Edge Delta Mask Processor

The Edge Delta mask processor redacts sensitive data.

  7 minute read  

Overview

The mask processor obfuscates sensitive data in logs by replacing them with a specified set of characters, such as a series of asterisks or a custom string. Masking is important for compliance with various data protection regulations and for privacy concerns. Sensitive data is identified using a regex pattern. There are several patterns available out of the box for common regex patterns such as email, different types of credit card numbers etc. You can also create multiple different masks.

Configuration

In this example, the email address attribute’s value has been replaced with the default word REDACTED.

In this example, the IP addresses have also been redacted:

In this example, there is an api token in the body and this has been parsed into the attributes. So you use a custom regex to capture and mask both values:

This is the input:

{
  "_type": "log",
  "timestamp": 1745456397792,
  "body": "{\"timestamp\": \"2025-04-24T00:59:56.527714Z\", \"level\": \"Emergency\", \"msg\": \"Critical error in processing\", \"user\": {\"email\": \"barbara.martinez@imaginarymail.com\", \"id\": \"8d25f352-dcde-4753-84a8-45960dc99f90\", \"name\": \"d6426c02-cd40-4278-90a4-c167d4e23370\"}, \"request\": {\"ip\": \"10.29.168.111\", \"method\": \"PUT\", \"path\": \"/json/submit\"}, \"status\": 503, \"response_time_ms\": 12521, \"api_token\": \"sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez\"}",
  "resource": {
...
  },
  "attributes": {
    "api_token": "sk_live_51NWz4nEXAMPLExQbG7nB2t6h8EpF3Df7oMBez",
    "level": "Emergency",
    "msg": "Critical error in processing",
    "request": {
      "ip": "10.29.168.111",
      "method": "PUT",
      "path": "/json/submit"
    },
    "response_time_ms": 12521,
    "status": 503,
    "timestamp": "2025-04-24T00:59:56.527714Z",
    "user": {
      "email": "barbara.martinez@imaginarymail.com",
      "id": "8d25f352-dcde-4753-84a8-45960dc99f90",
      "name": "d6426c02-cd40-4278-90a4-c167d4e23370"
    }
  }
}

Note: the resource field has been omitted reduced for brevity.

This is the pattern:

sk_(live|test)_[A-Za-z0-9]{20,}

This is the output:

{
  "_type": "log",
  "timestamp": 1745456397792,
  "body": "{\"timestamp\": \"2025-04-24T00:59:56.527714Z\", \"level\": \"Emergency\", \"msg\": \"Critical error in processing\", \"user\": {\"email\": \"barbara.martinez@imaginarymail.com\", \"id\": \"8d25f352-dcde-4753-84a8-45960dc99f90\", \"name\": \"d6426c02-cd40-4278-90a4-c167d4e23370\"}, \"request\": {\"ip\": \"10.29.168.111\", \"method\": \"PUT\", \"path\": \"/json/submit\"}, \"status\": 503, \"response_time_ms\": 12521, \"api_token\": \"REDACTED\"}",
  "resource": {
...
  },
  "attributes": {
    "api_token": "REDACTED",
    "level": "Emergency",
    "msg": "Critical error in processing",
    "request": {
      "ip": "10.29.168.111",
      "method": "PUT",
      "path": "/json/submit"
    },
    "response_time_ms": 12521,
    "status": 503,
    "timestamp": "2025-04-24T00:59:56.527714Z",
    "user": {
      "email": "barbara.martinez@imaginarymail.com",
      "id": "8d25f352-dcde-4753-84a8-45960dc99f90",
      "name": "d6426c02-cd40-4278-90a4-c167d4e23370"
    }
  }
}

The pattern is designed to match any string that looks like an API secret key, regardless of where it appears in the log. In the log, “body” is a string containing escaped quotes. The actual token value itself is not escaped, it appears as-is inside the larger string. Similarly, “attributes” is regular JSON: the token value is again unescaped. This regex will match any substring in the input that looks like a token, whether it’s inside the “body” JSON-encoded string or a regular attribute.

For values that might contain special characters that are escaped in JSON (e.g. strings with quotes or backslashes), test how those appear in logs in both the body (as a string) and in parsed attributes. You may need either a more flexible regex or two patterns.

Options

Select a telemetry type

You can specify, log, metric, trace or all. It is specified using the interface, which generates a YAML list item for you under the data_types parameter. This defines the data item types against which the processor must operate. If data_types is not specified, the default value is all. It is optional.

It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    data_types:
    - log

Condition

The condition parameter contains a conditional phrase of an OTTL statement. It restricts operation of the processor to only data items where the condition is met. Those data items that do not match the condition are passed without processing. You configure it in the interface and an OTTL condition is generated. It is optional.

Important: All conditions must be written on a single line in YAML. Multi-line conditions are not supported.

Comparison Operators

Operator Name Description Example
== Equal to Returns true if both values are exactly the same attributes["status"] == "OK"
!= Not equal to Returns true if the values are not the same attributes["level"] != "debug"
> Greater than Returns true if the left value is greater than the right attributes["duration_ms"] > 1000
>= Greater than or equal Returns true if the left value is greater than or equal to the right attributes["score"] >= 90
< Less than Returns true if the left value is less than the right attributes["load"] < 0.75
<= Less than or equal Returns true if the left value is less than or equal to the right attributes["retries"] <= 3
matches Regex match Returns true if the string matches a regular expression (generates IsMatch function) IsMatch(attributes["name"], ".*\\.log$")

Logical Operators

Important: Use lowercase and, or, not - uppercase operators will cause errors!

Operator Description Example
and Both conditions must be true attributes["level"] == "ERROR" and attributes["status"] >= 500
or At least one condition must be true attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
not Negates the condition not regex_match(attributes["path"], "^/health")

Functions

Function Description Example
regex_match Returns true if string matches the pattern regex_match(attributes["message"], "ERROR\|FATAL")
IsMatch Alternative regex function (UI generates this from “matches” operator) IsMatch(attributes["name"], ".*\\.log$")

Field Existence Checks

Check Description Example
!= nil Field exists (not null) attributes["user_id"] != nil
== nil Field doesn’t exist attributes["optional_field"] == nil
!= "" Field is not empty string attributes["message"] != ""

Common Examples

- name: _multiprocessor
  type: sequence
  processors:
  - type: <processor type>
    # Simple equality check
    condition: attributes["request"]["path"] == "/json/view"
    
  - type: <processor type>
    # Multiple values with OR
    condition: attributes["log_type"] == "TRAFFIC" or attributes["log_type"] == "THREAT"
    
  - type: <processor type>
    # Excluding multiple values (NOT equal to multiple values)
    condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"
    
  - type: <processor type>
    # Complex condition with AND/OR/NOT
    condition: (attributes["level"] == "ERROR" or attributes["level"] == "FATAL") and attributes["env"] != "test"
    
  - type: <processor type>
    # Field existence and value check
    condition: attributes["user_id"] != nil and attributes["user_id"] != ""
    
  - type: <processor type>
    # Regex matching using regex_match
    condition: regex_match(attributes["path"], "^/api/") and not regex_match(attributes["path"], "^/api/health")
    
  - type: <processor type>
    # Regex matching using IsMatch
    condition: IsMatch(attributes["message"], "ERROR|WARNING") and attributes["env"] == "production"

Common Mistakes to Avoid

# WRONG - Cannot use OR/AND with values directly
condition: attributes["log_type"] != "TRAFFIC" OR "THREAT"

# CORRECT - Must repeat the full comparison
condition: attributes["log_type"] != "TRAFFIC" and attributes["log_type"] != "THREAT"

# WRONG - Uppercase operators
condition: attributes["status"] == "error" AND attributes["level"] == "critical"

# CORRECT - Lowercase operators
condition: attributes["status"] == "error" and attributes["level"] == "critical"

# WRONG - Multi-line conditions
condition: |
  attributes["level"] == "ERROR" and 
  attributes["status"] >= 500  

# CORRECT - Single line (even if long)
condition: attributes["level"] == "ERROR" and attributes["status"] >= 500

Predefined Regex Patterns

You can toggle on or off a number of predefined regex patterns such as email addresses, IP addresses etc. If your sensitive data is not covered by these you create a custom mask and define a regex pattern.

Create a custom mask

Click Create a custom mask to add a mask pattern manually. There are a number of patterns you can quickly select from the regex patterns library. Alternatively, define your own pattern and test it in the live capture output pane. With a custom mask you can also define your own mask characters (REDACTED by default).

Excluded Fields

If you have fields that you want to exclude from masking, include them in the excluded fields section. Even if the pattern matches these fields and their children, they will not be masked.

Final

Determines whether successfully processed data items should continue through the remaining processors in the same processor stack. If final is set to true, data items output by this processor are not passed to subsequent processors within the node—they are instead emitted to downstream nodes in the pipeline (e.g., a destination). Failed items are always passed to the next processor, regardless of this setting.

The UI provides a slider to configure this setting. The default is false. It is defined in YAML as follows:

- name: multiprocessor
  type: sequence
  processors:
    - type: <processor type>
    final: true

See Also