1200KM / simulation
T1213.006 Databases — Attack Simulation
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…
Technique description
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…
No compatible procedure was found in the pinned Atomic index. This is a support gap, not a finding of technical impossibility.
Official ATT&CK definition · Detection rules and anomaly models
Documented simulation candidates
No compatible documented candidate in the pinned snapshot. This is a support gap, not technical impossibility.
Connected ecosystem references
Linked tags
Detection and collection
Attack tools
No reviewed association in this snapshot.
Threat actor context
These are explicit actor-to-technique associations in the existing Threat Matrix snapshot, not attribution of an event or proof that a detector identifies the actor. No tool-to-actor relationship is inferred.
Existing research
Pinned research references. No browser attack runner, live simulation result or validated detector is asserted. Source mappings and validation limits are preserved. ATT&CK / Atomic provenance · Detection provenance.