T1614: System Location Discovery
Adversaries may gather information in an attempt to calculate the geographical location of a victim host. Adversaries may use the information from System Location Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Adversaries may attempt to infer the location of a system using various system checks, such as time zone, keyboard layout, and/or language settings.[1][2][3] Windows API functions such as GetLocaleInfoW can also be used to determine the locale of the host.[1] In cloud environments, an instance's availability zone may also be discovered by accessing the instance metadata service from the instance.[4][5]
Adversaries may also attempt to infer the location of a victim host using IP addressing, such as via online geolocation IP-lookup services.[6][2]
Security context for executives and security teams
T1614: System Location Discovery describes Adversaries may gather information in an attempt to calculate the geographical location of a victim host. Adversaries may use the information from [System Location Discovery](https://attack.mitre.org/techniques/T1614) during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions. Adversaries may attempt to infer the location of a system using various system checks, such as time zone, keyboard layout, and/or language settings...
Executive priority
T1614: System Location Discovery is an official MITRE ATT&CK technique. Glexia treats it as defensive behavior context for prioritizing monitoring, control validation, and response planning without using the object by itself as an attribution claim.
Technical view
Security teams should validate T1614: System Location Discovery by reviewing the official ATT&CK relationships, mapped tactics (discovery), supported platforms (IaaS, Linux, macOS, Windows), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
- Endpoint process, command-line, and script execution logs
- Cloud control-plane, SaaS audit, and container platform logs
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1614: System Location Discovery appears in your detection coverage and tabletop scenarios.
- Use the object to align executive risk language with SOC, incident response, and detection engineering work.
- Do not treat ATT&CK relationship context as attribution without corroborating evidence.
Mitigation priorities
- Map the object to existing controls and identify missing telemetry or response ownership.
- Prioritize mitigations that reduce exposure on the listed platforms and tactics.
- Review adjacent ATT&CK relationships before changing policy, detections, or reporting language.
Additional notes and limits
Baseline Glexia take generated from the official MITRE ATT&CK STIX object, source hash, tactics, platforms, and detection fields. It is safe to replace with a richer model-generated take for the same source hash later.
This baseline take is source-grounded and schema-validated, but it does not include environment-specific telemetry, incident evidence, or threat-intelligence corroboration.
Generated from the cited source records. This long-tail analysis has not been individually reviewed by a named human.
System Location Discovery
Adversaries may gather information in an attempt to calculate the geographical location of a victim host. Adversaries may use the information from System Location Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.
Adversaries may attempt to infer the location of a system using various system checks, such as time zone, keyboard layout, and/or language settings.[1][2][3] Windows API functions such as GetLocaleInfoW can also be used to determine the locale of the host.[1] In cloud environments, an instance's availability zone may also be discovered by accessing the instance metadata service from the instance.[4][5]
Adversaries may also attempt to infer the location of a victim host using IP addressing, such as via online geolocation IP-lookup services.[6][2]
How security teams should use this page
Treat this object as behavior context, not an attribution claim. Validate the related groups, software, data sources, and mitigations against official ATT&CK relationships and your own telemetry before making control-coverage decisions.
Related techniques
This mirrors the MITRE pattern of making group, software, campaign, and technique relationships scannable. Relationship notes come from mirrored ATT&CK relationship text when available.
| Domain | ID | Name | Relationship / procedure |
|---|---|---|---|
| Enterprise | T1614.001 | System Language DiscoverySub-technique | System Language Discovery subtechnique of this object. |
Groups, software, and campaigns
G1008: SideCopy
SideCopy is a Pakistani threat group that has primarily targeted South Asian countries, including Indian and Afghani government personnel, since at least 2019. SideCopy's name comes from its infection chain that tries to mimic that of Sidewinder, a suspected Indian threat group.[1]
G1017: Volt Typhoon
Volt Typhoon is a People's Republic of China (PRC) state-sponsored actor that has been active since at least 2021, primarily targeting critical infrastructure organizations in the US and its territories including Guam. Volt Typhoon's targeting and pattern of behavior have been assessed as pre-positioning to enable lateral movement to operational technology (OT) assets for potential destructive or disruptive attacks. Volt Typhoon has emphasized stealth in operations using web shells, living-off-the-land (LOTL) binaries, hands on keyboard activities, and stolen credentials.[1][2][3][4]. The group has leveraged compromised SOHO routers to proxy command and control traffic and obscure its infrastructure, activity associated with the KV botnet.[5].
Reporting indicates a separate initial access cluster, SYLVANITE, has been observed exploiting internet-facing edge devices and transferring access to Volt Typhoon, also tracked as VOLTZITE, for follow-on operations. [6]
S1025: Amadey
S9034: Tsundere Botnet
Tsundere Botnet is a botnet first reported in mid-2025 that is delivered via MSI installer or a PowerShell script. It leverages Node.js and JavaScript for payload delivery and execution, and uses smart contracts on the blockchain to host command and control (C2) addresses. Tsundere Botnet is attributed to a likely Russian-speaking threat actor.
A variant named DinDoor has been linked to MuddyWater operations and uses the Deno runtime for execution rather than Node.js.[1][2][3][4]
S1245: InvisibleFerret
InvisibleFerret is a modular python malware that is leveraged for data exfiltration and remote access capabilities.[1][2][3] InvisibleFerret consists of four modules: main, payload, browser, and AnyDesk.[1] InvisibleFerret malware has been leveraged by North Korea-affiliated threat actors identified as DeceptiveDevelopment or Contagious Interview since 2023.[4][2][3][5] InvisibleFerret has historically been introduced to the victim environment through the use of the BeaverTail malware.[6][1][2][3][5]
S0115: Crimson
Crimson is a remote access Trojan that has been used by Transparent Tribe since at least 2016.[1][2]
S1138: Gootloader
Gootloader is a Javascript-based infection framework that has been used since at least 2020 as a delivery method for the Gootkit banking trojan, Cobalt Strike, REvil, and others. Gootloader operates on an "Initial Access as a Service" model and has leveraged SEO Poisoning to provide access to entities in multiple sectors worldwide including financial, military, automotive, pharmaceutical, and energy.[1][2]
S1249: HexEval Loader
HexEval Loader is a hex-encoded loader that collects host data, decodes follow-on scripts and acts as a downloader for the BeaverTail malware. HexEval Loader was first reported in April 2025. HexEval Loader has previously been leveraged by North Korea-affiliated threat actors identified as Contagious Interview. HexEval Loader has been delivered to victims through code repository sites utilizing typosquatting naming conventions of various npm packages.[1][2][3]
S1153: Cuckoo Stealer
Cuckoo Stealer is a macOS malware with characteristics of spyware and an infostealer that has been in use since at least 2024. Cuckoo Stealer is a universal Mach-O binary that can run on Intel or ARM-based Macs and has been spread through trojanized versions of various potentially unwanted programs or PUP's such as converters, cleaners, and uninstallers.[1][2]
S9030: SameCoin
S0481: Ragnar Locker
Ragnar Locker is a ransomware that has been in use since at least December 2019.[1][2]
S1124: SocGholish
SocGholish is a JavaScript-based loader malware that has been used since at least 2017. It has been observed in use against multiple sectors globally for initial access, primarily through drive-by-downloads masquerading as software updates. SocGholish is operated by Mustard Tempest and its access has been sold to groups including Indrik Spider for downloading secondary RAT and ransomware payloads.[1][2][3][4]
S0673: DarkWatchman
DarkWatchman is a lightweight JavaScript-based remote access tool (RAT) that avoids file operations; it was first observed in November 2021.[1]
S0013: PlugX
All related ATT&CK context
Object version and sync metadata
The fields below describe the current mirrored snapshot. When Glexia retains multiple ATT&CK source imports, you can open the table to compare the same object across releases (hashes and MITRE timestamps). For MITRE’s own release notes and roadmap, see ATT&CK resources — Updates.
Imported snapshots across ATT&CK releases(2)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.2 | 1.1 | Current bundle | fa863d2a8b00… | ||
| 19.1 | 1.1 | Older bundle | fa863d2a8b00… |
Mirrored ATT&CK source object
The raw object is retained through the mirrored ATT&CK source bundle and object hash. The raw endpoint returns the exact object from the mirrored bundle when available.
External references and citations
MITRE external references are preserved separately from Glexia analysis so citations remain traceable to their original source records.
- [1]FBI Ragnar Locker 2020
FBI. (2020, November 19). Indicators of Compromise Associated with Ragnar Locker Ransomware. Retrieved September 12, 2024.
Open source URL - [2]Sophos Geolocation 2016
Wisniewski, C. (2016, May 3). Location-based threats: How cybercriminals target you based on where you live. Retrieved April 1, 2021.
Open source URL - [3]Bleepingcomputer RAT malware 2020
Abrams, L. (2020, October 23). New RAT malware gets commands via Discord, has ransomware feature. Retrieved April 1, 2021.
Open source URL - [4]AWS Instance Identity Documents
Amazon. (n.d.). Instance identity documents. Retrieved April 2, 2021.
Open source URL - [5]Microsoft Azure Instance Metadata 2021
Microsoft. (2021, February 21). Azure Instance Metadata Service (Windows). Retrieved April 2, 2021.
Open source URL - [6]Securelist Trasparent Tribe 2020
Dedola, G. (2020, August 20). Transparent Tribe: Evolution analysis, part 1. Retrieved April 1, 2021.
Open source URL - [7]mitre-attackT1614Open source URL
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