BloodHound is a monolithic web application composed of an embedded React frontend with Sigma.js and a Go based REST API backend. It is deployed with a Postgresql application database and a Neo4j graph database, and is fed by the SharpHound and AzureHound data collectors.
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 identify quickly. 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 CE is created and maintained by the BloodHound Enterprise Team. The original BloodHound was created by @_wald0, @CptJesus, and @harmj0y.
The easiest way to get up and running is to use our pre-configured Docker Compose setup. The following steps will get BloodHound CE up and running with the least amount of effort.
curl -L https://ghst.ly/getbhce | docker compose -f - up
http://localhost:8080/ui/login
. Login with a username of admin
and the randomly generated password from the logsNOTE: going forward, the default docker-compose.yml
example binds only to localhost (127.0.0.1). If you want to access BloodHound outside of localhost, you'll need to follow the instructions in examples/docker-compose/README.md to configure the host binding for the container.
# Verify if Docker Engine is Running
docker info
# Attempt to stop Neo4j Service if running (on Windows)
Stop-Service "Neo4j" -ErrorAction SilentlyContinue
https://github.com/SpecterOps/BloodHound/assets/12970156/ea9dc042-1866-4ccb-9839-933140cc38b9
Please check out the Contact page in our wiki for details on how to reach out with questions and suggestions.
Toolkit demonstrating another approach of a QRLJacking attack, allowing to perform remote account takeover, through sign-in QR code phishing.
It consists of a browser extension used by the attacker to extract the sign-in QR code and a server application, which retrieves the sign-in QR codes to display them on the hosted phishing pages.
Watch the demo video:
Read more about it on my blog: https://breakdev.org/evilqr-phishing
The parameters used by Evil QR are hardcoded into extension and server source code, so it is important to change them to use custom values, before you build and deploy the toolkit.
parameter | description | default value |
---|---|---|
API_TOKEN | API token used to authenticate with REST API endpoints hosted on the server | 00000000-0000-0000-0000-000000000000 |
QRCODE_ID | QR code ID used to bind the extracted QR code with the one displayed on the phishing page | 11111111-1111-1111-1111-111111111111 |
BIND_ADDRESS | IP address with port the HTTP server will be listening on | 127.0.0.1:35000 |
API_URL | External URL pointing to the server, where the phishing page will be hosted | http://127.0.0.1:35000 |
Here are all the places in the source code, where the values should be modified:
You can load the extension in Chrome, through Load unpacked
feature: https://developer.chrome.com/docs/extensions/mv3/getstarted/development-basics/#load-unpacked
Once the extension is installed, make sure to pin its icon in Chrome's extension toolbar, so that the icon is always visible.
Make sure you have Go installed version at least 1.20.
To build go to /server
directory and run the command:
Windows:
build_run.bat
Linux:
chmod 700 build.sh
./build.sh
Built server binaries will be placed in the ./build/
directory.
./server/build/evilqr-server
https://discord.com/login
https://web.telegram.org/k/
https://whatsapp.com
https://store.steampowered.com/login/
https://accounts.binance.com/en/login
https://www.tiktok.com/login
http://127.0.0.1:35000
(default)Evil QR is made by Kuba Gretzky (@mrgretzky) and it's released under MIT license.