A free data masking and/or anonymizer library for Sql Server written in .NET
If you've ever needed to pull down databases from a live environment to stage or even dev you'll need to think about masking any personal information. There are options out there paid and free, however the free ones I've found do not provide genuine data and the paid options are too pricey when it's only a few tables.
Data generation is provided by https://github.com/bchavez/Bogus
Hello. I'm your host Brian Chavez (twitter). Bogus is a simple and sane fake data generator for .NET languages like C#, F# and VB.NET. Bogus is fundamentally a C# port of faker.js and inspired by FluentValidation's syntax sugar.
Bogus will help you load databases, UI and apps with fake data for your testing needs. If you like Bogus star ⭐️ the repository and show your friends! 😄
DataMasker is available as a library over on nuget.org should you need to customize any part of the process. Alternatively just ask for a new feature and I'll see what I can do.
install-package DataMasker
All configuration is done via a .json file, of which an example can be seen below.
Example Config
{
"dataSource": {
"type": "SqlServer",
"config": {
"name": "databasename",
"userName": "databaseUserName",
"password": "databasePassword",
"server": "databaseServer"
}
},
"tables": [
{
"name": "Users",
"schema": "dbo",
"primaryKeyColumn": "UserId",
"columns": [
{
"name": "FirstName",
"type": "FirstName",
"useGenderColumn": "Gender"
},
{
"name": "LastName",
"type": "LastName",
"retainEmptyStringValues": true,
"useGlobalValueMappings": true,
"valueMappings": {
"oldValue": "Jones",
"newValue": "Smith"
}
},
{
"name": "Password",
"type": "None",
"retainNullValues": false,
"useValue": "PasswordForDevEnvironment"
},
{
"name": "DOB",
"type": "DateOfBirth",
"min" :"1901-01-01",
"max": "2000-0101"
},
{
"name": "EmailAddress",
"type": "Bogus",
"unique": true,
"stringFormatPattern": "{{internet.email}}"
},
{
"name": "Gender",
"ignore": true,
"type": "None"
},
{
"name": "Address",
"type": "Bogus",
"retainNullValues": false,
"stringFormatPattern": "{{address.fullAddress}}"
},
{
"name": "ContactNumber",
"type": "PhoneNumber",
"retainNullValues": false,
"stringFormatPattern": "+447#########"
},
{
"name": "CompanyName",
"type": "Sql",
"sqlValue": {
"query":"SELECT Name FROM SampleCompanyNames WHERE UserId = @UserId",
"valueHandling": "Null"
}
}
]
}
]
}Table configuration is supplied by either the "tables" property or "tablesConfigPath" property.
If you want to keep your table configuration external to the main .json file this can be done by supplying "tablesConfigPath" with a file path. An example of this can be found in the example-configs directory in the example project.
External table config json
{
"dataSource": {
"type": "SqlServer",
"config": {
"name": "databasename",
"userName": "databaseUserName",
"password": "databasePassword",
"server": "databaseServer"
}
},
"tablesConfigPath": "example-configs\\config-example2-table-config.json",
}or embedded
{
"dataSource": {
"type": "SqlServer",
"config": {
"name": "databasename",
"userName": "databaseUserName",
"password": "databasePassword",
"server": "databaseServer"
}
},
"tables": [... insert config here ...],
}If both tables and tablesConfigPath is supplied then tablesConfigPath wins.
| Property Name | Values |
|---|---|
| type | None, Bogus, FirstName, lastName, DateOfBirth, Rant, StringFormat, FullAddress, PhoneNumber |
| name | Database column name |
| schema | Name of the schema in which the tables lives, defaults to dbo |
| valueMappings | Object with value mappings, e.g map "James" to "John" |
| useGenderColumn | Name of the database column to use as for the gender |
| ignore | true/false |
| min | Minimum value to use for the given data type |
| max | Maxiumum value to use for the given data type |
| stringFormatPattern | From Bogus, numbers #, letters ?, or * random number or letter |
| useValue | A hardcoded value to use for every row |
| retainNullValues | true/false |
| retainEmptyStringValues | true/false - when true if the existing value is null or empty (whitespace) then it will use the original value |
| useLocalValueMappings | true/false |
| useGlobalValueMappings | true/false |
| unique | true/false - when true it will attempt to generate a unique value for this column |
| sqlValue | Used when type is set to sql |
When using data type Sql this allows you to get values from other tables within the same database. The configuration object is made up of the following properties
| Property Name | Values |
|---|---|
| query | The query to use for the lookup, the current row will be passed into the query as parameters for use, see the example config above that uses @UserId. Columns are passed back into the query as parameters, any columns with spaces in their name, will be replaced with '_' . e.g. A column name "User Id" would become "User_Id" |
| valueHandling | "Null" or "KeepValue". If the query executes and no data is returned, this tells the masker what to do, null will set the value to Null while KeepValue will keep the existing value on that row |
To use None you must specify either valueMappings or useValue, no data will be generated for this type. If you specify only valueMappings and the target value is not found, an error will be thrown.
{
"name": "Title",
"type": "None",
"valueMappings": {
"Mr": "Master"
},
"ignore":"true/false",
"useValue": "Miss",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false"
}Bogus is a type that when specified requires the stringFormatPattern option, which is passed directly to the Bogus API, see here for available options
{
"name": "PhoneNumber",
"type": "Bogus",
"valueMappings": {
"+555-555-555": "+444-555-555-55"
},
"ignore":"true/false",
"useValue": "+50559-5-5-555",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"stringFormatPattern": "{{phonenumbers.phonenumber}}"
}{
"name": "FirstName",
"type": "FirstName",
"valueMappings": {
"James": "Bob"
},
"ignore":"true/false",
"useValue": "Steve",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"useGenderColumn": "Gender"
}{
"name": "Surname",
"type": "LastName",
"valueMappings": {
"Smith": "Jojnes"
},
"ignore":"true/false",
"useValue": "Timms",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false"
}minwill default to 1901-01-01maxwill default to current date- date format is
fullyear-month-day
{
"name": "DOB",
"type": "DateOfBirth",
"valueMappings": {
"1990-01-02": "1990-02-02"
},
"ignore":"true/false",
"useValue": "1940-02-02",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"min": "1901-12-25",
"max": "2000-11-20"
}maxwill default to 25
{
"name": "Comments",
"type": "Rant",
"valueMappings": {
"A comment": "Becomes this"
},
"ignore":"true/false",
"useValue": "A really important comment",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"max": 15
}minwill default to 5maxwill default to 30
{
"name": "Comments",
"type": "Lorem",
"valueMappings": {
"A comment": "Becomes this"
},
"ignore":"true/false",
"useValue": "A really important comment",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"min": 5,
"max": 15
}Check out the Bogus API for supported values
{
"name": "Comments",
"type": "StringFormat",
"valueMappings": {
"A comment": "Becomes this"
},
"ignore":"true/false",
"useValue": "A really important comment",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"stringFormatPattern": "#####****?????"
}{
"name": "Address",
"type": "FullAddress",
"valueMappings": {
"55 Long Name Street, Long Name Village, Long Name Town...": "Becomes this"
},
"ignore":"true/false",
"useValue": "55 Long Name Street, Long Name Village, Long Name Town...",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
}{
"name": "PhoneNumber",
"type": "PhoneNumber",
"valueMappings": {
"+555-555-555": "+444-555-555-55"
},
"ignore":"true/false",
"useValue": "+50559-5-5-555",
"retainNullValues": "true/false",
"retainEmptyStringValues": "true/false",
"useLocalValueMappings": "true/false",
"useGlobalValueMappings": "true/false",
"stringFormatPattern": "+1 ########-#-###-#"
}The current row is passed in as parameters and can be accessed using @ColumnName
{
"name":"CompanyName",
"type": "Sql",
"sqlValue": {
"query":"SELECT Name FROM SampleCompanyNames WHERE UserId = @UserId",
"valueHandling": "Null/KeepValue"
}
}name & type are required everything else is optional unless specified
Most data can be generated perfectly fine just by using the Bogus or StringFormat data types.
Only some data types currently use the min/max properties on the column configurations.
- Lorem, Rant & DOB
Example Usage
//load our configuration
Config config = Config.Load($"example-configs\\config-example1.json")
// you also can pass the JSON content directly:
// Config config = Config.LoadFromString(....);
//create a data masker
IDataMasker dataMasker = new DataMasker(new DataGenerator(config.DataGeneration));
//grab our dataSource from the config, note: you could just ignore the config.DataSource.Type
//and initialize your own instance
IDataSource dataSource = DataSourceProvider.Provide(config.DataSource.Type, config.DataSource);
//Enumerable all our tables and begin masking the data
foreach (TableConfig tableConfig in config.Tables)
{
//load the data, this needs optimizing for large tables
IEnumerable<IDictionary<string, object>> rows = dataSource.GetData(tableConfig);
foreach (IDictionary<string, object> row in rows)
{
//mask each row
dataMasker.Mask(row, tableConfig);
//update per row, or see below,
//dataSource.UpdateRow(row, tableConfig);
}
//update all rows, in batches of 100
dataSource.UpdateRows(rows, tableConfig, 100);
}All of the objects/datatypes from Bogus are supported, you can use the type "Bogus" in combination with "stringFormatPattern" to acheive any valueMappings
{
"name": "Address",
"type": "Bogus",
"stringFormatPattern": "{{address.fullAddress}}"
}You can combine multiple objects to generate complex data
{
"name": "Name",
"type": "Bogus",
"stringFormatPattern": "{{name.prefix}} {{name.firstName}} {{name.lastName}}"
}There are only two DataSources available at the moment
InMemoryFake- is there only for the examplesSqlServer- can pull and push data to SQL Server
There is some additional configuration required when using SqlServer, on the dataSource object a dynamic config property is available, you'll need to supply the name, server, userName & password for the connection or a connection string.
N.B. if the "connectionString" value is set name, server, userName & password will be ignored
{
"dataSource":{
"config":{
"name": "xxx",
"server": "xxx",
"userName": "xxx",
"password": "xxx",
"connectionString": "Data Source=(localdb)\\mssqllocaldb;Initial Catalog=Clients;Integrated Security=SSPI;"
}
}
}Dry run is supported. A transaction is created, the update statement is executed and then the transaction is rolled back.
To ensure the new data is more accurate you may want to take gender into consideration when generating certain data types such as names. This can be achieved with a small amount of additional configuration. If no gender is specified then non gender specific names are generated.
You must define the gender column and then tell your target column to use this when generating data.
Here we are saying, use the column "Gender" when generating data for "FirstName". We then include the "Gender" column but tell it to be ignored by the IDataMasker, it is purley there as a dependency to "FirstName".
"columns": [
{
"name": "FirstName",
"type": "FirstName",
"useGenderColumn": "Gender"
},
{
"name": "Gender",
"ignore": true,
"type": "None"
},
]By default the locale is "en", the locale.
The locale is used by Bogus to generate data, the locale can be changedby setting a property on the dataGeneration object
{
"dataGeneration": {
"locale": "en"
}
}Check out the Bogus page for a list of supported locales
The latest version can be found at https://github.com/Steveiwonder/DataMasker/releases
This is a CLI interface for the data masking tool. You might want to use this as part of your continuous integration if you backup/restore your live environments back to stage/dev after a release
The options are as follows
-c, --config-file Required. the json configuration to be
-d, --dry-run (Default: false) dry run, only supported by some data sources
-l, --locale set the locale
-u, --update-batchsize batch size to use when upating records
--print-options (Default: false) prints the arguments passed into this tool in a json format with executing anything else
--no-output (Default: false) if set, no output to the console will be written
--help Display this help screen.
--version Display version information.