A BloodHoundAD report engine that transforms Neo4J graph queries into actionable security reports for blue and purple teams.
PlumHound is a Python-based reporting engine that leverages BloodHoundAD's Neo4J graph database to generate actionable security reports for Active Directory environments. It solves the problem of BloodHound's graphical output being overwhelming for blue and purple teams by transforming complex cypher queries into structured, consumable reports that highlight vulnerabilities and misconfigurations.
Security professionals, blue teams, and purple teams responsible for hardening Active Directory infrastructures and identifying attack paths in enterprise environments.
Developers choose PlumHound because it bridges the gap between BloodHoundAD's red-team-focused pathfinding and the need for defensive, actionable insights, offering automation, customizable reporting, and community-shared query sets.
Bloodhound Reporting for Blue and Purple Teams
PlumHound executes predefined TaskLists to run multiple cypher queries automatically, generating comprehensive HTML or CSV reports that save time for security teams, as shown in the default.tasks example with over 70 pre-built queries.
Integrates BlueHound modules to analyze attack paths and identify specific relationships to break, providing clear remediation steps for hardening Active Directory, detailed in the AnalyzePath mode with output showing which relationships to remove.
Supports HTML templates with dynamic variables, CSS, and headers/footers, allowing teams to brand reports and include runtime data like dates, as specified in the HTML output options with default templates in the repo.
Leverages a shared repository (PlumHound-Tasks) for TaskLists, enabling teams to contribute and reuse query sets, fostering collaboration and efficiency beyond the included default tasks.
Requires a fully configured Neo4J database with BloodHoundAD data imported, adding significant setup overhead and maintenance compared to standalone tools, as noted in the installation requirements.
Designed for scheduled or manual report generation, not for real-time analysis or continuous monitoring, limiting its use in dynamic threat environments where immediate insights are needed.
Effective use demands knowledge of Neo4J cypher queries and BloodHound's data model, which can be a barrier for teams without prior experience, as custom tasks require writing or modifying complex queries.
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