NetWitness Platform vs OpenUBA

NetWitness Platform is a threat detection, investigation, and response platform for complex IT and OT environments. Its modules include network detection and response, endpoint detection and response, SIEM, SOAR, and UEBA, with additional OT security coverage described. NDR uses full packet capture and metadata analysis to monitor infrastructure and reconstruct sessions. Machine learning and behavioral analytics are described for identifying known and unknown threats and anomalous behavior, with real-time alerting. SIEM ingests logs from over 350 sources, including AWS, Azure, Office 365, and Salesforce, through Syslog, ODBC, SFTP, FTPS, and SNMP. It provides reporting templates and use cases for SOX, PCI, HIPAA, and NERC. SIEM can run on-premises, virtually, or in the cloud, including AWS and Azure. The EDR agent is described for hundreds to 100,000 endpoints with near-zero end-user impact. NetWitness is paid, supports Linux, self-hosted, and web deployments, and lists pricing on request.

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.