Attribute Sync and Transformers

Configure how user attributes from a source of identity are transformed and synchronized for target user accounts

When creating workflows in Lifecycle Management policies to create, sync, or de-provision identities, you will use attribute transformers to specify how user attributes for target accounts should be structured. The target attributes to create or update are typically mapped and optionally transformed from user metadata from the source of identity, such as an identity provider, HR system, or CSV upload. Attributes can be synchronized once or kept in continuous sync as changes occur over the user’s lifetime.

For example, attribute mapping and transformation can be used across Joiner, Mover, and Leaver scenarios:

• Joiner: Set new Azure AD User Principal Name to {source username}@{your-email-domain.com}. This is an example of mapping multiple attributes and performing a transformation.

• Mover: Always update a user’s “Manager” and “Department” attributes in Okta to match the user’s manager and department in Workday, a source of identity, whenever a department change or other employee mobility event occurs. This is an example of attribute mapping with continuous synchronization.

• Leaver: Mote a user’s Active Directory account to an OU reserved for terminated accounts.

When synchronizing a user’s attributes, Veza can apply one (or more) transformations to convert the source attribute values to a more suitable format, and apply the result within the target application as user account attribute.

For example, a transformer might remove the domain from an email address, replace special characters, or convert a string from upper case to lower case. Transformers can apply to any attribute on the target user account with the complexity varying depending on your business requirements.

See the following sections for more information about formatting destination attributes and possible transformations:

Continuous Sync

Continuous Sync keeps identity attributes in target systems up to date with your source of truth. It has three configuration levels that work together to determine how attributes are synchronized:

Workflow Level

The workflow's continuous sync setting controls change detection:

• When enabled: The workflow monitors for any changes in the source system

• When disabled: The workflow only runs during initial provisioning

Action Level

For Sync Identity actions, this controls whether existing entities can be updated:

• When enabled: The action can update existing entities

• When disabled: The action only sets attributes during initial creation

Attribute Level

Individual attributes can be configured for continuous sync:

• When enabled: The attribute will be updated when changes are detected

• When disabled: The attribute is only set during initial creation

All three levels must be enabled for an attribute to be continuously synchronized. For example, if you want to keep an employee's department updated:

1. Enable continuous sync on the workflow to monitor for changes

2. Enable continuous sync on the sync action to allow updates

3. Enable continuous sync on the department attribute transformer

Recommended Settings

Enable continuous sync for attributes that change during employment:

• Employee name

• Department

• Title

• Manager

• Cost Center

• AD Distinguished Name (DN)

• AD User Principal Name (UPN)

• AD Email

Disable continuous sync for stable identifiers:

• Active Directory sAMAccountName

• Email Addresses (for Email Write-Back action)

This configuration ensures that dynamic attributes stay updated while preserving stable identifiers.

Common Transformers

As part of implementing lifecycle management processes with Veza, you should create sets of common transformers to define how values such as username, login, or ID should be sourced for each target application. These transformers can then be reused across all identity sync and de-provision workflows involving those targets. Create common transformers to consistently form attributes for specific entity types, and re-use them to avoid errors and save time when creating actions for that entity type.

For instance, defining a common synced attribute to describe how to format Azure AD account names {username}@evergreentrucks.com enables reuse across multiple workflow actions. You can also define synced attributes at the action level when they are used only once within a policy, such as setting the primary group DN and OU of de-provisioned identities to a group reserved for terminated accounts.

Common Transformer Examples:

Transformer & Entity Type	Attribute	Value Format	Continuous Sync	Description
ADAccountTransformer ActiveDirectoryUser	account_name	{display_full_name}	No	Basic account name
	distinguished_name	CN={first_name} {last_name},OU={department},OU={location},DC=company,DC=local	Yes	Full AD path
	user_principal_name	{username}@company.com	Yes	UPN format
	email	{username}@company.com	Yes	Email address
OktaAccountTransformer OktaUser	login	{username}@company.com	No	Primary login
	email	{username}@company.com	Yes	Email address
	username_prefix	{first_name | SUB_STRING,0,1 | LOWER}{last_name | LOWER}	No	Username creation
AzureADTransformer AzureADUser	principal_name	{username}@company.com	No	Primary identifier
	mail_nickname	{first_name | SUB_STRING,0,1 | LOWER}{last_name | LOWER}	No	Email alias
	display_name	{first_name} {last_name}	Yes	Display name
GoogleAccountTransformer GoogleWorkspaceUser	email	{username}@company.com	No	Primary email
	email_addresses	{username}@company.com	No	Email list
	recovery_email	{personal_email}	Yes	Backup email
ContractorTransformer ActiveDirectoryUser	account_name	c-{username}	No	Contractor prefix
	distinguished_name	CN={first_name} {last_name},OU=Contractors,OU={department},DC=company,DC=local	Yes	Contractor OU
	description	Contractor - {vendor_company} - Start Date: {start_date}	Yes	Metadata
RegionalEmailTransformer ExchangeUser	email_address	{username}@{region}.company.com	No	Regional email
	alias	{first_name}.{last_name}@{region}.company.com	Yes	Regional alias

Adding transformers

Transformers can be defined at the policy level or when configuring an individual action in a workflow. To configure a transformer, add basic details as well as how to source the value of each attribute:

1. Give the transformer a name and description, and specify the data source it applies to.

2. Entity Type: Choose the target entity type in the destination system.

3. Click Add Attribute. The Destination Attribute dropdown will list available attributes for the chosen entity type.

   1. Destination Attribute: Choose the attribute that Veza will create or update for the target entity.

   2. Formatter: Choose how the destination attribute should be formatted. Specify the value, a {source_attribute}, or apply Transformation Functions.

   3. Pipeline Functions: Combine attribute formatters with the | character to apply more complex transformations, such as combining the first letter of a first_name and the first four characters of a last_name to generate a local username. See Pipeline Functions for more examples

   4. Continuous Sync: Enabling this option always syncs the attribute, whilst applying any defined transformations. By default, attributes will not sync if the target identity is already created.

After creating a common transformer, you can select it when editing a workflow action. You can edit or delete common transformers on the Edit Policy > Common Transformers tab.

Remember that “Sync Identity” and “De-Provision Identity” actions can have action-level transformers override common transformers. If the same destination attribute is defined in both, the action-level transformer will take precedence.

Formatters

Formatters specify the actual value of the attribute to synchronize. The target attribute can be set to a specific value, synchronized with a source attribute, transformed according to a function, or some combination of the three.

Note that some formatters should enable continuous synchronization for the attribute, while others should not. For example, the value of “Created By” should be immutable once a user account is provisioned. Other attributes that represent a state or status should be synchronized over the user or account lifecycle.

Simple Value Setting

To create a destination attribute with a fixed value, enter the desired value when configuring the formatter.

For setting the creator attribute:

Destination Attribute	Formatter	Continuous Sync
created_by	"Veza"	Disabled

For activating a re-hired employee:

Destination Attribute	Formatter	Continuous Sync
active	true	Enabled

Empty Values

To set empty values (common for de-provisioning flows):

Destination Attribute	Formatter	Continuous Sync
manager_id	" "	Enabled
active	false	Enabled

Source of Identity Formatters

Target attributes can be updated based on attributes belonging to the source of identity. To reference the value of a source entity attribute, use the format {<source_attribute_name>}.

Examples:

Destination Attribute	Formatter	Continuous Sync
first_name	{first_name}	Enabled
last_name	{last_name}	Enabled
email	{first_name}.{last_name}@domain.com	-

Transformation functions

Based on the user metadata that is available from your source of identity, you may need to convert a full email address to a valid username, standardize a date, or generate a unique identifier for users provisioned by Veza. If an attribute value needs to be altered for compatibility with the target system, you can transform the value of a source attribute, or apply a range of other functions to generate the target value.

Formatter expressions use the following syntax: {<source_attribute_name> | <FUNCTION_NAME>,<param1>,<param2>}

For example:

Destination Attribute	Formatter	Description
username	{email | REMOVE_DOMAIN}	Removes domain from email to create username
user_id	{id | UPPER}	Converts ID to uppercase

Table of transformation functions

See the table below for all supported functions and parameters. Some commonly used transformation functions include:

• Replacing a character with a different one

• Removing domains from email addresses

• Transforming to upper, lower, camel, or snake case

• Using a substring from the original value

Please contact Veza if additional transformations are required for your use case.

Function	Description	Parameters	Requires Input	Returns Multiple	Example
ASCII	Removes non-printable characters and replaces non-ASCII characters with their closest ASCII equivalents.	None	Yes	No	ASCII("Łukasz Gruba") results in Lukasz Gruba
COUNTRY_CODE_ISO3166	Transforms country code to ISO 3166 format.	Format (STRING, optional): [alpha2, alpha3, numeric], defaults to alpha2	Yes	No	COUNTRY_CODE_ISO3166("US", alpha3) results in USA
DATE_FORMAT	Transforms dates to a different format using Go time layout syntax.	Output Layout (STRING, required): Go time layout for output format. Input Layout (STRING, optional): Go time layout for input format	Yes	No	{start_date | DATE_FORMAT, "01/02/2006"} formats date as MM/DD/YYYY
FIRST_N	Picks the first N characters of a string.	Length (NUMBER, required): Number of characters to return	Yes	No	FIRST_N("first_name", 4) results in firs
FROM_ENTITY_ATTRIBUTE	Transforms a string from an attribute of another entity in the graph.	EntityType (STRING, required), SourceAttribute (STRING, required), TargetAttribute (STRING, required)	Yes	No	FROM_ENTITY_ATTRIBUTE("Employee", "ID", "ManagerID") results in the Manager ID for the employee
LANGUAGE_RFC5646	Transforms language to RFC 5646 format.	None	Yes	No	LANGUAGE_RFC5646("Spanish") results in es
LAST_N	Picks the last N characters of a string.	Length (NUMBER, required): Number of characters to return	Yes	No	LAST_N("last_name", 5) results in name
LEFT_PAD	Left pads a string with a character.	Length (NUMBER, required), Pad (CHARACTER, optional): Default is space	Yes	No	LEFT_PAD("123", 5, "0") results in 00123
LOOKUP	Transforms a value using a lookup table.	Table Name (STRING, required), Column Name (STRING, required), Return Column Name (STRING, required)	Yes	No	LOOKUP("IL001", "locationTable", "location_code", "city") results in Chicago
LOWER	Transforms string to lowercase.	None	Yes	No	LOWER("HELLO") results in hello
LOWER_CAMEL_CASE	Transforms string to lower camel case.	None	Yes	No	LOWER_CAMEL_CASE("hello world") results in helloWorld
LOWER_SNAKE_CASE	Transforms string to lowercase with underscores.	None	Yes	No	LOWER_SNAKE_CASE("Hello World") results in hello_world
NEXT_NUMBER	Generates a set of integers as strings.	BeginInteger (NUMBER, required), Length (NUMBER, required)	No	Yes	NEXT_NUMBER(2, 3) results in "", "2", "3", "4". Note: NEXT_NUMBER can also be used within IF/ELSE conditional transformers for intelligent username generation with automatic fallback strategies.
PHONE_NUMBER_E164	Transforms phone number to E.164 format.	Region (STRING, optional): ISO 3166-1 alpha-2 format	Yes	No	PHONE_NUMBER_E164("[phone]") results in [phone]
RANDOM_ALPHANUMERIC_GENERATOR	Generates a random alphanumeric string.	Length (NUMBER, required)	No	No	RANDOM_ALPHANUMERIC_GENERATOR(8) results in a1B2c3D4
RANDOM_NUMBER_GENERATOR	Generates a random number string.	Length (NUMBER, required)	No	No	RANDOM_NUMBER_GENERATOR(4) results in 4829
RANDOM_STRING_GENERATOR	Generates a random string.	Length (NUMBER, required)	No	No	RANDOM_STRING_GENERATOR(6) results in uFkLxw
REMOVE_CHARS	Removes all instances of specified characters from a string.	Characters (STRING, required): Characters to be removed	Yes	No	REMOVE_CHARS("[email protected]", "@.") results in FirstLastexamplecom
REMOVE_DIACRITICS	Removes diacritics (accents, etc.) from input string.	None	Yes	No	REMOVE_DIACRITICS("José") results in Jose
REMOVE_DOMAIN	Removes the domain from an email.	None	Yes	No	REMOVE_DOMAIN("[email protected]") results in user
REMOVE_WHITESPACE	Removes all whitespace characters from a string.	None	Yes	No	REMOVE_WHITESPACE("First Last") results in FirstLast
REPLACE_ALL	Replaces all instances of one string with another.	Original (STRING, required), New (STRING, required)	Yes	No	REPLACE_ALL("hello world", " ", "_") results in hello_world
RIGHT_PAD	Right pads a string with a character.	Length (NUMBER, required), Pad (CHARACTER, optional): Default is space	Yes	No	RIGHT_PAD("123", 5, "0") results in 12300
SPLIT	Splits a string and returns the string at the given index.	Split String (STRING, required), Index (NUMBER, required)	Yes	No	SPLIT("[email protected]", "@", 0) results in first.last
SUB_STRING	Picks a substring from the original value.	Offset (NUMBER, required), Length (NUMBER, required)	Yes	No	SUB_STRING("hello", 0, 3) results in hel
TRIM	Removes spaces before and after a string.	None	Yes	No	TRIM(" hello ") results in hello
TRIM_CHARS	Removes all specified characters from the beginning and end of a string.	Characters (STRING, required): Characters to be trimmed	Yes	No	TRIM_CHARS("....first.last----", ".-") results in first.last
TRIM_CHARS_LEFT	Removes all specified characters from the beginning of a string.	Characters (STRING, required): Characters to be trimmed from the left	Yes	No	TRIM_CHARS_LEFT("....first.last----", ".-") results in first.last----
TRIM_CHARS_RIGHT	Removes all specified characters from the end of a string.	Characters (STRING, required): Characters to be trimmed from the right	Yes	No	TRIM_CHARS_RIGHT("....first.last----", ".-") results in ....first.last
UPPER	Transforms string to uppercase.	None	Yes	No	UPPER("hello") results in HELLO
UPPER_CAMEL_CASE	Transforms string to upper camel case.	None	Yes	No	UPPER_CAMEL_CASE("hello world") results in HelloWorld
UPPER_SNAKE_CASE	Transforms string to uppercase with underscores.	None	Yes	No	UPPER_SNAKE_CASE("hello world") results in HELLO_WORLD
UUID_GENERATOR	Generates a UUID.	None	No	No	UUID_GENERATOR() results in 123e4567-e89b-12d3-a456-426614174000

Using the ASCII Transformer

The ASCII transformer is particularly useful when working with international user data or systems that have strict character limitations (such as Active Directory sAMAccountName restrictions). This transformer performs two main operations:

1. Removes all non-printable characters (including control codes, zero-width spaces, tabs, and newlines)

2. Converts non-ASCII characters to their closest ASCII equivalents

Whereas the REMOVE_DIACRITICS transformer only removes accent marks while preserving the basic character, the ASCII transformer performs a more comprehensive conversion, replacing characters like "Ł" with "L" and handling a wider range of non-ASCII characters.

Using the DATE_FORMAT Transformer

The DATE_FORMAT transformer formats date strings using Go time package layout syntax. This transformer is useful for converting between different date formats, such as transforming dates for LDAP integration or standardizing date formats across systems.

Go Time Layout Syntax

Go time layouts use a specific reference time: Monday, January 2, 15:04:05 MST 2006, which is Unix time 1136239445. All layout strings must use the exact digits and format from this reference time. For more information about Go time layouts, refer to the official Go time package documentation.

Date Components:

• 2006 = 4-digit year

• 06 = 2-digit year

• 01 = 2-digit month (01-12)

• 1 = 1-digit month (1-12)

• Jan = 3-letter month abbreviation

• January = full month name

• 02 = 2-digit day (01-31)

• 2 = 1-digit day (1-31)

• _2 = space-padded day

Time Components:

• 15 = 24-hour format hour (00-23)

• 03 = 12-hour format hour (01-12)

• 3 = 12-hour format hour without leading zero (1-12)

• 04 = minute (00-59)

• 4 = minute without leading zero (0-59)

• 05 = second (00-59)

• 5 = second without leading zero (0-59)

• PM = AM/PM indicator

• pm = am/pm indicator (lowercase)

Weekday Components:

• Mon = 3-letter weekday abbreviation

• Monday = full weekday name

Time Zone Components:

• MST = time zone abbreviation

• Z0700 = RFC3339 time zone format

• Z07:00 = RFC3339 time zone format with colon

Common Layout Examples

Layout String	Format	Example Output
01/02/2006	MM/DD/YYYY	03/15/2023
2006-01-02	YYYY-MM-DD	2023-03-15
02-Jan-2006	DD-MMM-YYYY	15-Mar-2023
Jan 2, 2006	MMM D, YYYY	Mar 15, 2023
Monday, January 2, 2006	Full date	Wednesday, March 15, 2023
2006-01-02 15:04:05	Full timestamp	2023-03-15 14:30:25
03:04:05 PM	12-hour time	02:30:25 PM
15:04	24-hour time	14:30
20060102150405Z	LDAP Z time format	20230315143025Z

Usage Examples

Basic Date Formatting:

{start_date | DATE_FORMAT, "01/02/2006"}

Formats any recognized date input into MM/DD/YYYY format.

Converting Between Specific Formats:

{hire_date | DATE_FORMAT, "2006-01-02", "01/02/2006"}

Parses input in MM/DD/YYYY format and outputs in YYYY-MM-DD format.

LDAP Integration Example:

The DATE_FORMAT transformer was specifically enhanced to support LDAP Z time format requirements. The Z time format (20060102150405Z) is commonly used in LDAP directories and represents timestamps in UTC with a 'Z' suffix indicating zero UTC offset.

{timestamp | DATE_FORMAT, "20060102150405Z"}

Converts a date to LDAP Z time format for directory integration.

Example for LDAP account expiration:

{account_expires | DATE_FORMAT, "20060102150405Z"}

Human-Readable Format:

{event_date | DATE_FORMAT, "Monday, January 2, 2006"}

Outputs a full, human-readable date format.

Time Zone Handling:

{utc_time | DATE_FORMAT, "2006-01-02 15:04:05 MST"}

Includes time zone information in the output.

Notes on DATE_FORMAT Transformers

• Input Format: When the second parameter (input layout) is omitted, the transformer attempts to parse the input using common date formats automatically

• Case Sensitivity: Layout components are case-sensitive (e.g., PM vs pm)

• Leading Zeros: Use 01, 02, etc. for zero-padded values, and 1, 2, etc. for non-padded values

• Reference Time: All layouts must use the exact reference time digits: Mon Jan 2 15:04:05 MST 2006

String Manipulation Transformers

These transformers provide capabilities for cleaning, formatting, and standardizing string data from your source systems.

REMOVE_CHARS

The REMOVE_CHARS transformer removes all instances of specified characters from a string. This is useful for cleaning up data by removing unwanted punctuation, special characters, or formatting elements.

Use Cases:

• User ID creation: {email | REMOVE_CHARS, "@._-"}

  • If email is "[email protected]", the result is "johndoeexamplecom"

• Phone number formatting: {phone_number | REMOVE_CHARS, "()- "}

  • If phone_number is "[phone]", the result is "1234567890"

• Cleaning account names: {account_name | REMOVE_CHARS, "!@#$%"}

  • Removes special characters that might cause issues in target systems

REMOVE_WHITESPACE

The REMOVE_WHITESPACE transformer removes all whitespace characters (spaces, tabs, newlines) from a string. It can help create compact identifiers or ensuring data consistency.

Use Cases:

• Username generation: {display_name | REMOVE_WHITESPACE}

  • If display_name is "John A. Doe", the result is "JohnA.Doe"

• Tag creation: {department | REMOVE_WHITESPACE | LOWER}

  • If department is "Human Resources", the result is "humanresources"

• Creating system identifiers: {cost_center | REMOVE_WHITESPACE}

  • Ensures cost center codes have no embedded spaces

TRIM, TRIM_CHARS, TRIM_CHARS_LEFT, and TRIM_CHARS_RIGHT

These transformers help clean up strings by removing unwanted characters from the beginning and/or end of strings. This is essential for data hygiene and ensuring consistent formatting.

TRIM: Removes leading and trailing whitespace

• Basic cleanup: {display_name | TRIM}

  • If display_name is " John Doe ", the result is "John Doe"

TRIM_CHARS: Removes specified characters from both ends

• Cleaning employee IDs: {employee_id | TRIM_CHARS, "0."}

  • If employee_id is "000.123.000", the result is "123"

• Removing padding characters: {code | TRIM_CHARS, "-_"}

  • If code is "---ABC123___", the result is "ABC123"

TRIM_CHARS_LEFT: Removes specified characters from the beginning only

• Removing leading zeros: {cost_center | TRIM_CHARS_LEFT, "0"}

  • If cost_center is "00012345", the result is "12345"

• Cleaning prefixes: {identifier | TRIM_CHARS_LEFT, "x"}

  • If identifier is "xxxABC123", the result is "ABC123"

TRIM_CHARS_RIGHT: Removes specified characters from the end only

• Removing trailing characters: {office_code | TRIM_CHARS_RIGHT, "0"}

  • If office_code is "ABC12300", the result is "ABC123"

• Cleaning suffixes: {code | TRIM_CHARS_RIGHT, "temp"}

  • If code is "ABC123temp", the result is "ABC123"

Advanced Conditional Logic with NEXT_NUMBER

The NEXT_NUMBER transformer can be combined with IF/ELSE conditional logic to create intelligent username generation with automatic fallback strategies. This is particularly useful for handling length constraints and ensuring unique usernames in Lifecycle Management attribute transformers.

• Only one NEXT_NUMBER transformer can be used per transformation expression

• The first alternative uses an empty string (""), followed by numbered alternatives ("2", "3", etc.)

• Alternative values are automatically generated to ensure username uniqueness

Username Generation with Length-Based Fallbacks

This example creates usernames that adapt based on length constraints, using the sys_attr__would_be_value_len system attribute to evaluate the length of the generated value:

IF sys_attr__would_be_value_len le 20
  {first_name | LOWER}.{last_name | LOWER | NEXT_NUMBER, 2, 3}
ELSE IF sys_attr__would_be_value_len le 30
  {first_name | LOWER}.{last_name | LOWER | FIRST_N, 1 | NEXT_NUMBER, 2, 3}
ELSE
  {first_name | LOWER | FIRST_N, 1}.{last_name | LOWER | FIRST_N, 1 | NEXT_NUMBER, 2, 3}

Example outputs:

For a user named "John Whitaker" (short enough for the first condition):

• Base value: john.whitaker

• Alternatives: john.whitaker2, john.whitaker3, john.whitaker4

For a user named "Leonevenkataramanathan Foster" (requires truncation to meet length limits):

• Base value: l.f

• Alternatives: l.f2, l.f3, l.f4

This approach ensures that username generation adapts to different name lengths while maintaining consistency and uniqueness across your identity management system.

Pipeline Functions

You can pipeline multiple transformation functions together, separated by a |. Each will apply in sequence, allowing for complex attribute formatters that use the output of one function as the input of another.

Example Pipeline Functions

• {name | UPPER}

  • If name = Smith, the result is SMITH.

• {first_name | SUB_STRING,0,1 | LOWER}.{last_name | LOWER}

  • If first_name = John and last_name = Smith, the result is j.smith.

• {email | REMOVE_DOMAIN}

  • If email = [email protected], the result is john.smith.

• {email | REPLACE_ALL, " ", "."}

  • If email = john [email protected], the result is [email protected].

• {location | LOOKUP locationTable, location_code, city}

  • If location = IL001, the result is Chicago (using a lookup table named locationTable).

• {start_date | DATE_FORMAT, "01/02/2006" | UPPER}

  • If start_date = 2023-03-15, the result is 03/15/2023 (DATE_FORMAT doesn't typically need UPPER, but shows pipeline capability).

• {hire_date | DATE_FORMAT, "Jan 2, 2006" | REPLACE_ALL, " ", "_"}

  • If hire_date = 2023-03-15, the result is Mar_15,_2023.

• {office_code | TRIM_CHARS_LEFT, ".0" | TRIM_CHARS_RIGHT, ".USCA"}

  • If office_code = 000.8675309.USCA, the result is 8675309.

• {username | REMOVE_CHARS, ".-_" | TRIM | UPPER}

  • If username = "--john.doe_--", the result is JOHNDOE.

• {employee_id | REMOVE_CHARS, "#" | TRIM_CHARS, "0" | LEFT_PAD, 6, "0"}

  • If employee_id = "##001234##", the result is 001234.

• {department | REMOVE_WHITESPACE | LOWER | REPLACE_ALL, "&", "and"}

  • If department = "Sales & Marketing", the result is salesandmarketing.