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Insider Threat Matrix™

  • ID: PR018.007
  • Created: 17th April 2025
  • Updated: 17th April 2025
  • Platforms: MacOS, Windows, Linux, iOS, Android,
  • Contributor: Lawrence Rake

Downgrading Microsoft Information Protection (MIP) labels

A subject may intentionally downgrade the Microsoft Information Protection (MIP) label applied to a file in order to obscure the sensitivity of its contents and bypass security controls. MIP labels are designed to classify and protect files based on their sensitivity—ranging from “Public” to “Highly Confidential”—and are often used to enforce Data Loss Prevention (DLP), access restrictions, encryption, and monitoring policies.

 

By reducing a file's label classification, the subject may make the file appear innocuous, thus reducing the likelihood of triggering alerts or blocks by email filters, endpoint monitoring tools, or other security mechanisms.

 

This technique can enable the unauthorized exfiltration or misuse of sensitive data while evading established security measures. It may indicate premeditated policy evasion and can significantly weaken the organization’s data protection posture.

 

Examples of Use:

  • A subject downgrades a financial strategy document from Highly Confidential to Public before emailing it to a personal address, bypassing DLP policies that would normally prevent such transmission.
  • A user removes a classification label entirely from an engineering design document to upload it to a non-corporate cloud storage provider without triggering security controls.
  • An insider reclassifies multiple project files from Confidential to Internal Use Only to facilitate mass copying to a removable USB device.

 

Detection Considerations:

  • Monitoring for sudden or unexplained MIP label downgrades, especially in proximity to data transfer events (e.g., email sends, cloud uploads, USB copies).
  • Correlating audit logs from Microsoft Purview (formerly Microsoft Information Protection) with outbound data transfer events.
  • Use of Data Classification Analytics to detect label changes on high-value files without associated business justification.
  • Reviewing file access and modification logs to identify users who have altered classification metadata prior to suspicious activity.

Prevention

ID Name Description
PV001No 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
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.