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SPECIFICTION
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Microsoft Defender for Business vs OpenUBA

Microsoft Defender for Business

microsoft.com

OpenUBA

github.com

Side by side

FigureMicrosoft Defender for BusinessOpenUBA
Price from$0.25/mo—
Free plan——
Free trialYes—
Open source——
Web—Yes
WindowsYes—
macOSYes—
Linux—Yes
iOSYes—
AndroidYes—
APIYesYes
Self-hosted—Yes
Plans published40
Spec score · User and Entity Behavior Analytics Software8.7 (#1)7.4 (#10)
SupportMicrosoft's Defender for Business documentation provides a guide for getting help or contacting support.The security policy asks vulnerability reporters to email [email protected] and states an acknowledgment target of 48 hours and an initial assessment target of 7 days.

Plans

Microsoft Defender for Business

  • Microsoft Defender for Business$3 a month
  • Microsoft Entra Internet Access$5 a month
  • Microsoft Entra Suite$12 a month
  • Microsoft Defender for Business$3 a year

Microsoft Defender for Business pricing →

OpenUBA

No plans published.

OpenUBA pricing →

In their own words

Microsoft Defender for Business

Microsoft Defender for Business has no write-up on Specifiction yet; its figures are above.

Visit microsoft.com

OpenUBA

OpenUBA is a free, open-source framework for user and entity behavior analytics in security analytics. Users can install, train, and run models, track versions and artifacts, and use feedback and shadow modes. Listed model frameworks include scikit-learn, PyTorch, TensorFlow, Keras, NetworkX, and Spark MLlib. A visual flow-based rule builder combines model outputs with logical conditions; alerts can link to anomalies and cases. Data loaders cover local CSV, Elasticsearch, Spark, and aggregated multi-source loading. The project describes a Kubernetes-native architecture, with containerized components for development Kind clusters or production Kubernetes clusters. It provides REST endpoints, a GraphQL API, and a Python SDK for model registration, job submission, and visualization. Access controls listed in the README include JWT authentication, four roles, per-page read and write permissions, and audit logging. Model training and inference use isolated Docker containers or ephemeral Kubernetes Jobs with resource limits. The built-in assistant supports local Ollama and cloud APIs from OpenAI, Claude, and Gemini. The project identifies itself as beta, and its listed release is v0.0.2 as a pre-release.

Visit github.com