T1682: Query Public AI Services
Adversaries may query publicly accessible artificial intelligence (AI) services, such as large language models (LLMs), to support targeting and operations. In addition to searching websites or databases directly (i.e., Search Open Websites/Domains), adversaries may use AI services to synthesize, aggregate, and analyze publicly available information at scale. This may include identifying individuals or organizations to target, researching organizational structures and personnel, identifying technologies used by target organizations, researching business relationships to develop plausible pretexts for Social Engineering approaches, identifying contact information for use in Phishing or Phishing for Information, or gathering derogatory or sensitive information about individuals that may be used for extortion or coercion.[1][2]
Information gathered through AI services may be leveraged for other behaviors, such as establishing operational resources (i.e., Generate Content or Establish Accounts). For obtaining access to AI tools and services, see Artificial Intelligence.
Security context for executives and security teams
T1682: Query Public AI Services describes Adversaries may query publicly accessible artificial intelligence (AI) services, such as large language models (LLMs), to support targeting and operations. In addition to searching websites or databases directly (i.e., [Search Open Websites/Domains](https://attack.mitre.org/techniques/T1593)), adversaries may use AI services to synthesize, aggregate, and analyze publicly available information at scale. This may include identifying individuals or organizations to target, researching organizational structures and per...
Executive priority
T1682: Query Public AI Services 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 T1682: Query Public AI Services by reviewing the official ATT&CK relationships, mapped tactics (reconnaissance), supported platforms (PRE), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
Detection direction
- Validate whether T1682: Query Public AI Services 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.
Query Public AI Services
Adversaries may query publicly accessible artificial intelligence (AI) services, such as large language models (LLMs), to support targeting and operations. In addition to searching websites or databases directly (i.e., Search Open Websites/Domains), adversaries may use AI services to synthesize, aggregate, and analyze publicly available information at scale. This may include identifying individuals or organizations to target, researching organizational structures and personnel, identifying technologies used by target organizations, researching business relationships to develop plausible pretexts for Social Engineering approaches, identifying contact information for use in Phishing or Phishing for Information, or gathering derogatory or sensitive information about individuals that may be used for extortion or coercion.[1][2]
Information gathered through AI services may be leveraged for other behaviors, such as establishing operational resources (i.e., Generate Content or Establish Accounts). For obtaining access to AI tools and services, see Artificial Intelligence.
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.
Groups, software, and campaigns
G1044: APT42
APT42 is an Iranian-sponsored threat group that conducts cyber espionage and surveillance.[1] The group primarily focuses on targets in the Middle East region, but has targeted a variety of industries and countries since at least 2015.[1] APT42 starts cyber operations through spearphishing emails and/or the PINEFLOWER Android malware, then monitors and collects information from the compromised systems and devices.[1] Finally, APT42 exfiltrates data using native features and open-source tools.[2]
APT42 activities have been linked to Magic Hound by other commercial vendors. While there are behavior and software overlaps between Magic Hound and APT42, they appear to be distinct entities and are tracked as separate entities by their originating vendor.
G0094: Kimsuky
Kimsuky is a Democratic People's Republic of Korea (DPRK)-based cyber espionage group that has been active since at least 2012. The group initially targeted South Korean government agencies, think tanks, and subject-matter experts in various fields. Its operations expanded to include the United Nations and organizations in the government, education, business services, and manufacturing sectors across the United States, Japan, Russia, and Europe. Kimsuky has focused collection on foreign policy and national security issues tied to the Korean Peninsula, nuclear policy, and sanctions. Kimsuky operations have overlapped with those of other North Korean state-sponsored cyber espionage actors as a result of ad hoc collaborations or other limited resource sharing.[1][2][3][4][5][6]
Kimsuky was assessed to be responsible for the 2014 Korea Hydro & Nuclear Power Co. compromise; other notable campaigns include Operation STOLEN PENCIL (2018), Operation Kabar Cobra (2019), and Operation Smoke Screen (2019).[7][8][9] In 2023, Kimsuky was observed using commercial large language models (LLMs) to assist with vulnerability research, scripting, social engineering and reconnaissance.[10]
DPRK threat actor cluster boundaries overlap in open source reporting, with some security researchers consolidating all attributed North Korean state-sponsored cyber activity under Lazarus Group, rather than tracking operationally distinct subgroups.
C0064: AI-Assisted Breach of Mexico's Government Infrastructure
The AI-Assisted Breach of Mexico's Government Infrastructure is a campaign where human operators used Claude Code AI and OpenAI GPT GPT-4.1 AI to perform reconnaissance, vulnerability exploitation, privilege escalation, discovery, credential harvesting, and exfiltration operations. The attack impacted several Mexican government institutions including the Federal Tax Authority (Servicio de Administracion Tributaria), Mexico State Government (Estado de Mexico), Mexico City Civil Registry (Registro Civil de CDMX), Jalisco State Government, National Electoral Institute (Instituto Nacional Electoral), Michoacan State Government, SADM Monterrey Municipal Water Utility (Agua y Drenaje), Tamaulipas State Government, and the Mexico City Health Department (Salud CDMX). The attack resulted in the theft of large amounts of sensitive government data and civilian records. [1]
All related ATT&CK context
Mitigation direction
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(4)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 20.1 | 1.0 | Current bundle | bb518b68a8f9… | ||
| 20.0 | 1.0 | Older bundle | 5b9e9621bce9… | ||
| 19.2 | 1.0 | Older bundle | 5b9e9621bce9… | ||
| 19.1 | 1.0 | Older bundle | 5b9e9621bce9… |
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]MSFT-AI
Microsoft Threat Intelligence. (2024, February 14). Staying ahead of threat actors in the age of AI. Retrieved March 11, 2024.
Open source URL - [2]GTIG AI Threat Tracker
Google Threat Intelligence Group . (2026, February 12). GTIG AI Threat Tracker: Distillation, Experimentation, and (Continued) Integration of AI for Adversarial Use. Retrieved March 25, 2026.
Open source URL - [3]mitre-attackT1682Open source URL
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