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A Python based ingestor for BloodHound
Quick Overview
BloodHound is an open-source tool for analyzing Active Directory environments. It uses graph theory to reveal hidden and often unintended relationships within an AD network, helping security professionals and attackers alike to identify complex attack paths that would otherwise be difficult to discover.
Pros
- Provides a visual representation of AD relationships, making it easier to understand complex network structures
- Helps identify potential security vulnerabilities and attack paths in AD environments
- Offers powerful query capabilities to find specific weaknesses or misconfigurations
- Integrates well with other security tools and penetration testing frameworks
Cons
- Can be resource-intensive when analyzing large AD environments
- Requires careful handling of sensitive data collected during enumeration
- May trigger security alerts or be flagged as malicious by some antivirus software
- Learning curve can be steep for users unfamiliar with graph theory or Cypher query language
Getting Started
To get started with BloodHound:
- Install Neo4j Community Edition
- Download the latest BloodHound release from the GitHub repository
- Run the SharpHound collector on a domain-joined Windows machine:
.\SharpHound.exe -c All
- Import the collected data into BloodHound
- Use the GUI or Cypher queries to analyze the AD environment
For detailed installation and usage instructions, refer to the official documentation on the BloodHound GitHub repository.
Competitor Comparisons
A Python based ingestor for BloodHound
Pros of BloodHound.py
- Written in Python, making it more lightweight and easier to run on various systems
- Can be used as a Python library, allowing for integration into other tools and scripts
- Supports direct output to Neo4j database, streamlining the data collection process
Cons of BloodHound.py
- Lacks the graphical user interface provided by BloodHound
- May have fewer features and less comprehensive data collection compared to the full BloodHound suite
- Requires more manual interpretation of results without the visual graph representation
Code Comparison
BloodHound (JavaScript):
this.state = {
sigmaInstance: null,
design: null,
dragged: false,
firstDraw: true,
session: driver.session()
};
BloodHound.py (Python):
def __init__(self, username, password, domain, host):
self.username = username
self.password = password
self.domain = domain
self.host = host
self.ldap = None
Both repositories focus on Active Directory enumeration and analysis, but they approach it differently. BloodHound provides a comprehensive suite with a graphical interface, while BloodHound.py offers a more lightweight, Python-based alternative that can be easily integrated into other tools or workflows. The choice between them depends on the specific use case and environment requirements.
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Latest Version of BloodHound Community Edition is Released
For the latest version of BloodHound you may follow this link to the BloodHound Community Edition repository.
Deprecation Notice
This repository will be archived in the near future.
Getting Started with BloodHound
To get started with BloodHound, check out the BloodHound docs.
About BloodHound
BloodHound is a single page Javascript web application, built on top of Linkurious, compiled with Electron, with a Neo4j database fed by a C# data collector.
BloodHound uses graph theory to reveal the hidden and often unintended relationships within an Active Directory or Azure environment. Attackers can use BloodHound to easily identify highly complex attack paths that would otherwise be impossible to quickly identify. Defenders can use BloodHound to identify and eliminate those same attack paths. Both blue and red teams can use BloodHound to easily gain a deeper understanding of privilege relationships in an Active Directory or Azure environment.
BloodHound was created by @_wald0, @CptJesus, and @harmj0y.
BloodHound is maintained by the BloodHound Enterprise team.
About BloodHound Enterprise
BloodHound Enterprise is an Attack Path Management solution that continuously maps and quantifies Active Directory Attack Paths. You can remove millions, even billions of Attack Paths within your existing architecture and eliminate the attackerâs easiest, most reliable, and most attractive techniques.
Downloading BloodHound Binaries
Pre-Compiled BloodHound binaries can be found here.
The rolling release will always be updated to the most recent source. Tagged releases are considered "stable" but will likely not have new features or fixes.
Creating example data
A sample database generator can be found here
You can create your own example Active Directory environment using BadBlood.
License
BloodHound uses graph theory to reveal hidden relationships and attack paths in an Active Directory environment. Copyright (C) 2016-2023 Specter Ops Inc.
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.
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A Python based ingestor for BloodHound
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