The article by Chris Haller provides a detailed overview of setting up, collecting data, analyzing, and leveraging BloodHound CE for identifying security risks in Active Directory environments. It covers the importance of understanding AD complexity, using the GOADv2 forest for sample data, and highlights tools such as SharpHound and BloodHound.py for data collection, along with insights on navigating the BloodHound CE interface and utilizing its features effectively. One trap he points out: legacy collectors produce data that CE refuses to ingest, so BloodHound.py has to come from its bloodhound-ce branch. For why CE looks so different from the old Electron app, SpecterOps’ launch post from August 2023 explains the move to containers, a Postgres and Neo4j backend, and an authenticated REST API that the GUI itself runs on.
