptable Use Policy | An Acceptable Use Policy (AUP) is a set of rules outlining acceptable and unacceptable uses of an organization's computer systems and network resources. It acts as a deterrent to prevent employees from conducting illegitimate activities by clearly defining expectations, reinforcing legal and ethical standards, establishing accountability, specifying consequences for violations, and promoting education and awareness about security risks. |
PV054 | Human Resources Collaboration for Early Threat Detection | Implement a process whereby HR data and observations, including those from managers and colleagues, can be securely communicated in a timely manner to investigators, triggering proactive monitoring of potential insider threats early in their lifecycle. Collaboration between HR teams, managers, colleagues, and investigators is essential for detecting concerning behaviors or changes in an employee's personal circumstances that could indicate an increased risk of insider threat.
Mental Health and Personal Struggles
Negative Statements or Discontent with the Company
Excessive Financial Purchases (Potential Embezzlement or Third-Party Influence)
Hearsay and Indirect Reports
Implementation Considerations
|
PV038 | Insider Threat Awareness Training | Training should equip employees to recognize manipulation tactics, such as social engineering and extortion, that are used to coerce actions and behaviors harmful to the individual and/or the organization. The training should also encourage and guide participants on how to safely report any instances of coercion. |
PV048 | Privileged Access Management (PAM) | Privileged Access Management (PAM) is a critical security practice designed to control and monitor access to sensitive systems and data. By managing and securing accounts with elevated privileges, PAM helps reduce the risk of insider threats and unauthorized access to critical infrastructure.
Key Prevention Measures:
Benefits:
|
PV046 | Regulation Awareness Training | Regulation Awareness Training equips staff with the knowledge and understanding required to comply with legal, regulatory, and policy obligations relevant to their roles. This includes, but is not limited to, export controls, international sanctions, anti-bribery laws, conflict-of-interest rules, antitrust regulations, and data protection requirements.
The training should be customized according to the specific risks of different roles within the organization, ensuring that employees in high-risk areas—such as legal, procurement, sales, finance, engineering, and senior management—receive in-depth education on how to recognize and avoid behaviors that could lead to regulatory violations. Scenarios that could result in inadvertent or intentional breaches should be addressed, alongside practical advice on how to report concerns and escalate issues.
To accommodate varying learning styles and operational needs, Regulation Awareness Training can be delivered through multiple formats:
By fostering a culture of compliance and accountability, Regulation Awareness Training helps minimize the risk of breaches, whether intentional or accidental, and strengthens the organization’s ability to identify, prevent, and respond to regulatory infringements. |
Detection
ID | Name | Description |
---|---|---|
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. |
DT048 | Data Loss Prevention Solution | 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. |
DT104 | Leaver Watchlist | In relevant security tooling (such as a SIEM or EDR), a watchlist (also known as a reference set) should be used to monitor for any activity generated by accounts belonging to employees who have left the organization, as this is unexpected. This can help to ensure that the security team readily detects any unrevoked access or account usage.
This process must be in partnership with the Human Resources team, which should inform the security team when an individual leaves the organization (during an Employee Off-Boarding Process, see PV024), including their full and user account names. Ideally, this process should be automated to prevent any gaps in monitoring between the information being sent and the security team adding the name(s) to the watchlist. All format variations should be considered as individual entries in the watchlist to ensure accounts using different naming conventions will generate alerts, such as john.smith, john smith, john.smith@company.com, and jsmith.
False positives could occur if there is a legitimate reason for interaction with the account(s), such as actions conducted by IT staff. |