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Data from a BRAWL Automated Adversary Emulation Exercise
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One of the challenging problems for cyber security researchers developing detection and response capabilities is finding a realistic environment in which to test their hypothesis and capabilities.

The cheapest method is to test capabilities on a small lab network. But this environment is lacking the scale of real enterprise network and the noise of real environments that makes detection much harder. In many ways, the best environment would be testing on multiple enterprise scale networks with a controlled but realistic attacker and real noise from users, system administrators, and third party software/devices. The challenge with testing in this environment is that it is expensive and in some scenarios high risk.

BRAWL seeks to create a compromise by creating a system to automatically create an enterprise network inside a cloud environment. OpenStack is the only currently supported environment, but it is being designed in such a way as to easily support other cloud environments in the future. BRAWL also builds an analysis network containing a data ingest and processing pipeline using LogStash and Kafka. As part of the analysis network, it creates an event storage and search system using Elasticsearch and Kibana. BRAWL spins up a enterprise network "Game Board" with Windows images. These images have Microsoft Sysmon and other sensors already installed and configured to forward logs into the data ingest framework.

BRAWL also has a concept of bots, which can be either Red, Blue, or Gray. Red bots are offensive, Blue bots are defensive, and Gray bots emulate legitimate user behavior in order to provide noise to make detection more difficult. When a user wants to test research hypotheses, they implement a BRAWL bot. The BRAWL bot registers itself with the BRAWL Controller, which then orchestrates games between BRAWL bots on the Game Board.

Data Release

Note: Due to issues with file sizes and GitHub quotas, we are placing all the files into a zip file instead of leaving them as plain text in the git repo. All the data is in the file

This release consists of some data from a BRAWL prototype. We created a small enterprise network, described below. We then ran a single game using the MITRE CALDERA research project as a red bot.

CALDERA is a related MITRE research project that automates adversary emulation activity based on the information in Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) model. It implements a set of ATT&CK tactics and techniques and uses a planning system ( to automate the actuation of those techniques and generate post-compromise adversary behavior within an enterprise network.

This data is released under the Creative Commons BY License

Network & Sensor Description

Our small enterprise network is a flat network that consists of a Domain Controller ( and 16 workstations. Each PC has the name of the primary user in the pc name (e.g. user beane typically logs into beane-pc). That user has Local Administrator privileges on the computer.

All the PCs are running Windows 8.1. The Domain controller is running Windows Server 2012 R2.

On the Windows 8 PCs, we made changes to enable WDigest to keep plaintext passwords in LSASS's memory using the following registry command: reg ADD HKLM\SYSTEM\CurrentControlSet\Control\SecurityProviders\WDigest\ /v UseLogonCredential /t REG_DWORD /d 1 /F

Scenario Description

For this exercise, CALDERA was the only BRAWL bot participating. While conceptually BRAWL can be used to test a variety of attacker behaviors and detection, many of MITRE's research efforts follow an "assume breach" philosophy. Therefore we give CALDERA a starting point as a Local Administrator on a box on the network at the beginning of the exercise.

Also, without a Grey bot performing logon across different hosts, the BRAWL Game Board is sterile from the perspective of credentials that can be stolen and used by Red bots. To enable lateral movement, the BRAWL Controller uses psexec to create logon events on hosts with the credentials of other users from the network.

CALDERA Performed the following ATT&CK Techniques during the exercise:


There are five types of data in this repository. Each is contained in its own file in the data/ folder.

Data Type Description
game_metadata Data describing the BRAWL scenario
sysmon Data gathered from Sysmon running on each of the workstations
win_event Windows Event Logs
computer_properties Data gathered from custom scripts that provides some information about the computers in the network
bsf Red bot actions in BRAWL Shared Format (BSF)

BRAWL Shared Format

Red bots and blue bots are encouraged to log information about their activities or detections in BRAWL Shared Format (BSF). The goal of this is to make it easier to compare blue bot detection/actions with red bot actions.

The format is currently in development and could change in future data sets.

The fields for BSF are described below in the Data Sources Detail section.

Notes About Time

Different event sources in BRAWL handle time differently. The time is either the time that an event hit our logging ingest framework, the time the event was generated on the host/endpoint, or the time recorded by a bot on the network. In general those times should be within a few milliseconds of each other. When possible the logging ingest framework uses the event time stored in the event instead of the time of the event hitting the ingest nodes. The table below details the method used for each data type.

Data Source Time Notes
computer_properties from the time field
game_metadata time it hits the ingest framework
sysmon from the utc_time field
win_event pulled from the windows event time
bsf The @timestamp field is time it hits the ingest framework. However the time related BSF fields (e.g. happened_after,happened_before, etc) are the times the events started or ended based on the time on CALDERA's command and control server.

Data Sources Detail


Field Name Description
@timestamp Time related to the event. See note about time above.
@uuid Unique Event ID
game_id The unique game_id for this exercise.
type Event Type. Always game_metadata for these records
hosts A list of hosts that were a part of the exercise and "in bounds" for the red bot
randomization_seed A seed that can be used by BRAWL Bot Participants to implement "random" behavior that is that same across executions of BRAWL
starting_host host that the red bot starts on.


Field Name Description
@timestamp Time related to the event. See note about time above.
@uuid Unique Event ID
type Event Type. Always sysmon for these records
game_id The unique game_id for this exercise.
data_model.object The CAR object being acted on.
data_model.action The CAR action being performed on the object. This field is an array because some events can correspond to more than one action in the CAR data model. An example of this is remote thread creation events.
data_model.fields.* The fields relevant for the given object/action pair.
game_id The unique game_id for this exercise.
host Hostname that the event was logged from.

We are using Sysmon v3.11. sysmon_config.txt contains the output of the sysmon -c command detailing our configuration.

Sysmon generates many different kinds of events, that map to different CAR object/action pairs. The fields for each type are explained in more detail on the CAR website:

The object/action pairs that are generated by Sysmon in our configuration are:

  • driver/load
  • file/attr_modify
  • flow/start
  • module/load
  • process/create
  • process/terminate
  • thread/create
  • threat/remote_create

Use the CAR data model to determine the field names and semantics for fields contained in data_model.fields.* for each object/action pair above.


Field Name Description
@timestamp Time related to the event. See each event below for details on how this is calculated
@uuid Unique Event ID
type Event Type. Always win_event for these records
game_id The unique game_id for this exercise.
host Host that logged the event
raw The windows event log entry in it's raw XML format
data_model.fields.log_name Windows Log name (Application, System, or Security)
data_model.fields.log_type The log type for a given log_name


Field Name Description
@timestamp Time related to the event. See note about time above.
@uuid Unique Event ID
type Event Type. Always computer_properties for these records
game_id The unique game_id for this exercise.
host Name of computer that the script ran on
netinfo Collection of netinfo objects
netinfo.DNSServers collection of DNS resolvers configured for this host
netinfo.Gateway Gateway for this interface
netinfo.IPAddress IPAddresses for this interface
netinfo.IsDHCPEnabled Is DHCP Enabled?
netinfo.MACAddress MAC Address for this interface
netinfo.SubnetMask Subnet Mask for respective IP addresses
pcinfo Object describing information about the PC
pcinfo.AssetTag AssetTag if accessible
pcinfo.CPU Information about CPU(s)
pcinfo.ChassisType Not used in BRAWL. "Unknown"
pcinfo.Disks Information about attached disk(s)
pcinfo.DomainName domain system is a part of
pcinfo.LastBootUpTime Time system booted
pcinfo.Memory Information about memory on the systems
pcinfo.OS Information about the running OS
pcinfo.SerialNumber HW Serial Number
time Time that the script ran
userinfo Array containing userinfo objects describing users who have logged onto the system since last boot
userinfo.AuthenticationPackage Authentication Package used for authentication
userinfo.Domain Domain (or local pc) account belongs to
userinfo.LogonId LogonId
userinfo.LogonTime Time of logon
userinfo.LogonType Windows Logon Type Constants
userinfo.LogonTypeName Description of LogonType
userinfo.UserName UserName of principal logging on

This data was collected periodically using the unified_json.ps1 module from MITRE's PowerShell Utilities for Security Situational Awareness. The userinfo field can be useful in determining which credentials may have been compromised if a credential dumper such as Mimikatz was run on the system.


Field Name Description
@timestamp Time related to the event. See note about time above.
@uuid Unique Event ID
type Event Type. Always bsf_events for these records
game_id The unique game_id for this exercise.
bsf Array of BSF events describing bot activity. Fields for this array are described in more detail below.
bsf_version Version of the BSF schema used for bsf array of events
producer_id Bot that produced this BSF data.

The objects inside of the bsf array field are of type operation, step, or event. All objects have a nodetype field that can be used to determine the object type

event BSF Object

Field Description
id A unique identifier for each event.
nodetype This node's type. One of: {"operation", "step", "event"}.
host Hostname or IP at which this event was enacted / detected.
time Note: At least one of the following three time fields (i.e., "time", "happened_after", or "happened_before") must be reported. "time" is especially desired; all three are encouraged. Please see note 1 in General Notes below.

Note on time format: All time information must be in ISO 8601 format. More specifically as: 'yyyy-mm-ddThh:nn:ss.llll00'. Where y is year, m is month, d is day, h is hour, n is minute, s is second, l is millisecond (and there are two trailing zeros). For example: 2017-02-22T18:38:14.060000

Optional: Estimate of the time this event occurred.
happened_after Optional: An early bound ("temporal left bracket") on uncertainty in "time".
happened_before Optional: A late bound ("temporal right bracket") on uncertainty in "time".
confidence Optional: Enables blue bots to communicate confidence (a real number between 0.0 and 1.0) in this event's association with an attack.
object Object acted upon; see table below for permissible values. Loosely based on the CAR Data Model
action Actions for a given object. Loosely based on the CAR Data Model
specific_field_1 .. N 1-N descriptive attributes (see below). Loosely based on the CAR Data Model

Object/Action/Fields Information for Event Objects

Object Action Required Field(s) Optional Fields(s)
process create
At least one of:
     {pid, command_line, exe, image_path}
flow start
At least one of:
At least one of:
    {dest_hostname, dest_ip}
At least one of:
     {src_port, dest_port, protocol}
file create
file_path company

You can read more about the semantics of the Required and Optional Fields by finding the associated object in the CAR Data Model

step BSF Object

Step objects connect one or more events together into a higher level grouping of activity. Step objects also present a place for BSF emitters to label activity with ATT&CK labels.

Field name Description
id A unique identifier for operation steps.
nodetype This node's type. One of: {"operation", "step", "event"}.
attack_info An array of technique objects (defined in the table directly below), describing how this step relates to the ATT&CK taxonomy. Why an array? Although a single technique often describes a step and all its events, in some cases, multiple techniques can be implemented.
attack_info.technique_id An ATT&CK technique ID (e.g., "T1059") describing the attack mechanism red employed in this step and its referenced events.
attack_info.technique_name A human readable string describing this technique (e.g., "Command-Line Interface").
attack_info.tactic An array of one or more ATT&CK tactic labels describing the intent/strategy of this technique. (Note that a single technique can exercise multiple tactics.) For example: ["Lateral Movement", "Execution"]
description Optional: Notes or annotations for this step go here.
events An array of ids of the event objects comprising this step.

operation BSF Object

Operation objects connect multiple step objects together. However there are no Operation objects present in this data set.

General BSF Notes

Descriptions and Notes for Event Fields (especially "At least one of"s):

  1. Time fields.
  2. Punctiliar Time. Activities such as a file deletion are essentially punctiliar, having a single time of occurrence which can be provided via the time field. However, it is possible that neither red nor blue will know this exact timestamp. For example, red bots may spawn a process to accomplish some action within a time window, but the exact time the action occurs is unknown. Blue bots can use sensors which may involve detection delays. Thus, BSF also provides two time fields happened_after and happened_before as temporal left and right brackets respectively, defining bounds on an uncertainty interval for the actual event. At least one of these three fields (i.e., time, happened_after, happened_before) must be reported with each event object. The other fields are optional, but should be reported as they are known. In particular, bots are encouraged to report a value for "time" which is their best guess, even if they do not have an exact time.
  3. Durative Time. Activities such as a flow are durative in nature, spanning a time period. BSF generally addresses durative activities by recording the end points of their interval as punctiliar times. Thus a flow start event requires one of {time, happened_after, happened_before}, as does the flow end event. However, some blue sensors may detect a durative activity in mid-course (e.g., a scanner which periodically scans the state of all processes, and determines one has become malicious). For flows, mid-course flow detections can be reported as "flow, message, time, ... (other fields)". For processes, mid-course flow detections can be reported as "process, scanned, time, ... (other fields)".
  4. Process identification. Ideally, a pid is used to identify a process, however the pid is not always known, especially by the red bot. Alternatively, the command_line spawning the process, or the exe / image_path which was executed can be provided.
  5. Flow ports. The source and destination ports in flows can be described by either a hostname or an IP address.
  6. In this data set, the only bot participating is CALDERA, therefore the only BSF records present are from CALDERA.


Hosts on our BRAWL network for this game:

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