Netskope One Behavior Analytics vs OpenUBA
Netskope One Behavior Analytics
netskope.comOpenUBA
github.comSide by side
| Figure | Netskope One Behavior Analytics | OpenUBA |
|---|---|---|
| Price from | — | — |
| Free plan | — | — |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| iOS | Yes | — |
| Android | Yes | — |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 3 | 0 |
| Spec score · User and Entity Behavior Analytics Software | 7.4 (#9) | 7.4 (#10) |
| Intended users | Netskope positions Behavior Analytics for organizations seeking UEBA insights to detect insider risk and compromised accounts. | OpenUBA is designed for security analysts interested in understanding how detection models work under the hood. |
| Support | Netskope says its global technical support team operates 24/7/365 and provides support through its customer and partner Support Portal. | 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
Netskope One Behavior Analytics
- Advanced UEBAPriced on request
- SOC Detection PackPriced on request
- Standard UEBAPriced on request
In their own words
Netskope One Behavior Analytics
Netskope One Behavior Analytics has no write-up on Specifiction yet; its figures are above.
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.