- Welcome to Exabeam Security Content
- What is Security Content?
- Common Information Model
- What is the Common Information Model?
- Common Information Model Context Elements
- Common Information Model Interface
- Common Information Model Event-naming Format
- Common Information Model Impact on Downstream Processes
- Using the Common Information Model to Create Custom Content
- Transitioning to the Common Information Model
- Understanding the Log
- Exabeam Parsers
- Exabeam Event Building
- Exabeam Enrichment
- Exabeam Persistence and Templates
- Exabeam Models
- Exabeam Rules
Categorical Models
Categorical models are used to train on data represented by string values, such as host or user names. These models can be based either on user behavior or on asset activity. In the sections below, each example models specific endpoint process activity, but one is a user-based model while the other is an asset-based model.
User-based Model
This example models the process-create and process-alert endpoint activity of a specific user. The user-based nature of the model is clear from the value for the Scope
attribute. For more information about the model attributes, see the table below the example.
EPA-HP { ModelTemplate = "Processes for the user" Description = "Models processes for this user" Category = "End Point Activity" IconName = "" ScopeType = "USER" Scope = """user""" Feature = """process_name""" FeatureName = "process" FeatureType = "process_name" TrainIf = """sequenceCount(process_name,'process-created','process-alert')=1""" ModelType = "CATEGORICAL" AgingWindow = "32" CutOff = "10" Alpha = "2" MaxNumberOfBins = "10000000" ConvergenceFilter = "confidence_factor>=0.8" HistogramEventTypes = [ "process-created", "process-alert" ] Disabled = "FALSE" }
Model Attribute | Description |
---|---|
Category | Helps define the scope of a model. Process-related activity is categorized as endpoint activity, so the For a list of other Exabeam |
Scope | Specifies the field for which the model is collecting data. The |
Feature | The data object for which values are being collected. The |
TrainIf | An expression that tells the model what data to train on. For user-based models, this attribute often contains one of the following types of expressions:
In this example, the following expression ensures that the model trains on all
|
ModelType | This model trains on non-numerical data, so the |
HistogramEventTypes | A histogram for this model displays the |
For definitions and examples of other Exabeam model attributes, see Model Attributes.
Asset-based Model
This example models the process-create and process-alert endpoint activity of a specific asset. The A–
at the start of the model name indicates that it's an asset-based model. The asset-based nature of the model is also clear from the value for the SequenceTypes
attribute. For more information about the model attributes, see the table below the example.
A-EPA-HP { ModelTemplate = "Processes on this asset" Description = "Models processes on this asset" Category = "End Point Activity" IconName = "" ScopeType = "DEVICE" Scope = """dest_host""" Feature = """process_name""" FeatureName = "process" FeatureType = "process_name" TrainIf = """CountBy(process_name,dest_host,'process-created','process-alert','process-network')=1""" ModelType = "CATEGORICAL" AgingWindow = "" CutOff = "10" Alpha = "3" MaxNumberOfBins = "5000000" ConvergenceFilter = "confidence_factor>=0.8" HistogramEventTypes = [ "process-created", "process-alert", "process-network" ] SequenceTypes = [asset] Disabled = "FALSE" }
Model Attribute | Description |
---|---|
Category | Helps define the scope of a model. Process-related activity is categorized as endpoint activity, so the For a list of other Exabeam |
Scope | Specifies the field for which the model is collecting data. The |
Feature | The data object for which values are being collected. The |
TrainIf | An expression that tells the model what data to train on. For asset-based models, this attribute often contains one of the following types of expressions:
In this example, the following expression ensures that the model trains on all
|
ModelType | This model trains on non-numerical data, so the |
HistogramEventTypes | A histogram for this model displays the |
SequenceTypes | This example is an asset-based model, so the value is |
For definitions and examples of other Exabeam model attributes, see Model Attributes.