Masking

This filter was introduced in MariaDB MaxScale 2.1.

Overview

With the masking filter it is possible to obfuscate the returned value of a particular column.

For instance, suppose there is a table person that, among other columns, contains the column ssn where the social security number of a person is stored.

With the masking filter it is possible to specify that when the ssn field is queried, a masked value is returned unless the user making the query is a specific one. That is, when making the query

> SELECT name, ssn FROM person;

instead of getting the real result, as in

+-------+-------------+
+ name  | ssn         |
+-------+-------------+
| Alice | 721-07-4426 |
| Bob   | 435-22-3267 |
...

the ssn would be masked, as in

+-------+-------------+
+ name  | ssn         |
+-------+-------------+
| Alice | XXX-XX-XXXX |
| Bob   | XXX-XX-XXXX |
...

Note that the masking filter should be viewed as a best-effort solution intended for protecting against accidental misuse rather than malicious attacks.

Security

From MaxScale 2.3 onwards, the masking filter will reject statements that use functions in conjunction with columns that should be masked. Allowing function usage provides a way for circumventing the masking, unless a firewall filter is separately configured and installed.

Please see the configuration parameter prevent_function_usage for how to change the default behaviour.

From MaxScale 2.3.5 onwards, the masking filter will check the definition of user variables and reject statements that define a user variable using a statement that refers to columns that should be masked.

Please see the configuration parameter check_user_variables for how to change the default behaviour.

From MaxScale 2.3.5 onwards, the masking filter will examine unions and if the second or subsequent SELECT refer to columns that should be masked, the statement will be rejected.

Please see the configuration parameter check_unions for how to change the default behaviour.

From MaxScale 2.3.5 onwards, the masking filter will examine subqueries and if a subquery refers to columns that should be masked, the statement will be rejected.

Please see the configuration parameter check_subqueries for how to change the default behaviour.

Note that in order to ensure that it is not possible to get access to masked data, the privileges of the users should be minimized. For instance, if a user can create tables and perform inserts, he or she can execute something like

CREATE TABLE cheat (revealed_ssn TEXT);
INSERT INTO cheat SELECT ssn FROM users;
SELECT revealed_ssn FROM cheat;

to get access to the cleartext version of a masked field ssn.

From MaxScale 2.3.5 onwards, the masking filter will, if any of the prevent_function_usage, check_user_variables, check_unions or check_subqueries parameters is set to true, block statements that cannot be fully parsed.

Please see the configuration parameter require_fully_parsed for how to change the default behaviour.

From MaxScale 2.3.7 onwards, the masking filter will treat any strings passed to functions as if they were fields. The reason is that as the MaxScale query classifier is not aware of whether ANSI_QUOTES is enabled or not, it is possible to bypass the masking by turning that option on.

mysql> set @@sql_mode = 'ANSI_QUOTES';
mysql> select concat("ssn") from managers;

Before this change, the content of the field ssn would have been returned in clear text even if the column should have been masked.

Note that this change will mean that there may be false positives if ANSI_QUOTES is not enabled and a string argument happens to be the same as the name of a field to be masked.

Please see the configuration parameter [treat_string_arg_as_field(#treat_string_arg_as_field) for how to change the default behaviour.

Limitations

The masking filter can only be used for masking columns of the following types: BINARY, VARBINARY, CHAR, VARCHAR, BLOB, TINYBLOB, MEDIUMBLOB, LONGBLOB, TEXT, TINYTEXT, MEDIUMTEXT, LONGTEXT, ENUM and SET. If the type of the column is something else, then no masking will be performed.

Currently, the masking filter can only work on packets whose payload is less than 16MB. If the masking filter encounters a packet whose payload is exactly that, thus indicating a situation where the payload is delivered in multiple packets, the value of the parameter large_payloads specifies how the masking filter should handle the situation.

Configuration

The masking filter is taken into use with the following kind of configuration setup.

[Mask-SSN]
type=filter
module=masking
rules=...

[SomeService]
type=service
...
filters=Mask-SSN

Filter Parameters

The masking filter has one mandatory parameter - rules.

rules

• Type: path
• Mandatory: Yes
• Dynamic: Yes

Specifies the path of the file where the masking rules are stored. A relative path is interpreted relative to the module configuration directory of MariaDB MaxScale. The default module configuration directory is /etc/maxscale.modules.d.

rules=/path/to/rules-file

warn_type_mismatch

• Type: enum
• Mandatory: No
• Dynamic: Yes
• Values: never, always
• Default: never

With this optional parameter the masking filter can be instructed to log a warning if a masking rule matches a column that is not of one of the allowed types.

warn_type_mismatch=always

large_payload

• Type: enum
• Mandatory: No
• Dynamic: Yes
• Values: ignore, abort
• Default: abort

This optional parameter specifies how the masking filter should treat payloads larger than 16MB, that is, payloads that are delivered in multiple MySQL protocol packets.

The values that can be used are ignore, which means that columns in such payloads are not masked, and abort, which means that if such payloads are encountered, the client connection is closed. The default is abort.

Note that the aborting behaviour is applied only to resultsets that contain columns that should be masked. There are no limitations on resultsets that do not contain such columns.

large_payload=ignore

prevent_function_usage

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should behave if a column that should be masked, is used in conjunction with some function. As the masking filter works only on the basis of the information in the returned result-set, if the name of a column is not present in the result-set, then the masking filter cannot mask a value. This means that the masking filter basically can be bypassed with a query like:

SELECT CONCAT(masked_column) FROM tbl;

If the value of prevent_function_usage is true, then all statements that contain functions referring to masked columns will be rejected. As that means that also queries using potentially harmless functions, such as LENGTH(masked_column), are rejected as well, this feature can be turned off. In that case, the firewall filter should be setup to allow or reject the use of certain functions.

prevent_function_usage=false

require_fully_parsed

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should behave in case any of prevent_function_usage, check_user_variables, check_unions or check_subqueries is true and it encounters a statement that cannot be fully parsed,

If true, then statements that cannot be fully parsed (due to a parser limitation) will be blocked.

require_fully_parsed=false

Note that if this parameter is set to false, then prevent_function_usage, check_user_variables, check_unions and check_subqueries are rendered less effective, as it with a statement that can not be fully parsed may be possible to bypass the protection that they are intended to provide.

treat_string_arg_as_field

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should treat strings used as arguments to functions. If true, they will be handled as fields, which will cause fields to be masked even if ANSI_QUOTES has been enabled and " is used instead of backtick.

treat_string_arg_as_field=false

check_user_variables

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should behave with respect to user variables. If true, then a statement like

set @a = (select ssn from customer where id = 1);

will be rejected if ssn is a column that should be masked.

check_user_variables=false

check_unions

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should behave with respect to UNIONs. If true, then a statement like

SELECT a FROM t1 UNION select b from t2;

will be rejected if b is a column that should be masked.

check_unions=false

check_subqueries

• Type: bool
• Mandatory: No
• Dynamic: Yes
• Default: true

This optional parameter specifies how the masking filter should behave with respect to subqueries. If true, then a statement like

SELECT * FROM (SELECT a as b FROM t1) as t2;

will be rejected if a is a column that should be masked.

check_subqueries=false

Rules

The masking rules are expressed as a JSON object.

The top-level object is expected to contain a key rules whose value is an array of rule objects.

{
    "rules": [ ... ]
}

Each rule in the rules array is a JSON object, expected to contain the keys replace, with, applies_to and exempted. The two former ones are obligatory and the two latter ones optional.

{
    "rules": [
        {
            "replace": { ... },
            "with": { ... },
            "applies_to": [ ... ],
            "exempted": [ ... ]
        }
    ]
}

replace

The value of this key is an object that specifies the column whose values should be masked. The object must contain the key column and may contain the keys table and database. The value of these keys must be a string.

If only column is specified, then a column with that name matches irrespective of the table and database. If table is specified, then the column matches only if it is in a table with the specified name, and if database is specified when the column matches only if it is in a database with the specified name.

{
    "rules": [
        {
            "replace": {
                "database": "db1",
                "table": "person",
                "column": "ssn"
            },
            "with": { ... },
            "applies_to": [ ... ],
            "exempted": [ ... ]
        }
    ]
}

NOTE If a rule contains a table/database then if the resultset does not contain table/database information, it will always be considered a match if the column matches. For instance, given the rule above, if there is a table person2, also containing an ssn field, then a query like

SELECT ssn FROM person2;

will not return masked values, but a query like

SELECT ssn FROM person UNION SELECT ssn FROM person2;

will only return masked values, even if the ssn values from person2 in principle should not be masked. The same effect is observed even with a nonsensical query like

SELECT ssn FROM person2 UNION SELECT ssn FROM person2;

even if nothing from person2 should be masked. The reason is that as the resultset contains no table information, the values must be masked if the column name matches, as otherwise the masking could easily be circumvented with a query like

SELECT ssn FROM person UNION SELECT ssn FROM person;

The optional key match makes partial replacement of the original value possible: only the matched part would be replaced with the fill character. The match value must be a valid pcre2 regular expression.

            "replace": {
                "column": "ssn",
                "match": "(123)"
            },
            "with": {
                "fill": "X#"
            }

obfuscate

The obfuscate rule allows the obfuscation of the value by passing it through an obfuscation algorithm. Current solution uses a non-reversible obfuscation approach.

However, note that although it is in principle impossible to obtain the original value from the obfuscated one, if the range of possible original values is limited, it is straightforward to figure out the possible original values by running all possible values through the obfuscation algorithm and then comparing the results.

The minimal configuration is:

            "obfuscate": {
                "column": "name"
            }

Output example for Db field name = 'remo'

SELECT name from db1.tbl1;`

+------+
| name |
+------+
| $-~) |
+------+

with

The value of this key is an object that specifies what the value of the matched column should be replaced with for the replace rule. Currently, the object is expected to contain either the key value or the key fill. The value of both must be a string with length greater than zero. If both keys are specified, value takes precedence. If fill is not specified, the default X is used as its value.

If value is specified, then its value is used to replace the actual value verbatim and the length of the specified value must match the actual returned value (from the server) exactly. If the lengths do not match, the value of fill is used to mask the actual value.

When the value of fill (fill-value) is used for masking the returned value, the fill-value is used as many times as necessary to match the length of the return value. If required, only a part of the fill-value may be used in the end of the mask value to get the lengths to match.

{
    "rules": [
        {
            "replace": {
                "column": "ssn"
            },
            "with": {
                "value": "XXX-XX-XXXX"
            },
            "applies_to": [ ... ],
            "exempted": [ ... ]
        },
        {
            "replace": {
                "column": "age"
            },
            "with": {
                "fill": "*"
            },
            "applies_to": [ ... ],
            "exempted": [ ... ]
        },
        {
            "replace": {
                "column": "creditcard"
            },
            "with": {
                "value": "1234123412341234",
                "fill": "0"
            },
            "applies_to": [ ... ],
            "exempted": [ ... ]
        },
    ]
}

applies_to

With this optional key, whose value must be an array of strings, it can be specified what users the rule is applied to. Each string should be a MariaDB account string, that is, % is a wildcard.

{
    "rules": [
        {
            "replace": { ... },
            "with": { ... },
            "applies_to": [ "'alice'@'host'", "'bob'@'%'" ],
            "exempted": [ ... ]
        }
    ]
}

If this key is not specified, then the masking is performed for all users, except the ones exempted using the key exempted.

exempted

With this optional key, whose value must be an array of strings, it can be specified what users the rule is not applied to. Each string should be a MariaDB account string, that is, % is a wildcard.

{
    "rules": [
        {
            "replace": { ... },
            "with": { ... },
            "applies_to": [ ... ],
            "exempted": [ "'admin'" ]
        }
    ]
}

Module commands

Read Module Commands documentation for details about module commands.

The masking filter supports the following module commands.

reload

Reload the rules from the rules file. The new rules are taken into use only if the loading succeeds without any errors.

MaxScale> call command masking reload MyMaskingFilter

MyMaskingFilter refers to a particular filter section in the MariaDB MaxScale configuration file.

Example

In the following we configure a masking filter MyMasking that should always log a warning if a masking rule matches a column that is of a type that cannot be masked, and that should abort the client connection if a resultset package is larger than 16MB. The rules for the masking filter are in the file masking_rules.json.

Configuration

[MyMasking]
type=filter
module=masking
warn_type_mismatch=always
large_payload=abort
rules=masking_rules.json

[MyService]
type=service
...
filters=MyMasking

masking_rules.json

The rules specify that the data of a column whose name is ssn, should be replaced with the string 012345-ABCD. If the length of the data is not exactly the same as the length of the replacement value, then the data should be replaced with as many X characters as needed.

{
    "rules": [
        {
            "replace": {
                "column": "ssn"
            },
            "with": {
                "value": "012345-ABCD",
                "fill": "X"
            }
        }
    ]
}