T1614.001: System Language Discovery
Adversaries may attempt to gather information about the system language of a victim in order to infer the geographical location of that host. This information may be used to shape follow-on behaviors, including whether the adversary infects the target and/or attempts specific actions. This decision may be employed by malware developers and operators to reduce their risk of attracting the attention of specific law enforcement agencies or prosecution/scrutiny from other entities.[1]
There are various sources of data an adversary could use to infer system language, such as system defaults and keyboard layouts. Specific checks will vary based on the target and/or adversary, but may involve behaviors such as Query Registry and calls to Native API functions.[2]
For example, on a Windows system adversaries may attempt to infer the language of a system by querying the registry key HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Nls\Language or parsing the outputs of Windows API functions GetUserDefaultUILanguage, GetSystemDefaultUILanguage, GetKeyboardLayoutList and GetUserDefaultLangID.[3][4][5]
On a macOS or Linux system, adversaries may query locale to retrieve the value of the $LANG environment variable.
Security context for executives and security teams
T1614.001: System Language Discovery describes Adversaries may attempt to gather information about the system language of a victim in order to infer the geographical location of that host. This information may be used to shape follow-on behaviors, including whether the adversary infects the target and/or attempts specific actions. This decision may be employed by malware developers and operators to reduce their risk of attracting the attention of specific law enforcement agencies or prosecution/scrutiny from other entities.(Citation: Malware System Language Che...
Executive priority
T1614.001: System Language 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 T1614.001: System Language Discovery by reviewing the official ATT&CK relationships, mapped tactics (discovery), supported platforms (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
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1614.001: System Language 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 Language Discovery
Adversaries may attempt to gather information about the system language of a victim in order to infer the geographical location of that host. This information may be used to shape follow-on behaviors, including whether the adversary infects the target and/or attempts specific actions. This decision may be employed by malware developers and operators to reduce their risk of attracting the attention of specific law enforcement agencies or prosecution/scrutiny from other entities.[1]
There are various sources of data an adversary could use to infer system language, such as system defaults and keyboard layouts. Specific checks will vary based on the target and/or adversary, but may involve behaviors such as Query Registry and calls to Native API functions.[2]
For example, on a Windows system adversaries may attempt to infer the language of a system by querying the registry key HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\Nls\Language or parsing the outputs of Windows API functions GetUserDefaultUILanguage, GetSystemDefaultUILanguage, GetKeyboardLayoutList and GetUserDefaultLangID.[3][4][5]
On a macOS or Linux system, adversaries may query locale to retrieve the value of the $LANG environment variable.
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 | System Location Discovery | This object subtechnique of System Location Discovery. |
Groups, software, and campaigns
G1043: BlackByte
BlackByte is a ransomware threat actor operating since at least 2021. BlackByte is associated with several versions of ransomware also labeled BlackByte Ransomware. BlackByte ransomware operations initially used a common encryption key allowing for the development of a universal decryptor, but subsequent versions such as BlackByte 2.0 Ransomware use more robust encryption mechanisms. BlackByte is notable for operations targeting critical infrastructure entities among other targets across North America.[1][2][3][4][5]
G0004: Ke3chang
G1053: Storm-0501
Storm-0501 is a financially motivated cyber criminal group that uses commodity and open-source tools to conduct ransomware operations. Storm-0501 has been active since 2021 and has previously been affiliated with Sabbath Ransomware and other Ransomware-as-a-Service (RaaS) variants such as Hive, BlackCat, Hunters International, LockBit 3.0, and Embargo ransomware.[1][2][3][4]
G1054: MirrorFace
MirrorFace is a People's Republic of China (PRC)-aligned cyberespionage actor believed to be a subgroup under the menuPass umbrella based on targeting, tools, and infrastructure overlaps. MirrorFace has been active since at least 2019, at first exclusively targeting Japanese organizations across the media, defense, diplomatic, financial, manufacturing, and academic sectors. Subsequent MirrorFace operations included targets in Central Europe and featured use of LODEINFO, HiddenFace, and UPPERCUT malware.[1][2][3][4][5][6]
G1026: Malteiro
Malteiro is a financially motivated criminal group that is likely based in Brazil and has been active since at least November 2019. The group operates and distributes the Mispadu banking trojan via a Malware-as-a-Service (MaaS) business model. Malteiro mainly targets victims throughout Latin America (particularly Mexico) and Europe (particularly Spain and Portugal).[1]
S0543: Spark
S0242: SynAck
S0546: SharpStage
SharpStage is a .NET malware with backdoor capabilities.[1][2]
S0083: Misdat
Misdat is a backdoor that was used in Operation Dust Storm from 2010 to 2011.[1]
S0330: Zeus Panda
Zeus Panda is a Trojan designed to steal banking information and other sensitive credentials for exfiltration. Zeus Panda’s original source code was leaked in 2011, allowing threat actors to use its source code as a basis for new malware variants. It is mainly used to target Windows operating systems ranging from Windows XP through Windows 10.[1][2]
S1228: PUBLOAD
PUBLOAD is a stager malware that has been observed installing itself in existing directories such as `C:\Users\Public` or creating new directories to stage the malware and its components.[1] PUBLOAD malware collects details of the victim host, establishes persistence, encrypts victim details using RC4 and communicates victim details back to C2. PUBLOAD malware has previously been leveraged by China-affiliated actors identified as Mustang Panda. PUBLOAD is also known as “NoFive” and some public reporting identifies the loader component as CLAIMLOADER.[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]
S0547: DropBook
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]
S0691: Neoichor
S1122: Mispadu
Mispadu is a banking trojan written in Delphi that was first observed in 2019 and uses a Malware-as-a-Service (MaaS) business model.[1][2] This malware is operated, managed, and sold by the Malteiro cybercriminal group.[2] Mispadu has mainly been used to target victims in Brazil and Mexico, and has also had confirmed operations throughout Latin America and Europe.[2][3][4]
S0483: IcedID
C0022: Operation Dream Job
Operation Dream Job was a cyber espionage operation likely conducted by Lazarus Group that targeted the defense, aerospace, government, and other sectors in the United States, Israel, Australia, Russia, and India. In at least one case, the cyber actors tried to monetize their network access to conduct a business email compromise (BEC) operation. In 2020, security researchers noted overlapping TTPs, to include fake job lures and code similarities, between Operation Dream Job, Operation North Star, and Operation Interception; by 2022 security researchers described Operation Dream Job as an umbrella term covering both Operation Interception and Operation North Star.[1][2][3][4]
C0061: Operation Digital Eye
Operation Digital Eye was conducted in June and July of 2024 by suspected People's Republic of China (PRC)-nexus threat actors targeting business-to-business IT service providers in Southern Europe. Operation Digital Eye activity included the use of Visual Studio Code tunnels for command and control (C2) and custom lateral movement capabilities. Overlaps in tooling between Digital Eye and previous China-nexus campaigns, Operation Soft Cell and Operation Tainted Love, indicate the potential use of shared vendors or digital quartermasters.[1]
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 | 8c3b7719d5bd… | ||
| 19.1 | 1.1 | Older bundle | 8c3b7719d5bd… |
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]Malware System Language Check
Pierre-Marc Bureau. (2009, January 15). Malware Trying to Avoid Some Countries. Retrieved August 18, 2021.
Open source URL - [2]CrowdStrike Ryuk January 2019
Hanel, A. (2019, January 10). Big Game Hunting with Ryuk: Another Lucrative Targeted Ransomware. Retrieved May 12, 2020.
Open source URL - [3]Darkside Ransomware Cybereason
Cybereason Nocturnus. (2021, April 1). Cybereason vs. Darkside Ransomware. Retrieved August 18, 2021.
Open source URL - [4]Securelist JSWorm
Fedor Sinitsyn. (2021, May 25). Evolution of JSWorm Ransomware. Retrieved August 18, 2021.
Open source URL - [5]SecureList SynAck Doppelgänging May 2018
Ivanov, A. et al. (2018, May 7). SynAck targeted ransomware uses the Doppelgänging technique. Retrieved May 22, 2018.
Open source URL - [6]mitre-attackT1614.001Open source URL
Source: MITRE ATT&CK®. © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation. MITRE ATT&CK and ATT&CK are registered trademarks of The MITRE Corporation. Glexia is not affiliated with or endorsed by MITRE.
