Mutual Exclusion (T1480.002)
Geofencing [T1480.002]
Last updated
Geofencing [T1480.002]
Last updated
Name: Mutual Exclusion
ID: T1480.002
Tactics:
Technique:
Geofencing () is a sub-technique within the MITRE ATT&CK framework under the technique "Execution Guardrails." This technique involves adversaries using geographical constraints to control the execution of malicious payloads. Specifically, attackers configure malware or other malicious tools to execute only when the infected system resides within or outside certain geographic regions. Geofencing helps threat actors evade detection, complicate analysis, and target specific victims or regions, ensuring greater precision and operational security.
Geofencing relies on various technical mechanisms to determine the location of the compromised system and decide whether or not to execute a malicious payload. Attackers typically implement geofencing using the following methods:
IP Address Geolocation:
Malware queries online IP geolocation services or built-in IP databases to determine the victim's approximate location.
Common services include public APIs, such as IPinfo, MaxMind, or ip-api.com.
Attackers may embed offline databases within malware to avoid network-based detection.
Locale and Language Settings:
Malware checks the system's locale, language, keyboard layout, or timezone settings.
Execution triggers only if these settings match predefined criteria, such as a specific country or region.
GPS and Cellular Data:
Mobile malware may leverage GPS coordinates or cellular network information to identify geographic location.
Payload execution is contingent upon the device physically entering or leaving defined geographic boundaries.
Network Infrastructure Checks:
Malware checks for known regional network infrastructure characteristics, such as specific ISPs or network routes.
Attackers implement geofencing logic through conditional statements embedded in malware code. For example, malware may contain logic similar to:
This approach ensures the payload executes only within targeted countries, thereby minimizing detection in non-targeted regions.
Geofencing is typically employed by adversaries in various attack scenarios and stages, including:
Targeted Attacks and Espionage Campaigns:
Attackers use geofencing to precisely target specific regions, organizations, or nations.
Espionage groups frequently utilize geofencing to limit exposure and detection.
Financially Motivated Attacks:
Cybercriminals may employ geofencing to target regions known for lucrative financial institutions or businesses.
Banking trojans and ransomware often use geofencing to avoid attention from law enforcement agencies in certain countries.
Malware Distribution and Botnet Operations:
Malware authors use geofencing to limit malware spread to specific regions, reducing visibility and detection.
Botnet operators may restrict payload delivery to specific regions, optimizing resources and evading detection.
Anti-Analysis and Evasion Techniques:
Malware may avoid execution in regions known for cybersecurity research or law enforcement activity.
Geofencing helps attackers evade sandbox environments or analysis by security researchers in certain geographic locations.
Organizations can detect geofencing through multiple approaches, including:
Network Traffic Analysis:
Monitor DNS requests and HTTP(S) traffic to known IP geolocation APIs or databases.
Unusual or repeated queries to geolocation services from internal endpoints may indicate malicious activity.
Endpoint Behavioral Monitoring:
Endpoint detection and response (EDR) tools can detect malware performing system locale checks, timezone queries, or language settings enumeration.
Suspicious processes accessing locale-related registry keys or system APIs can trigger alerts.
Code and Binary Analysis:
Static analysis of malware samples can reveal embedded IP databases, geolocation API endpoints, or conditional logic related to geographic checks.
Dynamic analysis in sandboxes configured with various geographic settings can expose malware behavior dependent on geolocation.
Threat Intelligence and IoC Feeds:
Threat intelligence platforms provide indicators of compromise (IoCs) related to malware campaigns known to leverage geofencing.
IoCs may include IP addresses, domains, API endpoints, or specific malware hashes.
Typical Indicators of Compromise (IoCs) include:
Unusual outbound requests to geolocation services or APIs (e.g., ip-api.com, ipinfo.io).
Malware binaries containing embedded country codes, IP address ranges, or geolocation databases.
Registry or process logs indicating unusual checks of system locale, timezone, or language settings.
Detecting geofencing is critical due to several significant impacts it can have on organizational security:
Targeted Attack Risk:
Geofencing indicates highly targeted attacks, often associated with advanced persistent threats (APTs) or sophisticated cybercriminal groups.
Early detection helps organizations proactively mitigate potential espionage, sabotage, or financial theft.
Detection and Response Challenges:
Malware leveraging geofencing can evade security controls, sandboxes, and automated analysis tools.
Detecting geofencing behavior helps organizations improve threat hunting and threat intelligence capabilities.
Operational Security and Threat Intelligence:
Identification of geofencing tactics provides valuable intelligence on adversary motives, targets, and operational security measures.
Understanding geographic targeting helps organizations and security researchers better predict and respond to future threats.
Compliance and Regulatory Impact:
Organizations operating in sensitive industries or regions must detect and respond to geographically targeted attacks to ensure compliance with regulations and standards.
Failure to detect geographically targeted malware can lead to regulatory fines, reputational damage, and loss of customer trust.
Real-world examples of malware campaigns utilizing geofencing include:
DarkHotel APT:
A sophisticated espionage group known for targeting executives traveling in specific regions, particularly Asia.
Malware executed payloads only when victims' IP addresses matched targeted geographic regions, ensuring precision and stealth.
Dridex Banking Trojan:
Cybercriminals behind Dridex implemented geofencing to target financial institutions primarily in Europe and North America.
Malware performed IP geolocation checks and executed payloads only within targeted regions, reducing detection and analysis.
Cerber Ransomware:
Cerber ransomware used geofencing to avoid infecting systems in certain CIS countries, likely to avoid attention from local law enforcement.
Malware checked system language and locale settings before executing the encryption payload.
Emotet Malware:
Emotet operators used geofencing to selectively distribute malware payloads based on victim location, optimizing infection rates and avoiding detection in non-targeted regions.
Payload execution depended on IP geolocation queries and system locale checks.
These examples illustrate attackers' strategic use of geofencing to enhance operational security, evade detection, and precisely target victims for maximum effectiveness.