This page describes how to update policies using the Policy Handler API.
The create policy handler endpoint must be a policy handler object.
The update policy handler endpoint must be a policy handler object.
dataSourceId
(integer): ID of the data source the policy will be applied to.
Example: 1
jsonRules
(array[object]): Array of JSON rules objects.
Example: See defining policy rules
The jsonRules
array contains rules objects. The following types of policy rules are supported:
Not all combination of policy rules are valid. The examples below are supported policy rule combinations:
Prerequisite, Visibility, Masking
Prerequisite, Masking, Minimization
Prerequisite policies are used to limit usage to one or more purposes.
type
(string): Policy rule type. Must be prerequisite
for prerequisite policy rules.
Example: "prerequisite"
operator
(string): Operator to be applied on conditions. Possible values: and, or.
Example: "or"
conditions
(array[object]): Conditions to be applied for the rule. Multiple values will be evaluated according to the operator.
Example: See purpose condition object
Example:
In this example, users will only have access to data from this data source when they are acting under the purpose
named Purpose Name
.
Visibility policies are used to enforce row-level security.
type
(string): Policy rule type. Must be visibility
for row-level security policy rules.
Example: "visibility"
operator
(string): Operator to be applied on conditions. Possible values: and, or.
Example: "or"
conditions
(array[object]): Conditions to be applied for the rule. Multiple values will be evaluated according to the operator.
Example: See policy conditions
Note: When adding conditions to a visibility policy rule, the field
is required, and the condition value
should be left empty. For example, for a group policy condition, the group name is not specified.
The user must possess the group, attribute, or purpose that matches the value stored in the field
.
Example:
In this example, users will only see rows when they have an authorization
that matches the value in the field department
and they belong to a group
that matches the value in the field organization
.
Masking policy rules will mask the value in one or more columns.
type
(string): Policy rule type. Must be masking
for masking policy rules.
Example: "masking"
fields
(array[string]): Fields that will be masked when a user does not fulfill policy conditions.
Example: ["email", "location"]
operator
(string): Operator to be applied on conditions. Possible values: and, or.
Example: "or"
conditions
(array[object]): Conditions to be applied for the rule. Multiple values will be evaluated according to the operator.
Example: See policy conditions
Note: When adding conditions to a masking policy rule, the field
will be left blank, and the condition value
should be populated.
When using a masking rule, there is an additional field that needs to be sent in the update data source request in the policyHandler.maskingConfiguration
array field.
name
(string): Name of the field being masked.
Example: "social"
type
(string): Type of masking to apply. Supported values are "Consistent Value"
, "Grouping"
, "Regular Expression"
Example: "Consistent Value"
metadata
(object): Extra metadata used when masking the value.
Example: See masking configuration metadata
Consistent value
constant
(string|null): Constant value to mask to. If this field is not defined, the value will be hashed.
Example: "REDACTED"
Regular expression
regex
(string): Regex to match against when masking columns.
Example: "[0-9]{3}-[0-9]{2}"
replacement
(string): String used to replace the matched regex.
Example: "xxx-xx"
Grouping
bucketSize
(integer): For number fields. Size of buckets to round numbers to.
Example: 100
timePrecision
(string): For time fields. Time precision to round to. Possible values: "MIN"
, "HOUR"
, "DAY"
, "WEEK"
, "MONTH"
, "YEAR"
Example: "HOUR"
Example policy handler update with masking configuration metadata:
Example:
In this example, the fields email
and location
will be masked unless the user belongs to the group admins
.
Minimization policy rules will show a limited percentage of the data, based on a high cardinality column, for everyone unless the user fulfills the policy conditions.
type
(string): Policy rule type. Must be additional
for minimization policy rules.
Example: "additional"
name
(string): Name of additional policy. Must be minimization
for minimization policy rules.
Example: "minimization"
operator
(string): Operator to be applied on conditions. Possible values: and, or.
Example: "or"
conditions
(array[object]): Conditions to be applied for the rule. Multiple values will be evaluated according to the operator.
Example: See policy conditions
Note: When adding conditions to a minimization policy rule the field
will be left blank.
When using a minimization rule, there is an additional field that needs to be sent in the update data source request in the policyHandler.additionalFilters.minimization
field.
percent
(integer): Percentage of the data to show to the users. This percentage will be based off of unique values in the hashPhrase
column.
Example: 50
hashPhrase
(string): Column to base the percentage off of. This should be a high cardinality column in the data source.
Example: "name"
Example policy handler rule:
In this example, 50 percent of the data, based on the name
field, will be visible to users unless they fulfill the policy conditions.
Example data source update (partial):
Time-based rules will make a limited portion of the data available based on event time. The data source must contain an event time column in order for this policy type to be valid. For instance, users who do not fulfill the policy conditions will only see data from within the defined time window.
type
(string): Policy rule type. Must be additional
for minimization policy rules.
Example: "additional"
name
(string): Name of additional policy. Must be time
for time based policy rules.
Example: "time"
operator
(string): Operator to be applied on conditions. Possible values: and, or.
Example: "or"
conditions
(array[object]): Conditions to be applied for the rule. Multiple values will be evaluated according to the operator.
Example: See policy conditions
Note: When adding conditions to a time based policy rule the field
will be left blank.
When using a time based rule, there is an additional field that needs to be sent in the update data source request in the policyHandler.additionalFilters
field.
time
(integer): Age in seconds of the oldest data a user will be allowed to see. This counts backward from the present.
Example: 14400
Example policy handler rule:
In this example, only data from the last 4 hours will be visible to users unless they fulfill the policy conditions.
Example data source update (partial):