T1213.006: Databases
Adversaries may leverage databases to mine valuable information. These databases may be hosted on-premises or in the cloud (both in platform-as-a-service and software-as-a-service environments).
Examples of databases from which information may be collected include MySQL, PostgreSQL, MongoDB, Amazon Relational Database Service, Azure SQL Database, Google Firebase, and Snowflake. Databases may include a variety of information of interest to adversaries, such as usernames, hashed passwords, personally identifiable information, and financial data. Data collected from databases may be used for Lateral Movement, Command and Control, or Exfiltration. Data exfiltrated from databases may also be used to extort victims or may be sold for profit.[1]
Security context for executives and security teams
T1213.006: Databases describes Adversaries may leverage databases to mine valuable information. These databases may be hosted on-premises or in the cloud (both in platform-as-a-service and software-as-a-service environments). Examples of databases from which information may be collected include MySQL, PostgreSQL, MongoDB, Amazon Relational Database Service, Azure SQL Database, Google Firebase, and Snowflake. Databases may include a variety of information of interest to adversaries, such as usernames, hashed passwords, personally identifiable inf...
Executive priority
T1213.006: Databases 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 T1213.006: Databases by reviewing the official ATT&CK relationships, mapped tactics (collection), supported platforms (IaaS, Linux, macOS, SaaS), and available local telemetry before making detection or mitigation decisions.
Likely telemetry
- Official ATT&CK relationships and object metadata
- Cloud control-plane, SaaS audit, and container platform logs
- Network, endpoint, and security-tool telemetry
Detection direction
- Validate whether T1213.006: Databases 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.
Databases
Adversaries may leverage databases to mine valuable information. These databases may be hosted on-premises or in the cloud (both in platform-as-a-service and software-as-a-service environments).
Examples of databases from which information may be collected include MySQL, PostgreSQL, MongoDB, Amazon Relational Database Service, Azure SQL Database, Google Firebase, and Snowflake. Databases may include a variety of information of interest to adversaries, such as usernames, hashed passwords, personally identifiable information, and financial data. Data collected from databases may be used for Lateral Movement, Command and Control, or Exfiltration. Data exfiltrated from databases may also be used to extort victims or may be sold for profit.[1]
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 | T1213 | Data from Information Repositories | This object subtechnique of Data from Information Repositories. |
Groups, software, and campaigns
G0037: FIN6
G0034: Sandworm Team
Sandworm Team is a destructive threat group that has been attributed to Russia's General Staff Main Intelligence Directorate (GRU) Main Center for Special Technologies (GTsST) military unit 74455.[1][2] This group has been active since at least 2009.[3][4][5][6]
In October 2020, the US indicted six GRU Unit 74455 officers associated with Sandworm Team for the following cyber operations: the 2015 and 2016 attacks against Ukrainian electrical companies and government organizations, the 2017 worldwide NotPetya attack, targeting of the 2017 French presidential campaign, the 2018 Olympic Destroyer attack against the Winter Olympic Games, the 2018 operation against the Organisation for the Prohibition of Chemical Weapons, and attacks against the country of Georgia in 2018 and 2019.[1][2] Some of these were conducted with the assistance of GRU Unit 26165, which is also referred to as APT28.[7]
G1041: Sea Turtle
Sea Turtle is a Türkiye-linked threat actor active since at least 2017 performing espionage and service provider compromise operations against victims in Asia, Europe, and North America. Sea Turtle is notable for targeting registrars managing ccTLDs and complex DNS-based intrusions where the threat actor compromised DNS providers to hijack DNS resolution for ultimate victims, enabling Sea Turtle to spoof log in portals and other applications for credential collection.[1][2][3][4]
G0010: Turla
Turla is a cyber espionage threat group that has been attributed to Russia's Federal Security Service (FSB). They have compromised victims in over 50 countries since at least 2004, spanning a range of industries including government, embassies, military, education, research and pharmaceutical companies. Turla is known for conducting watering hole and spearphishing campaigns, and leveraging in-house tools and malware, such as Uroburos.[1][2][3][4][5]
G1057: ShinyHunters
ShinyHunters is a cyber criminal collective that has been active since at least 2019 operating under the ShinyCorp persona. ShinyHunters has targeted multiple industries and geographic regions gathering legitimate credentials and personally identifiable information (PII) for resale or extortion of victims. ShinyHunters has been associated with the broader collective called The Community, also known as The Com whose members have also included Scattered Spider and LAPSUS$. Public reporting has mentioned a variety of names for operations ShinyHunters members have reportedly conducted with members of other groups, including “Scattered Lapsus Hunters,” “Scattered Lapsus Shiny Hunters,” and “SLSH.”[1][2][3][4][5][6][7][8]
S0598: P.A.S. Webshell
P.A.S. Webshell is a publicly available multifunctional PHP webshell in use since at least 2016 that provides remote access and execution on target web servers.[1]
S9010: GlassWorm
GlassWorm is a worm that propagated through supply chain attacks by compromising repository credentials from victim environments and having malicious payloads added to those compromised accounts for distribution to victims across the various development ecosystems.[1][2][3] GlassWorm has numerous variants, including Rust binaries, encrypted JavaScript and a variant leveraging invisible Unicode characters that made reverse engineering difficult.[4][1][5] GlassWorm has employed a unique command and control (C2) methodology using Solana blockchain.[6][1] GlassWorm was first reported in October 2025.[6][1][3]
S1146: MgBot
S9041: TeamPCP Cloud Stealer
The TeamPCP Cloud Stealer is a comprehensive filesystem credential stealer that can harvest, encrypt, and exfiltrate credentials from over 50 sensitive file paths across CI/CD, cloud, developer tooling, and container environments. The TeamPCP Cloud Stealer was the primary payload used by TeamPCP in March 2026 during early stages of a cascading supply chain campaign targeting CI/CD workflows.[1][2][3][4][5][6][7][8]
C0062: Anthropic AI-orchestrated Campaign
The Anthropic AI-orchestrated Campaign was conducted in September 2025 by a likely China nexus espionage actor identified as GTG-1002. The Anthropic AI-orchestrated Campaign was a highly coordinated operation that manipulated Claude Code to perform reconnaissance, vulnerability discovery, exploitation, lateral movement, credential harvesting, data analysis, and exfiltration operations at approximately 30 entities in the technology, financial, chemical, and government sectors. During the Anthropic AI-orchestrated Campaign, human operators used Claude Code agents and Model Context Protocol (MCP) tools to automate cyber operations. Operators broke attacks into discrete tasks, used crafted prompts, and established personas to bypass AI guardrails, enabling the agents to execute the operations with minimal human involvement.[1][2]
C0040: APT41 DUST
APT41 DUST was conducted by APT41 from 2023 to July 2024 against entities in Europe, Asia, and the Middle East. APT41 DUST targeted sectors such as shipping, logistics, and media for information gathering purposes. APT41 used previously-observed malware such as DUSTPAN as well as newly observed tools such as DUSTTRAP in APT41 DUST.[1]
C0049: Leviathan Australian Intrusions
Leviathan Australian Intrusions consisted of at least two long-term intrusions against victims in Australia by Leviathan, relying on similar tradecraft such as external service exploitation followed by extensive credential capture and re-use to enable privilege escalation and lateral movement. Leviathan Australian Intrusions were focused on exfiltrating sensitive data including valid credentials for the victim organizations.[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(2)
| Release | Bundle imported | Object version | Modified | Status | Raw hash |
|---|---|---|---|---|---|
| 19.2 | 1.0 | Current bundle | a4f11e9c2d8c… | ||
| 19.1 | 1.0 | Older bundle | a4f11e9c2d8c… |
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]Google Cloud Threat Intelligence UNC5537 Snowflake 2024
Mandiant. (2024, June 10). UNC5537 Targets Snowflake Customer Instances for Data Theft and Extortion. Retrieved May 22, 2025.
Open source URL - [2]mitre-attackT1213.006Open 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.
