OpenUBA
OpenUBA: A flexible self-hosted framework for teams building custom UEBA models. Ranked #15 of 20 in User and Entity Behavior Analytics Software by our editors (7.6/10); pricing: Open source; best for teams building custom UEBA models.
At a glance
- Editor score7.6 / 10
- PricingOpen source
- Best forTeams building custom UEBA models
- Paid fromFree
- DeploymentOn-premises
- Facts checked20 Sep 2026

Where it wins
- Supports multiple ML frameworks, registries, data loaders, and execution jobs.
- Visual flow builder combines threshold and deviation-based detection logic.
- Includes model lifecycle management, risk tracking, cases, alerts, and an SDK.
Where it doesn't
- Requires self-hosted Docker or Kubernetes deployment.
- The project is currently marked beta by its maintainers.
- Entity coverage and response automation are limited.
Our verdict on OpenUBA
OpenUBA is an open-source User and Entity Behavior Analytics framework for security analytics teams building custom detection workflows. It supports user and entity analysis through model lifecycle management, anomaly detection, alerting, case investigation, and entity-risk tracking. The platform is available through web, API, and self-hosted deployments, with a Kubernetes-native design for managing, training, and executing inspectable models.
Its strongest differentiator is breadth for teams that want to assemble their own analytics stack. OpenUBA supports scikit-learn, PyTorch, TensorFlow, Keras, NetworkX, and Spark MLlib models, with registries spanning GitHub, OpenUBA Hub, Hugging Face, Kubeflow, and local filesystems. Data loaders cover local CSV files, Elasticsearch, Spark, and grouped sources. Visual flow graphs let teams compose threshold- and deviation-based rules, while isolated Docker and Kubernetes jobs separate model training and inference. Managed JupyterLab workspaces and a Python SDK add options for development and automation.
Deployment and operational maturity are the main considerations. OpenUBA requires self-hosted Docker or Kubernetes deployment, so it suits organizations prepared to manage infrastructure rather than teams seeking a hosted UEBA service. JWT authentication, role-based access control, and configurable permissions support controlled access. An optional LLM assistant can connect to Ollama, OpenAI, Claude, or Gemini. The project is marked beta, and its focus is model construction and transparent workflows rather than broad verified entity coverage or extensive response automation. Choose OpenUBA when flexibility, inspectability, and an open-source model lifecycle matter most; consider an alternative if you need a managed deployment or more developed automated response capabilities.
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OpenUBA pricing
OpenUBA fact sheet
| Free plan | Not verified |
|---|---|
| Paid from | Free |
| Deployment | On-premises |
| Entity coverage | users; entities |
| Data retention | Not verified |
| Data sources | Not verified |
| Anomaly methods | Hybrid |
| Response automation | Not verified |
| Deployment | Self-hosted |
| Platforms | Web |
| Support | Community, Docs |
| Built for | Mid-market, Enterprise (editorial estimate) |
| Integrations | 10 integrations: GitHub, OpenUBA Hub, Hugging Face, Kubeflow, Elasticsearch, Apache Spark … |
| Pricing | Open source |
| Website | github.com |
| Facts checked | 20 Sep 2026 |
OpenUBA integrations
OpenUBA lists 10 integrations on its own site.
- GitHub
- OpenUBA Hub
- Hugging Face
- Kubeflow
- Elasticsearch
- Apache Spark
- Ollama
- OpenAI
- Claude
- Gemini
Alternatives to OpenUBA
- DTEX Insider Risk ManagementBroad analytics, forensics, DLP, and workflow automation for enterprise insider-risk teams.9.4
- Varonis Insider Risk ManagementA data-focused platform for detecting, investigating, and reducing insider risk.9.3
- Gurucul UEBAA SIEM-centered UEBA platform combining machine learning, risk scoring, and automated response.9.2
See all OpenUBA alternatives →
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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