Python-Adsimulator: A realistic simulator of Active Directory domains

adsimulator: a realistic simulator of Active Directory domains

Author: Nicolas Carolo [email protected]

Copyright: © 2022, Nicolas Carolo.

Date: 2022-01-09

Version: 1.0.0

PURPOSE

adsimulator is a graph-based tool for the simulation of realistic Active Directory environments. The graph models are generated according to a customizable list of requirements and represent the relationships between the nodes of an Active Directory domain. Finally, graphs are stored in a Neo4j graph database instance. This tool is inspired by DBCreator, but it provides more features.

The ability to generate graphs according to specific requirements is the most relevant functionality offered by adsimulator. For example, it is possible to generate environments affected by vulnerabilities (e.g., various types of ACL misconfigurations, inadequate security policies) that make them possible targets of cyber-attacks, such as AS-REP Roasting and DCSync. In addition, it is possible to choose the size of Active Directory environments by setting up the number of domain trusts, Security Principals, OUs, and GPOs. Moreover, it is possible to set the probabilities associated with object properties.

The following table summarizes the most relevant parameters used in the generation of an Active Directory domain.

Object Property Description Value
ACL ACLsProbability Probability of each access control right (e.g., GenericAll, AddMember, WriteDacl) Integer for each right (0-100). The sum of the probabilities must be equal to 100
Computer nComputers Number of computers Integer > 0
Computer CanRDPFromUserPercentage
CanRDPFromGroupPercentage
Maximum percentage of computers with CanRDP edges from users groups. Integer (0-100)
Computer CanPSRemoteFromUserPercentage
CanPSRemoteFromGroupPercentage
Maximum percentage of computers with CanPSRemote edges from users groups Integer (0-100)
Computer ExecuteDCOMFromUserPercentage
ExecuteDCOMFromGroupPercentage
Maximum Percentage of computers with ExecuteDCOM edges from users groups Integer (0-100)
Computer AllowedToDelegateFromUserPercentage
AllowedToDelegateFromComputerPercentage
Maximum percentage of users computers with AllowedToDelegate edges Integer (0-100)
Computer
DC
User
enabled Probability that an object is enabled Integer (0-100)
Computer
User
unconstraineddelegation Probability that an object has unconstrained delegation enabled Integer (0-100)
Computer
DC
osProbability Probability of each OS version Integer for each OS version (0-100).
The sum of the probabilities must be equal to 100
Domain functionalLevelProbability Probability of each functional level value Integer for each functional level (0-100).
The sum of the probabilities must be equal to 100
Domain Trusts Number of Inbound, Outbound and Bidirectional trusts Integer >= 0
GPO nGPOs Number of GPOs Integer > 0
Group nGroups The number of groups nteger > 0
OU nOUs Number of OUs Even integer > 0
User nUsers Number of users Integer > 0
User dontreqpreauth Probability that a user has Kerberos pre-authentication disabled Integer (0-100)
User hassp Probability that a user has a SPN Integer (0-100)
User passwordnotreqd Probability that a user does not have a login password Integer (0-100)
User pwdneverexpires Probability that a user’s password never expires Integer (0-100)
User sidhistory Probability that a user previously belonged to another domain Integer (0-100)

Structure of simulated Active Directory domains

The graph generated by adsimulator contains nodes and edges. Nodes represent the domain objects, while edges represent the relationships between objects.

Nodes represent the following Active Directory objects:

  • Domains
  • Organizational Units (OUs)
  • Groups
  • Users
  • Computers
  • Group Policy Objects (GPOs)

Edges represent the following relationships:

  • Domain/OU to OU, Domain/OU to Security Principal: Contains
  • Domain to Domain: TrustedBy
  • Security Principal to Group: AddMember, MemberOf
  • Security Principal to Computer: AdminTo, CanPSRemote, CanRDP, ExecuteDCOM
  • User to Computer: HasSession
  • ACLs: AllExtendedRights, AddAllowedToAct, AllowedToAct, AllowedToDelegate, ForceChangePassword, GenericAll, GenericWrite, GetChanges, GetChangesAll, Owns, WriteDacl, WriteOwner
  • GPO to Domain/OU: GpLink

For more details about relationships, you can consult the official BloodHound guide.

This graph shows an example of how users and computers are organized in Organizational Units and in the domain. Yellow nodes represent users, violet nodes represent computers, blue nodes are Organizational Units, and the red node is the domain. The green node denotes the compromised user who was exploited for enumerating the Active Directory domain represented by the graph model. Users and computers are contained in Organizational Units and Organizational Units are contained in the domain.

Domain structure

MINIMUM REQUIREMENTS

Supported OS

  • Linux
  • macOS

Interpreter and tools

  • Python 3
  • Neo4j

INSTALLATION

Linux

  1. Install Neo4j
  2. Create a new Neo4j database instance with the following credentials:
    • Username: neo4j
    • Password: password
  3. Install apoc plugin
  4. Append the following lines to the settings file:
    apoc.import.file.enabled=true
    apoc.import.file.use_neo4j_config=false
    apoc.export.file.enabled=true
    
  5. Install adsimulator running the following commands:
    git clone https://github.com/nicolas_carolo/adsimulator
    cd adsimulator
    ./installer_linux.sh
    pip install -r requirements.txt
    python setup.py install

macOS

  1. Install Neo4j
  2. Create a new Neo4j database instance with the following credentials:
    • Username: neo4j
    • Password: password
  3. Install apoc plugin
  4. Append the following lines to the settings file:
    apoc.import.file.enabled=true
    apoc.import.file.use_neo4j_config=false
    apoc.export.file.enabled=true
    
  5. Install adsimulator running the following commands:
    git clone https://github.com/nicolas_carolo/adsimulator
    cd adsimulator
    ./installer_darwin.sh
    pip install -r requirements.txt
    python setup.py install

USAGE

Running

$ adsimulator

Commands

  • dbconfig - Set the credentials and the database URL
  • connect - Connect to the database using supplied credentials
  • setparams - Import the settings JSON file containing the parameters for the graph generation. Here, a template you can use for customizing setting and generate different Active Directory models.
  • setdomain - Set the domain name
  • cleardb - Clear the database and set the schema properly
  • generate - Connect to the database, clear the DB, set the schema, and generate the random graph model. If you use this command followed by a file path (e.g., generate /tmp/testlab.json), you can export the graph model as a JSON file.
  • exit - Exit

View generated graph models

The generated graph models are available at http://localhost:7474/, where we can execute Cypher queries for generating graphs. Here, some examples of Cypher queries.

Neo4j Web Interface

COPYRIGHT

Copyright © 2022, Nicolas Carolo. All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

  1. Redistributions of source code must retain the above copyright notice, this list of conditions, and the following disclaimer.

  2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution.

  3. Neither the name of the author of this software nor the names of contributors to this software may be used to endorse or promote products derived from this software without specific prior written consent.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

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