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YAML administration data sources
In this YAML file you can administrate your available data sources and score their quality. You can find more information on data quality here.
Sample file: data-sources-endpoints.yaml
Current version: version 1.1
Version 1.0 can be found here.
Name | Type | Required | Description |
---|---|---|---|
version | string | yes | Version of this data source administration file. The current version is 1.1. |
file_type | string | yes | Used to indicate what type of YAML file it is. Possible values: data-source-administration, technique-administration and group-administration. For data source administration the value should be: data-source-administration . |
name | string | yes | Describes for what type of assets you describe the data sources for. E.g. endpoints. It is just a name which will be used in different places of the output. |
domain | string | yes (defaults to enterprise-attack ) |
Specify the ATT&CK domain using the value enterprise-attack , ics-attack or mobile-attack
|
systems | list of system objects | yes | Contains a list of applicable_to values, as used within the data source details object, combined with the relevant ATT&CK platforms. |
data_sources | list with data source global objects | yes | Contains all the data sources for which information is administrated. See the description of the data source global object. |
exceptions | list with ATT&CK technique IDs | no | Contains a list of ATT&CK technique IDs. Adding an ID result in removing that technique from any derived output. For example, it will be excluded when generating a technique YAML administration file using: python dettect.py ds -f sample-data/data-sources-endpoints.yaml --yaml
|
notes | string | no | An optional field to include notes on this groups administration file. |
This object specifies the ATT&CK platforms that apply to the applicable_to
values as used within the data source details object.
Name | Type | Required | Description |
---|---|---|---|
applicable_to | string | Yes | Specify the type of system. This is a free format text field, so any string value is valid except for 'all'. The value 'all' is reserved and cannot be used. 'all' can be used as a value in a data source details object's kv-pair applicable_to . The value 'all' will result in that particular data source details object to be effective for all type of systems (i.e. applicable_to 's) specified in this Systems object. |
platform | string or list of strings | yes | Indicates ATT&CK platform(s) relevant for this particular applicable_to value. Possible values (in the list) are the MITRE ATT&CK platform values or 'all' to select all platforms: PRE, Windows, Linux, macOS, Office 365, Azure AD, Google Workspace, IaaS, SaaS, Network, Containers. |
This object only contains the name of the data source and the key-value pair data_source
, which includes all the details regarding the data source within a data source details object.
Name | Type | Required | Description |
---|---|---|---|
data_source_name | string | yes | The name of the data source according to MITRE ATT&CK. E.g. Process Creation. A specific data source name value can only be part of a data source administration file once. |
data_source | list of data source details objects | yes | Contains the details regarding data sources divided using the key-value pair applicable_to . |
You can have multiple data source details objects to score the same data source (e.g. Process monitoring), but for different types of systems (e.g. Windows endpoints, Crown jewel X, Linux servers, Azure IaaS, etc.). The key-value pair applicable_to
indicates the type of system(s) the details apply to. Please note that a system can only be part of one applicable_to
key-value pair for the same data source.
We recommend using the same applicable_to
values between your data source and technique administration file. More info on this topic can be found on the Wiki.
Name | Type | Required | Description |
---|---|---|---|
applicable_to | list of strings | yes | Specify to which type of system this data source applies by choosing one of the system's applicable_to values. Use the value ['all'] to let it apply to every type of system. When setting the value to `['all'] no other values should be used. |
date_registered | date yyyy-mm-dd | yes | Date of registration of the data source in this YAML file. |
date_connected | date yyyy-mm-dd | yes | Date when the data source is connected to your security data lake. This date is used to draw a graph indicating the progress of connected data sources. |
products | list | yes | A list with one or more products where the data source data is located. E.g. Windows event log. |
available_for_data_analytics | boolean | yes | Indicates if the data source is available in such a way that blue teamers can use it for data analytics. This property has no impact on the output generated by the DeTTECT CLI. It can influence the output when used within an EQL query. |
comment | string | yes | An option to comment on this data source. If you want to have a multiline comment in the Excel output. We recommend making use of | . For more info have a look at: https://yaml-multiline.info/. |
data_quality | data quality object | yes | The scores on the five different data quality dimensions. See the description of the data quality object. |
The five data quality dimensions are explained here.
Name | Type | Required | Description |
---|---|---|---|
device_completeness | int | yes | Score between 0-5. Scoring this aspect is explained in a separate section. |
data_field_completeness | int | yes | Score between 0-5. Scoring this aspect is explained in a separate section. |
timeliness | int | yes | Score between 0-5. Scoring this aspect is explained in a separate section. |
consistency | int | yes | Score between 0-5. Scoring this aspect is explained in a separate section. |
retention | int | yes | Score between 0-5. Scoring this aspect is explained in a separate section. |
- Home
- Introduction
- Installation and requirements
- Getting started / How to
- Changelog
- Future developments
- ICS - Inconsistencies
- Introduction
- DeTT&CT data sources
- Data sources per platform
- Data quality
- Scoring data quality
- Improvement graph