Use of Browser-Based VPN Extensions

By only allowing pre-approved software to be installed and run on corporate devices, the subject is unable to install software themselves.

An enterprise-managed browser is a web browser controlled by an organization to enforce security policies, manage employee access, and ensure compliance. It allows IT administrators to monitor and restrict browsing activities, apply security updates, and integrate with other enterprise tools for a secure browsing environment.

MDM solutions require employees to register their personal devices with the organization's MDM system before gaining access to corporate networks and applications. This process ensures that only approved and known devices are permitted to connect.

Once a device is enrolled, the MDM system can enforce security policies that include:

• Access Control: Restricting or granting access based on the device's compliance with corporate security standards.
• Configuration Management: Ensuring that devices are configured securely, with up-to-date operating systems and applications.
• Remote Wipe and Lock: Allowing the organization to remotely wipe or lock a device if it is lost, stolen, or if suspicious activity is detected.
• Data Encryption: Enforcing encryption for data stored on and transmitted by the device to protect sensitive information.
• Application Control: Managing and restricting the installation of unauthorized applications that could pose security risks.

Next-generation firewall (NGFW) network appliances and services provide the ability to control network traffic based on rules. These firewalls provide basic firewall functionality, such as simple packet filtering based on static rules and track the state of network connections. They can also provide the ability to control network traffic based on Application Layer rules, among other advanced features to control network traffic.

A example of simple functionality would be blocking network traffic to or from a specific IP address, or all network traffic to a specific port number. An example of more advanced functionality would be blocking all network traffic that appears to be SSH or FTP traffic to any port on any IP address.

Only allow necessary protocols to communicate over the network. Implement strict access controls to prevent unauthorized protocols from being used. Typically these controls would be implemented on next-generation firewalls with Deep Packet Inspection (DPI) and other network security appliances.

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.

Google's Chrome browser stores details about any browser extensions that are installed, providing the user with additional functionality.

On Windows, this information is stored in the following location: C:\Users\[Username]\AppData\Local\Google\Chrome\User Data\Default\Extensions. Several directories will be listed, each one representing an installed extension. The directories and files inside, notably 'manifest.json', will contain information about the extension and its functionality. This can be combined with OSINT to learn more about the extension.

Google's Chrome browser stores the history of accessed websites and files downloaded.

On Windows, this information is stored in the following location:

C:/Users/<Username>/AppData/Local/Google/Chrome/User Data/Default/

On macOS:

/Users/<Username>/Library/Application Support/Google/Chrome/Default/

On Linux:

/home/<Username>/.config/google-chrome/Default/

Where /Default/ is referenced in the paths above, this is the default profile for Chrome, and can be replaced if a custom profile is used. In this location one database file is relevant, history.sqlite.
 

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.

Implement Deep Packet Inspection (DPI) tools to inspect the content of network packets beyond the header information. DPI can identify unusual patterns and hidden data within legitimate protocols. DPI can be conducted with a range of software and hardware solutions, such as Unified Threat Management (UTM) and Next-Generation Firewalls (NGFWs), as well as Intrusion Detection and Prevention Systems (IDPS) such as Snort and Suricata, 

Logging DNS requests made by corporate devices can assist with identifying what web resources a system has attempted to or successfully accessed.

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.

Microsoft's Edge browser stores the history of accessed websites and files downloaded.

On Windows, this information is stored in the following location:

C:\Users\<Username>\AppData\Local\Microsoft\Edge\User Data\Default\

On macOS:

/Users/<Username>/Library/Application Support/Microsoft Edge/Default/

On Linux:

/home/<Username>/.config/microsoft-edge/Default/

Where /Default/ is referenced in the paths above, this is the default profile for Edge, and can be replaced if a custom profile is used. In this location one database file is relevant, history.sqlite.
 

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.

Leverage telemetry produced by Endpoint Network Access Agents (such as Zscaler Client Connector or Cisco AnyConnect Secure Mobility Client) to detect network-layer evasion attempts, obfuscation behaviors, or deviations from expected usage patterns in hybrid and remote environments.

Detection Methods:

• Per-Session Telemetry Analysis: Collect detailed logs of outbound destination IPs, domain names, protocols, and session metadata from the agent. Correlate with identity logs to validate that the subject's traffic aligns with role-based expectations.
• Geographic and Network Mismatch: Detect inconsistencies between subject geolocation (from agent logs) and declared work location, or anomalous IPs (e.g., Tor exit nodes, commercial VPN infrastructure) accessed during active sessions.
• Split-Tunnel Indicators: Analyze whether only partial traffic is visible in agent logs. Absence of common destinations (e.g., productivity platforms, update services) may indicate concurrent use of a secondary tunnel outside agent visibility.
• Extension-Specific Access Patterns: Identify repeated access to known VPN browser extensions or proxy service endpoints from within the inspected agent traffic, suggesting circumvention efforts within the tunnel.
• Traffic Timing Correlation: Compare network activity timestamps from the agent with endpoint activity logs (e.g., EDR or system audit logs). Large gaps may indicate periods of disconnection, traffic redirection, or uninspected activity.
• Policy Bypass Attempts: Monitor for failed or repeated attempts to reach restricted domains, use unauthorized ports, or alter routing behavior as captured in agent logs. These may indicate probing or manipulation of enforcement boundaries.

This detection approach assumes full deployment and telemetry integration of the access agent, enabling fine-grained monitoring of network obfuscation behaviors even in decentralized, off-corporate-network scenarios.

Mozilla's Firefox browser stores the history of accessed websites.

On Windows, this information is stored in the following location:

C:\Users\<Username>\AppData\Roaming\Mozilla\Firefox\Profiles\<Profile Name>\

On macOS:

/Users/<Username>/Library/Application Support/Firefox/Profiles/<Profile Name>/

On Linux:

/home/<Username>/.mozilla/firefox/<Profile Name>/

In this location two database files are relevant, places.sqlite (browser history and bookmarks) and favicons.sqlite (favicons for visited websites and bookmarks).
 

These database files can be opened in software such as DB Browser For SQLite.

Analyze network flow data (NetFlow) to identify unusual communication patterns and potential tunneling activities. Flow data offers insights into the volume, direction, and nature of traffic.

NetFlow, a protocol developed by Cisco, captures and records metadata about network flows—such as source and destination IP addresses, ports, and the amount of data transferred.

Various network appliances support NetFlow, including Next-Generation Firewalls (NGFWs), network routers and switches, and dedicated NetFlow collectors.

Deploy User and Entity Behavior Analytics (UEBA) solutions designed for cloud environments to monitor and analyze the behavior of users, applications, network devices, servers, and other non-human resources. UEBA systems track normal behavior patterns and detect anomalies that could indicate potential insider events. For instance, they can identify when a user or entity is downloading unusually large volumes of data, accessing an excessive number of resources, or engaging in data transfers that deviate from their usual behavior.

Implement User Behavior Analytics (UBA) tools to continuously monitor and analyze user (human) activities, detecting anomalies that may signal security risks. UBA can track and flag unusual behavior, such as excessive data downloads, accessing a higher-than-usual number of resources, or large-scale transfers inconsistent with a user’s typical patterns. UBA can also provide real-time alerts when users engage in behavior that deviates from established baselines, such as accessing sensitive data during off-hours or from unfamiliar locations. By identifying such anomalies, UBA enhances the detection of insider events.