Kaspersky Unified Monitoring and Analysis Platform
- About Kaspersky Unified Monitoring and Analysis Platform
- Program architecture
- Installing and removing KUMA
- Program licensing
- About the End User License Agreement
- About the license
- About the License Certificate
- About the license key
- About the key file
- Adding a license key to the program web interface
- Viewing information about an added license key in the program web interface
- Removing a license key in the program web interface
- Integration with other solutions
- Integration with Kaspersky Security Center
- Configuring Kaspersky Security Center integration settings
- Adding a tenant to the list for Kaspersky Security Center integration
- Creating Kaspersky Security Center connection
- Editing Kaspersky Security Center connection
- Deleting Kaspersky Security Center connection
- Working with Kaspersky Security Center tasks
- Importing events from the Kaspersky Security Center database
- Kaspersky Endpoint Detection and Response integration
- Integration with Kaspersky CyberTrace
- Integration with Kaspersky Threat Intelligence Portal
- Integration with R-Vision Incident Response Platform
- Integration with Active Directory
- Connecting over LDAP
- Enabling and disabling LDAP integration
- Adding a tenant to the LDAP server integration list
- Creating an LDAP server connection
- Creating a copy of an LDAP server connection
- Changing an LDAP server connection
- Changing the data update frequency
- Changing the data storage period
- Starting account data update tasks
- Deleting an LDAP server connection
- Authorization with domain accounts
- Connecting over LDAP
- RuCERT integration
- Integration with Security Vision Incident Response Platform
- Kaspersky Industrial CyberSecurity for Networks integration
- Integration with Kaspersky Security Center
- KUMA resources
- KUMA services
- Analytics
- Working with tenants
- Working with incidents
- About the incidents table
- Saving and selecting incident filter configuration
- Deleting incident filter configurations
- Viewing information about an incident
- Incident creation
- Incident processing
- Changing incidents
- Automatic linking of alerts to incidents
- Categories and types of incidents
- Exporting incidents to RuCERT
- Sending incidents involving personal information leaks to RuCERT
- Working in hierarchy mode
- Working with alerts
- Working with events
- Retroscan
- Working with geographic data
- Transferring events from isolated network segments to KUMA
- Managing assets
- Asset categories
- Adding an asset category
- Configuring the table of assets
- Searching assets
- Viewing asset details
- Adding assets
- Assigning a category to an asset
- Editing the parameters of assets
- Deleting assets
- Updating third-party applications and fixing vulnerabilities on Kaspersky Security Center assets
- Moving assets to a selected administration group
- Asset audit
- Managing users
- Managing KUMA
- Contacting Technical Support
- REST API
- Creating a token
- Configuring permissions to access the API
- Authorizing API requests
- Standard error
- Operations
- Viewing a list of active lists on the correlator
- Import entries to an active list
- Searching alerts
- Closing alerts
- Searching assets
- Importing assets
- Deleting assets
- Searching events
- Viewing information about the cluster
- Resource search
- Loading resource file
- Viewing the contents of a resource file
- Importing resources
- Exporting resources
- Downloading the resource file
- Search for services
- Tenant search
- View token bearer information
- Dictionary updating in services
- Dictionary retrieval
- Appendices
- Commands for components manual starting and installing
- Integrity check of KUMA files
- Normalized event data model
- Alert data model
- Asset data model
- User account data model
- Audit event fields
- Event fields with general information
- User was successfully signed in or failed to sign in
- User login successfully changed
- User role was successfully changed
- Other data of the user was successfully changed
- User successfully logged out
- User password was successfully changed
- User was successfully created
- User access token was successfully changed
- Service was successfully created
- Service was successfully deleted
- Service was successfully reloaded
- Service was successfully restarted
- Service was successfully started
- Service was successfully paired
- Service status was changed
- Storage partition was deleted by user
- Storage partition was deleted automatically due to expiration
- Active list was successfully cleared or operation failed
- Active list item was successfully deleted or operation was unsuccessful
- Active list was successfully imported or operation failed
- Active list was exported successfully
- Resource was successfully added
- Resource was successfully deleted
- Resource was successfully updated
- Asset was successfully created
- Asset was successfully deleted
- Asset category was successfully added
- Asset category was deleted successfully
- Settings were updated successfully
- Information about third-party code
- Trademark notices
- Glossary
Normalizer settings
The normalizer window contains two tabs: Normalization scheme and Enrichment.
Normalization scheme
This tab is used to specify the main settings of the normalizer and to define the rules for converting events into KUMA format.
Available settings:
- Name (required)—the name of the normalizer. Must contain from 1 to 128 Unicode characters. The name of the main normalizer will be used as the name of the normalizer resource.
- Tenant (required)—name of the tenant that owns the resource.
This setting is not available for extra normalizers.
- Parsing method (required)—drop-down list for selecting the type of incoming events. Depending on your choice, you can use the preconfigured rules for matching event fields or set your own rules. When you select some parsing methods, additional parameter fields required for filling in may become available.
Available parsing methods:
- json
This parsing method is used to process JSON data.
When processing files with hierarchically arranged data, you can access the fields of nested objects by specifying the names of the parameters dividing them by a period. For example, the
username
parameter from the string"user": {"username": "system: node: example-01"}
can be accessed by using theuser.username
query. - cef
This parsing method is used to process CEF data.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
- regexp
This parsing method is used to create custom rules for processing JSON data.
In the Normalization parameter block field, add a regular expression (RE2 syntax) with named capture groups. The name of a group and its value will be interpreted as the field and the value of the raw event, which can be converted into an event field in KUMA format.
To add event handling rules:
- Copy an example of the data you want to process to the Event examples field. This is an optional but recommended step.
- In the Normalization parameter block field add a regular expression with named capture groups in RE2 syntax, for example "(?P<name>regexp)".
You can add multiple regular expressions by using the Add regular expression button. If you need to remove the regular expression, use the
button.
- Click the Copy field names to the mapping table button.
Capture group names are displayed in the KUMA field column of the Mapping table. Now you can select the corresponding KUMA field in the column next to each capture group. Otherwise, if you named the capture groups in accordance with the CEF format, you can use the automatic CEF mapping by selecting the Use CEF syntax for normalization check box.
Event handling rules were added.
- syslog
This parsing method is used to process data in syslog format.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
- csv
This parsing method is used to create custom rules for processing CSV data.
When choosing this method, you must specify the separator of values in the string in the Delimiter field. Any single-byte ASCII character can be used as a delimiter.
- kv
This parsing method is used to process data in key-value pair format.
If you select this method, you must provide values in the following required fields:
- Pair delimiter—specify a character that will serve as a delimiter for key-value pairs. You can specify any one-character (1 byte) value, provided that the character does not match the value delimiter.
- Value delimiter—specify a character that will serve as a delimiter between the key and the value. You can specify any one-character (1 byte) value, provided that the character does not match the delimiter of key-value pairs.
- xml
This parsing method is used to process XML data.
When this method is selected in the parameter block XML Attributes you can specify the key attributes to be extracted from tags. If an XML structure has several attributes with different values in the same tag, you can indicate the necessary value by specifying its key in the Source column of the Mapping table.
To add key XML attributes,
Click the Add field button, and in the window that appears, specify the path to the required attribute.
You can add more than one attribute. Attributes can be removed one at a time using the cross icon or all at once using the Reset button.
If XML key attributes are not specified, then in the course of field mapping the unique path to the XML value will be represented by a sequence of tags.
- netflow5
This parsing method is used to process data in the NetFlow v5 format.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
In mapping rules, the protocol type for netflow5 is not indicated in the fields of KUMA events by default. When parsing data in NetFlow format on the Enrichment normalizer tab, you should create a constant data enrichment rule that adds the
netflow
value to theDeviceProduct
target field. - netflow9
This parsing method is used to process data in the NetFlow v9 format.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
In mapping rules, the protocol type for netflow9 is not indicated in the fields of KUMA events by default. When parsing data in NetFlow format on the Enrichment normalizer tab, you should create a constant data enrichment rule that adds the
netflow
value to theDeviceProduct
target field. - sflow5
This parsing method is used to process data in sFlow5 format.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
- ipfix
This parsing method is used to process IPFIX data.
When choosing this method, you can use the preconfigured rules for converting events to the KUMA format by clicking the Apply default mapping button.
In mapping rules, the protocol type for ipfix is not indicated in the fields of KUMA events by default. When parsing data in NetFlow format on the Enrichment normalizer tab, you should create a constant data enrichment rule that adds the
netflow
value to theDeviceProduct
target field. - sql
This parsing method is used to process SQL data.
- json
- Keep raw log (required)—in this drop-down list, you can indicate whether you need to store the original raw event in the newly created normalized event. Available values:
- Never—do not save the raw event This is the default setting.
- Only errors—save the raw event in the
Raw
field of the normalized event if errors occurred when parsing it. This value is convenient to use when debugging a service. In this case, every time an event has a non-emptyRaw
field, you know there was a problem.If fields containing the names
*Address
or*Date*
do not comply with normalization rules, these fields are ignored. No normalization error will occur, and the values of the fields will not show up in theRaw
field of the normalized event even if Keep raw log → Only errors was indicated. - Always—always save the raw event in the
Raw
field of the normalized event.
This setting is not available for extra normalizers.
- Save extra fields (required)—in this drop-down list, you can choose whether you want to save fields and their values if no mapping rules have been configured for them (see below). This data is saved as an array in the Extra event field. Normalized events can be searched and filtered based on the data stored in the Extra field.
Filtering based on data from the Extra event field
Conditions for filters based on data from the Extra event field:
- Condition—If.
- Left operand—event field.
- In this event field, you can specify one of the following values:
- Extra field.
- Value from the Extra field in the following format:
Extra.<field name>
For example,
Extra.app
.A value of this type is specified manually.
- Value from the array written to the Extra field in the following format:
Extra.<field name>.<array element>
For example,
Extra.array.0
.The values in the array are numbered starting from 0.
A value of this type is specified manually.
- Operator – =.
- Right operand—constant.
- Value—the value by which you need to filter events.
By default, no extra fields are saved.
- Description—up to 256 Unicode characters describing the resource.
This setting is not available for extra normalizers.
- Event examples—in this field, you can provide an example of data that you want to process. Event examples can also be loaded from a TSV, CSV, or TXT file by using the Load from file button.
This setting is not available for the sFlow5 parsing method.
- Mapping settings block—here you can configure mapping of original event fields to fields of the event in KUMA format:
- Source—column for the names of the raw event fields that you want to convert into KUMA event fields.
Clicking the
button next to the field names in the Source column opens the Conversion window, in which you can use the Add conversion button to create rules for modifying the original data before they are written to the KUMA event fields.
Conversions are changes that can be applied to a value before it gets written to the event field. The conversion type is selected from a drop-down list.
Available conversions:
- lower—is used to make all characters of the value lowercase
- upper—is used to make all characters of the value uppercase
- regexp – used to convert a value using the regular expression RE2. When this conversion type is selected, the field appears where regular expression should be added.
- substring—is used to extract characters in the position range specified in the Start and End fields. These fields appear when this conversion type is selected.
- replace—is used to replace specified character sequence with the other character sequence. When this type of conversion is selected, new fields appear:
- Replace chars—in this field you can specify the character sequence that should be replaced.
- With chars—in this field you can specify the characters sequence should be used instead of replaced characters.
- trim—used to simultaneously remove the characters specified in the Chars field from the leading and end positions of the value. The field appears when this type of conversion is selected. For example, a trim conversion with the
Micromon
value applied toMicrosoft-Windows-Sysmon
results insoft-Windows-Sys
. - append is used to add the characters specified in the Constant field to the end of the event field value. The field appears when this type of conversion is selected.
- prepend—used to prepend the characters specified in the Constant field to the start of the event field value. The field appears when this type of conversion is selected.
- replace with regexp—is used to replace RE2 regular expression results with the character sequence.
- Expression—in this field you can specify the regular expression which results that should be replaced.
- With chars—in this field you can specify the characters sequence should be used instead of replaced characters.
- KUMA field—drop-down list for selecting the required fields of KUMA events. You can search for fields by entering their names in the field.
- Label—in this column, you can add a unique custom label to event fields that begin with DeviceCustom*.
New table rows can be added by using the Add row button. Rows can be deleted individually using the
button or all at once using the Clear all button.
If you have loaded data into the Event examples field, the table will have an Examples column containing examples of values carried over from the raw event field to the KUMA event field.
- Source—column for the names of the raw event fields that you want to convert into KUMA event fields.
Enrichment
This tab is used to add additional data to fields of a normalized event by using enrichment rules similar to the rules in enrichment rule resources. These enrichment rules are stored in the normalizer resource where they were created. There can be more than one enrichment rule. Enrichments are created by using the Add enrichment button.
Settings available in the enrichment rule settings block:
- Source kind (required)—drop-down list for selecting the type of enrichment. Depending on the selected type, you may see advanced settings that will also need to be completed.
Available Enrichment rule source types:
- constant
This type of enrichment is used when a constant needs to be added to an event field. Settings of this type of enrichment:
- In the Constant field, specify the value that should be added to the event field. The value should not be longer than 255 Unicode characters. If you leave this field blank, the existing event field value will be cleared.
- In the Target field drop-down list, select the KUMA event field to which you want to write the data.
- dictionary
This type of enrichment is used if you need to add a value from the dictionary to the event field.
When this type is selected in the Dictionary name drop-down list, you must select the dictionary that will provide the values. In the Key fields settings block, you must use the Add field button to select the event fields whose values will be used for dictionary entry selection.
- event
This type of enrichment is used when you need to write a value from another event field to the current event field. Settings of this type of enrichment:
- In the Target field drop-down list, select the KUMA event field to which you want to write the data.
- In the Source field drop-down list, select the event field whose value will be written to the target field.
- Clicking the
button opens the Conversion window in which you can, using the Add conversion button, create rules for modifying the original data before writing them to the KUMA event fields.
Conversions are changes that can be applied to a value before it gets written to the event field. The conversion type is selected from a drop-down list.
Available conversions:
- lower—is used to make all characters of the value lowercase
- upper—is used to make all characters of the value uppercase
- regexp – used to convert a value using the regular expression RE2. When this conversion type is selected, the field appears where regular expression should be added.
- substring—is used to extract characters in the position range specified in the Start and End fields. These fields appear when this conversion type is selected.
- replace—is used to replace specified character sequence with the other character sequence. When this type of conversion is selected, new fields appear:
- Replace chars—in this field you can specify the character sequence that should be replaced.
- With chars—in this field you can specify the characters sequence should be used instead of replaced characters.
- trim—used to simultaneously remove the characters specified in the Chars field from the leading and end positions of the value. The field appears when this type of conversion is selected. For example, a trim conversion with the
Micromon
value applied toMicrosoft-Windows-Sysmon
results insoft-Windows-Sys
. - append is used to add the characters specified in the Constant field to the end of the event field value. The field appears when this type of conversion is selected.
- prepend—used to prepend the characters specified in the Constant field to the start of the event field value. The field appears when this type of conversion is selected.
- replace with regexp—is used to replace RE2 regular expression results with the character sequence.
- Expression—in this field you can specify the regular expression which results that should be replaced.
- With chars—in this field you can specify the characters sequence should be used instead of replaced characters.
- template
This type of enrichment is used when you need to write a value obtained by processing Go templates into the event field. Settings of this type of enrichment:
- Put the Go template into the Template field.
Event field names are passed in the
{{.EventField}}
format, whereEventField
is the name of the event field from which the value must be passed to the script.Example:
Attack on {{.DestinationAddress}} from {{.SourceAddress}}
. - In the Target field drop-down list, select the KUMA event field to which you want to write the data.
- Put the Go template into the Template field.
- constant
- Target field (required)—drop-down list for selecting the KUMA event field that should receive the data.