Sensitive data masking in OneAgent

Your log data contains information that may be considered sensitive. Specific log messages may include user names, email addresses, URL parameters, and other information that you may not want to disclose. Log Monitoring features the ability to mask any information by modifying the configuration file on each OneAgent that handles information you consider to be sensitive.

Masking is performed directly on OneAgent, ensuring that sensitive data are never ingested into the system.

You can select the data that needs to be protected by applying a set of masking rules. Within each rule, you can decide what to hide and replace your hidden content with. If you need to address only specific attributes, such as predefined containers, log sources, or process groups, you can achieve it by adding matchers to your rules.

Create rule

You can configure sensitive data masking on the host, host group or environment level.

  1. Go to Settings > Log Monitoring > Sensitive data masking, and select Add rule to start configuring your rule.

  2. Rule name: The name to display for your configuration.

  3. Search expression: A regular expression to match the string that you want to mask. Use the regular expression format.

  4. Select Test your regular expression. Input sample logs to test your regular expression against, and select Test to view the result.

  5. Masking type: You can replace your data with a string or Secure Hash Algorithm 256 (SHA-256) (SHA-1 is deprecated).

    • If you select SHA-256, your data will be replaced by the 40-character hash string.
    • If you select replace with string, set Replacement to the string that is meant to replace your sensitive data.
  6. Select Add condition to create a specific match for this rule and narrow down the scope for that rule. You can include multiple matchers in one rule. For example, the masking rule can be applied to logs from a specific container, namespace, or log source.

  7. Select the matching attribute.

    Attribute

    Description

    Search dropdown logic

    Process group

    Matching is based on the process group ID.

    Attributes visible in the last 3 days are listed.

    Log source

    Matching is based on a log path; wildcards are supported in form of an asterisk. Autocompletion for Log source is only partial. You can either choose one of the predefined values or enter your log source.

    Can be entered manually. No time limit.

    Log source origin1

    Matching is based on the detector was used by the log agent to discover the log file.

    Can be entered manually. No time limit.

    Host tag23

    Matching is based on the host tag. The attribute only supports the tags set with the OneAgent command line tool or with the Remote configuration in a key=value pair format. They can be distinguished by the [Environment] prefix on the UI, but you should use the value without the prefix. Multiple tags can be specified in a single matcher, but each tag needs to have the same key, such as logscope=frontend, logscope=backend.

    Can be entered manually. No time limit.

    K8s container name

    Matching is based on the name of the Kubernetes container.

    Attributes visible in the last 90 days are listed.

    K8s namespace name

    Matching is based on the name of the Kubernetes namespace.

    Attributes visible in the last 90 days are listed.

    K8s deployment name

    Matching is based on the name of the Kubernetes deployment.

    Attributes visible in the last 90 days are listed.

    Container name

    Matching is based on the name of the container.

    Attributes visible in the last 90 days are listed.

    DT entity container group ID

    Matching is based on any of the selected container groups.

    Can be entered manually. No time limit.

    Process technology

    Matching is based on the technology name.

    Can be entered manually. No time limit.

    1

    The minimum required OneAgent version is 1.295.

    2

    Manually or automatically applied tags are not visible to OneAgent.

    3

    The minimum required OneAgent version is 1.289.

  8. Select Add value and select the detected log data items from the Values list (log files or process groups containing log data). Multiple values can be added to the selected operator. You can have one matcher that indicates log source and matches values /var/log/syslog and Windows Application Log.

  9. Select Save changes.

Defined rules can be reordered, and they are executed in the order in which they appear on the Sensitive data masking page.

Rule hierarchy

Masking rule execution occurs in a predefined hierarchy, from top to bottom. Each consecutive rule is applied to the result of a preceding rule. The hierarchy is as follows:

  1. Host configuration rules
  2. Host group configuration rules
  3. Environment configuration rules

Host configuration rules

The host configuration rules can be accessed through the Host settings for a specific host.

  1. Go to Hosts or Hosts Classic (latest Dynatrace).
  2. Find and select your host to display the host overview page.
  3. In the upper-right corner of the host overview page, select More () > Settings.
  1. From the host settings, go to Log Monitoring > Sensitive data masking.
  2. Configure data masking by adding rules with a set of matchers that identify your sensitive data.

Host group configuration rules

The host group configuration rules can be accessed via the Host page.

  1. Go to Hosts or Hosts Classic (latest Dynatrace) and select the host that interests you.
  2. On the host overview page, select Properties and tags.
  3. On the Properties and tags panel, find the Host group property to see the name of the host group to which the selected host belongs.

    The Host group property is not displayed when the selected host doesn't belong to any host group.

  4. Select the host group name to list all hosts in that host group. This displays the OneAgent deployment page filtered by the selected host group. Each listed host has a Host group: <group name> link, where <group name> is the name of the host group that you want to configure.
  5. Select the host group name in any row.
  1. In the host group settings, select Log Monitoring > Sensitive data masking.
  2. Configure data masking by adding rules with a set of matchers that identify your sensitive data.

Environment configuration rules

The tenant scope is available in the settings menu.

  1. Go to Settings and select Log Monitoring > Sensitive data masking.
  2. Configure data masking by adding rules with a set of matchers that identify your sensitive data.

REST API

You can use the Settings API to manage your sensitive data masking configuration:

  • View schema
  • List stored configuration objects
  • View single configuration object
  • Create, edit, or remove configuration object

To check the current schema version for sensitive data masking configuration, list all available schemas and look for the builtin:logmonitoring.sensitive-data-masking-settings schema identifier. Sensitive data masking configuration objects are available for configuration on the following scopes:

  • tenant—configuration object affects all hosts in a given environment.
  • host_group—configuration object affects all hosts assigned to a given host group.
  • host—configuration object affects only the given host.

To create a sensitive data masking configuration using the API

  1. Create an access token with the Write settings (settings.write) and Read settings (settings.read) permissions.
  2. Use the GET a schema endpoint to learn the JSON format required to post your configuration. The sensitive data masking configuration schema identifier (schemaId) is builtin:sensitive-data-masking-settings. Here is an example JSON payload with the sensitive data masking configuration:
[
{
"schemaId":"builtin:logmonitoring.sensitive-data-masking-settings",
"scope":"tenant",
"value":{
"config-item-title":"Added from REST API",
"masking":{
"expression":"run (\\d+?)",
"type":"STRING",
"replacement":"testing"
},
"matchers":[
{
"attribute":"log.source",
"operator":"MATCHES",
"values":[
"/var/log/syslog"
]
}
]
}
}
]

SHA-256 examples

You can mask such data as your credit card or phone number, with or without specifying the capturing group.

Mask credit card number

In this example, you will configure a sensitive data masking rule that targets a credit card number in the following log record:

Username: John Doe, CreditCardNumber: 1234-1234-1234-1234

The rule is further narrowed to the c:\inetpub\logs\LogFiles\ex_*.log files in two process groups: IIS (PROCESS_GROUP-3D9D854163F8F07A) and IIS (PROCESS_GROUP-4A7B47FDB53137AE).

Go to Settings and select Log Monitoring > Sensitive data masking

  1. Select Create new rule and provide the name for your configuration.
  2. Provide a regular expression for the credit card number, such as CreditCardNumber: (\d{4}-\d{4}-\d{4}-\d{4}).
  3. Select SHA-256 for Masking type.
  4. Select Add condition.
  5. From the Matcher attribute list select Process group.
  6. In the Value field, type IIS, and select IIS (PROCESS_GROUP-3D9D854163F8F07A) from the suggestions list.
  7. In the Value field, again type IIS, and select the second process group from the suggestions list: PROCESS_GROUP-4A7B47FDB53137AE.
  8. Select Add matcher again.
  9. Select the matching attribute Log Source.
  10. Select Add value and type c:\inetpub\logs\LogFiles\ex_*.log.
  11. Save changes.

Only content found within a capturing group is masked, and it is transformed to the following:

Username: John Doe, CreditCardNumber: 7e938e089861f3975b38cff3a93cc3aa659f7779

Mask phone number

In this example, you will configure a sensitive data masking rule that targets all phone numbers in the following log record for all log files.

Username: John Doe, PhoneNumber: +48123010100

Go to Settings and select Log Monitoring > Sensitive data masking.

  1. Select Create new rule and provide the name for your configuration.
  2. Provide a regular expression for the phone number. For example, PhoneNumber: [0-9\-\+]{9,15}.
  3. Select SHA-256 for Masking type.
  4. Select Add matcher.
  5. Save changes.

The capturing group is not specified, so the full expression is treated as one capturing group and is masked so that it is transformed into the following in all log files:

Username: John Doe, 011897d555c81e88f286cbb74c59f4ad99ec2f8d

Advanced SHA-256 examples

In the examples below, you can see how various combinations of sensitive data can be masked. You can use the listed payload JSON files in the REST API, or enter the listed masking rules, matchers, Regex expressions, and attributes directly when creating your rules via Dynatrace web UI.

Mask credit card numbers and emails

To mask all credit card numbers and emails in your content, you need to create two separate rules, each with a different matcher:

{
"masking": {
"expression": "(\\d{4}-\\d{4}-\\d{4}-\\d{4})",
"type": "STRING",
"replacement": "MaskedCreditCardNumber"
},
"matchers": [
],
"enabled": true
},
{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
],
"enabled": true
}

Mask Apache logs

To mask logs that are written by Apache AND whose log filename is error.log, you can create one rule with two matchers:

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "log.source",
"values": [
"/path/to/error.log"
]
},
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID"
]
}
],
"enabled": true
}

To mask logs that are written by Apache OR whose log filename is error.log, you need to create two rules with one matcher each:

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "log.source",
"values": [
"/path/to/error.log"
]
}
],
"enabled": true
},
{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID"
]
}
],
"enabled": true
}

To mask logs that are written by Apache and whose log filename starts with error AND ends with log, you need to have one rule with three matchers, each matcher having one value.

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "log.source",
"values": [
"/path/to/error*"
]
},
{
"attribute": "log.source",
"values": [
"*log"
]
},
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID"
]
}
],
"enabled": true
}

To mask logs that Apache writes and whose log filename starts with error OR ends with log, you need to have one rule with two matchers, one with the process group value, and the second one with two content values, /path/to/error* and *log:

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "log.source",
"values": [
"/path/to/error*", "*log"
]
},
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID"
]
}
],
"enabled": true
}

Mask Apache or MySQL logs

To mask logs that are written by Apache or MySQL, you need to have either two rules or one rule with one matcher that has two values.

The scenario with two rules:

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-MYSQL"
]
}
],
"enabled": true
},
{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID"
]
}
],
"enabled": true
}

The scenario with one rule with a matcher that has two values:

{
"masking": {
"expression": "email: (.*),",
"type": "SHA256"
},
"matchers": [
{
"attribute": "dt.entity.process_group",
"values": [
"PROCESS_GROUP-APACHEID", "PROCESS_GROUP-MYSQL"
]
}
],
"enabled": true
}

Regex examples

The common regex formats for sensitive data include:

Sensitive data type

ReGEx

IPv4

\b\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\b

Email address

\b[\w\-\._]+?@[\w\-\._]+?\.\w{2,10}?\b

Credit card number

\b[0-9]{4}-[0-9]{4}-[0-9]{4}-[0-9]{4}\b

Phone number

\+?[0-9]{3}-?[0-9]{6,12}\b

Unsupported regular expressions

Data masking occurs within the entire expression or a capturing group. An expression has to match the regular expression engine syntax, and it cannot:

  • Be part of more than one capturing group
  • Contain the lookbehind zero-length assertion in a capturing group
  • Contain the backreference zero-length assertion in a capturing group
  • Contain greedy quantifiers (such as x?, x*, or x+) or possessive quantifiers (such as x?+, x*+, or xx++). Use lazy/reluctant qualifiers (such as x?? and x+?) instead.

Frequently asked questions

You can execute sensitive data masking in your environment so that the confidential data does not leave your infrastructure unprotected. If you import your data to Dynatrace via generic ingest, you need to mask the sensitive data on the source level, before ingestion. Alternatively, you can mask sensitive data during Log Processing. However, if you choose to mask your data during Log processing, your data will leave your environment as log processing occurs on the Dynatrace side. Therefore, it is safer to mask it within your environment.

One. If none is provided, then the entire scope of the regular expression you provide is treated as one capturing group.

Sensitive data masking limits

Be aware of the following limitations to sensitive data masking:

  • If the masking process takes too much time, the log file affected is blocked until the restart of OneAgent or any configuration change, and then you get the File not monitored - incorrect sensitive data masking rule message.