Attack Ent T1614 System Location Discovery

MITRE ATT&CK T1614: System Location Discovery

When to use this skill

Use this skill when the task involves T1614, System Location Discovery, enterprise ATT&CK, TTP mapping, detection engineering, hunting, incident-response enrichment, control validation, or authorized adversary-emulation planning. Treat it as a defensive analysis aid: keep outputs focused on understanding, detecting, mitigating, and safely validating this ATT&CK technique.

Technique context

• ATT&CK domain: enterprise
• ATT&CK ID: T1614
• Technique name: System Location Discovery
• Type: technique
• ATT&CK URL: https://attack.mitre.org/techniques/T1614
• Tactics: discovery
• Platforms: IaaS, Linux, macOS, Windows
• Required permissions: Not specified
• Effective permissions: Not specified
• Defenses bypassed: Not specified

ATT&CK description

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.(Citation: FBI Ragnar Locker 2020)(Citation: Sophos Geolocation 2016)(Citation: Bleepingcomputer RAT malware 2020) Windows API functions such as GetLocaleInfoW can also be used to determine the locale of the host.(Citation: FBI Ragnar Locker 2020) In cloud environments, an instance's availability zone may also be discovered by accessing the instance metadata service from the instance.(Citation: AWS Instance Identity Documents)(Citation: Microsoft Azure Instance Metadata 2021)

Adversaries may also attempt to infer the location of a victim host using IP addressing, such as via online geolocation IP-lookup services.(Citation: Securelist Trasparent Tribe 2020)(Citation: Sophos Geolocation 2016)

Agent workflow

1. Clarify scope: identify the system, asset class, log sources, cloud or endpoint platform, and whether the user wants triage, detection, coverage assessment, or safe emulation planning.
2. Load bundled resources as needed: use references/technique-profile.json for structured metadata, references/detection-and-mitigation.md for triage and telemetry guidance, references/known-threat-context.md for ATT&CK relationship context, and templates/ for repeatable outputs.
3. Map observations to ATT&CK: compare the user's evidence to the ATT&CK description, tactics, platforms, and known procedure patterns before asserting a match.
4. Produce defensive outputs: prioritize hypotheses, telemetry requirements, detection logic ideas, validation steps, containment guidance, and mitigations.
5. Preserve uncertainty: distinguish confirmed evidence, plausible indicators, assumptions, and gaps. Recommend what to collect next.
6. Stay safe: do not provide malware, credential theft, persistence, evasion, destructive automation, or unauthorized exploitation instructions. For adversary emulation, keep steps bounded to approved lab or control-validation contexts and omit operational abuse details.

Bundled resources

• references/technique-profile.json: machine-readable ATT&CK metadata for this technique.
• references/detection-and-mitigation.md: detection notes, telemetry checklist, triage questions, mitigation candidates, and false-positive considerations.
• references/known-threat-context.md: ATT&CK relationship context with attribution cautions.
• templates/detection-brief.md: detection engineering brief template.
• templates/hunt-plan.md: threat hunt plan template.
• templates/incident-response-note.md: incident response note template.
• templates/coverage-assessment.md: ATT&CK coverage assessment template.
• scripts/render_brief.py: local helper that renders a Markdown defensive brief from technique-profile.json.
• assets/output-schema.json: JSON schema for structured technique analysis outputs.

To generate a quick brief, run python scripts/render_brief.py --output brief.md from inside this skill directory, or adapt the templates directly.

Detection guidance

No ATT&CK detection guidance was present in the source STIX object.

Useful telemetry and data sources

• Not specified in the STIX object.

Mitigations to consider

• No ATT&CK mitigation relationships were present in the source STIX bundle.

Known threat context

Use these examples only as contextual leads, not as proof that an observed event is this technique:

• Amadey (malware)
• AshTag (malware)
• Crimson (malware)
• Cuckoo Stealer (malware)
• DarkGate (malware)
• DarkWatchman (malware)
• GlassWorm (malware)
• Gootloader (malware)
• GrimAgent (malware)
• HexEval Loader (malware)
• InvisibleFerret (malware)
• PlugX (malware)
• PureCrypter (malware)
• QuasarRAT (tool)
• Raccoon Stealer (malware)
• Ragnar Locker (malware)
• RedLine Stealer (malware)
• Remcos (tool)
• SDBbot (malware)
• Saint Bot (malware)

Recommended output pattern

When responding with this skill, structure the answer as:

• Assessment: whether the evidence supports this ATT&CK mapping and why.
• Evidence: specific indicators, logs, behaviors, and assumptions.
• Detection: telemetry sources, analytic logic, and tuning considerations.
• Response: containment, eradication, recovery, and validation actions.
• Coverage gaps: missing logs, sensors, controls, or environmental details.
• References: include the ATT&CK URL and any user-provided evidence references.

ATT&CK contributors

• Pooja Natarajan, NEC Corporation India
• Hiroki Nagahama, NEC Corporation
• Manikantan Srinivasan, NEC Corporation India
• Wes Hurd
• Katie Nickels, Red Canary