Log obfuscation: Hash or mask sensitive data in your logs (2024)

With log obfuscation rules, you can prevent certain types of information from being saved in New Relic.

Requirements

Our log obfuscation feature is available as part of our Data Plus option.

What is log obfuscation?

Our service automatically masks number patterns that we identify as likely being sensitive items, such as credit card or Social Security numbers.

If you need additional obfuscation, one option is to adjust the configuration of the log forwarder you use (for example, our infrastructure agent). But an easier option is to use our log obfuscation feature, available with Data Plus. This feature lets you set up log obfuscation rules directly from the log management UI, or via our NerdGraph API, without lengthy manual configuration. You'll define regular expressions matching your sensitive information, and then create rules to obfuscate that data. You can choose either to have sensitive information masked or hashed.

Definitions

Here are some important terms:

  • Obfuscation rules define what logs to apply obfuscation actions to.
  • Obfuscation rule actions define what attributes to look at, what text to obfuscate, and how to obfuscate (either by masking or hashing).
  • Obfuscation expressions are named regular expressions identifying what text to obfuscate.
  • Masking completely removes information, replacing it with X characters. You cannot search for specific values once this is done.
  • Hashing hides information. You can use the hashing tool to get the hash of a sensitive value, and then search for logs containing that hash.

How obfuscation works

The JSON objects displayed in the following example are simplifications of the payloads used by our NerdGraph API. This will help you better correlate the different API operations with their UI equivalent counterparts.

Example: Log record before obfuscation

Imagine you have the following log record:

{

"message": "The credit card number 4321-5678-9876-2345 belongs to user user@email.com (born on 01/02/2003) with SSN 123-12-1234",

"creditCardNumber": "4321-5678-9876-2345",

"ssn": "123-12-1234",

"department": "sales",

"serviceName": "loginService"

}

This log record contains several sensitive data. Ideally, you would like your log to end up looking like this:

{

"message": "The credit card number 9aa9bc1528859aee1b1df75795f1ebd54beb2f0d26c8a1d4580a71a07189cdd5 belongs to user user@email.com (born on XXXXXXXXXX) with SSN 30e6897f76dc102e32ee1d781c43417d259e586eac15c963d75ab8b5187769da",

"creditCardNumber": "9aa9bc1528859aee1b1df75795f1ebd54beb2f0d26c8a1d4580a71a07189cdd5",

"ssn": "30e6897f76dc102e32ee1d781c43417d259e586eac15c963d75ab8b5187769da",

"department": "sales",

"serviceName": "loginService"

}

Example: Basic process

Here is the basic process you would use to obfuscate the sensitive data in this example.

You decide you want to apply the following obfuscation actions to all the logs coming from that service:

  • HASH the credit card number present in the message and creditCardNumber attributes.
  • MASK the birth date present in the message attribute.
  • HASH the Social Security number present in the message and ssn attributes.

The first thing you need to do is to define some obfuscation expressions that allow you to capture this sensitive information.

Tip

The examples below show regular expressions you'd use directly in the UI. Later in this document, we discuss how you could use escaped versions of these regular expressions for NerdGraph.

Obfuscation expression

Definition

Credit card number

We need to capture 4 groups of 4 digits separated by hyphens:

{

"name": "Credit Card Number",

"regex": "((?:(?:4\d{3})|(?:5[1-5]\d{2})|6(?:011|5[0-9]{2}))(?:-?|\040?)(?:\d{4}(?:-?|\040?)){3}|(?:3[4,7]\d{2})(?:-?|\040?)\d{6}(?:-?|\040?)\d{5})"

}

Social Security number

We need to capture 3 groups of 3, 2, and 4 digits separated by hyphens:

{

"name": "Social Security Number",

"regex": "(\d{3}-\d{2}-\d{4})"

}

Born date (loginService specific)

In this example, the born date is part of the Login service. We define the portion to obfuscate based on the date information in the surrounding words "(born on 01/02/2003)":

{

"name": "Born date - loginService specific",

"regex": "born on (.*)\)"

}

Each obfuscation expression defines how to capture some sensitive information out of a string (using a regex) and associates it with some friendly name so that you can easily identify it later.

Obfuscation expressions can be reusable; they are totally agnostic to how the log attribute containing the sensitive data is named. For instance, the Social Security expression defined above could be applied to a log attribute named ssn, socialSecurityNumber, or socSecNum.

You can also create non-reusable obfuscation expressions, like Born date (loginService specific), that are tightly coupled to the log attribute's format. For example, you could use whatever comes after born on and before.

Nested regular expression capture groups not supported

The main responsibility of this feature is to replace sensitive data with the hash or mask in an easy and performant way.If you want or need to group different matches inside a capture group, remember to use the non-capture group syntax (?:{EXPRESSION}) to avoid creating nested capture groups.For example, avoid (([A-Z]{12})|([a-z]{6})) and instead use ((?:[A-Z]{12})|((?:[a-z]{6})).

Now that we have defined how to capture our sensitive data, we need to specify which logs need to be obfuscated (the ones of the Login Service) and how (with the obfuscation actions we defined). To achieve this, we define an obfuscation rule.

{

"name": "Obfuscate Login Service Logs",

"filter": "serviceName = 'loginService' AND department = 'sales'",

"actions": [

{

"attributes": ["message", "creditCardNumber"],

"expression": { "name": "Credit Card Number" },

"method": "HASH_SHA256"

},

{

"attributes": ["message"],

"expression": { "name": "Born date - loginService specific" },

"method": "MASK"

},

{

"attributes": ["message", "ssn"],

"expression": { "name": "Social Security Number" },

"method": "HASH_SHA256"

}

]

}

This rule contains three main components:

Obfuscation rule component

Description

Name

The name helps to easily identify what the rule does. In this example, this rule defines how to obfuscate the different attributes of the logs coming from the Login Service.

Filter

The filter uses NRQL format to tell our system how to identify the target logs coming from the Login Service. This example queries for logs where serviceName = loginService and department = sales.

Actions

Finally, this rule defines the set of obfuscation actions to apply to the logs matching the filter. Each action defines:

  • Which previously created obfuscation expression to use to extract the sensitive information from each set of attributes

  • Which obfuscation method (HASH_SHA256 or MASK) to be applied to obfuscate this data

    Note that when defining obfuscation rules via NerdGraph, you will need to specify the id of the obfuscation expressions instead of their names. To make the previous example more readable, we used the obfuscation expression names instead.

As a final example, imagine we also needed to obfuscate logs coming from another service named "Checkout Service" that have an attribute serviceName = checkoutService as well as a ccn attribute that contains credit card information:

{

"message": "Order completed",

"ccn": "4321-5678-9876-2345",

"department": "sales",

"serviceName": "checkoutService"

}

To obfuscate the logs from this service, we would only have to define another obfuscation rule targeting these specific logs, and we would simply reuse the previously created Credit card number obfuscation expression:

{

"name": "Obfuscate Checkout Service Logs",

"filter": "serviceName = 'checkoutService' AND department = 'sales'",

"actions": [

{

"attributes": ["ccn"],

"expression": { "name": "Credit Card Number" },

"method": "HASH_SHA256"

}

]

}

Checklist: Steps to obfuscate logs

To obfuscate your logs:

  1. Study the shape of your logs by identifying patterns of sensitive data that appear in them. For example:

    • Do all your logs contain sensitive information? Or can you be more specific (only the logs from service A or region B)?
    • What sensitive information do they contain: credit card numbers, driver's license numbers, national IDs, biometrics, other values?
  2. Create obfuscation expressions to identify how to extract sensitive data.

  3. Define obfuscation rules for each set of logs:

    • Define how you will capture them using NRQL.
    • Define which obfuscation actions need to be applied to each of them. Ask yourself: Will I need to query my logs using this sensitive information later (consider using HASH), or do I need to remove this information entirely from my logs (consider using MASK)?

Tip

The Logs obfuscation UI includes a Hashing tool so that you can find a hash from a known value and copy it for use with other expressions and rules.

CPU limits

Obfuscation has per-minute CPU limits. If an account hits these resource limits, logs won't be obfuscated as expected. To check your CPU limits, go to your system Limits page in the Data management UI.

If you exceed the obfuscation per-minute CPU limits and logs cannot be obfuscated or hashed, the attribute the obfuscation rule was applied to will be dropped and replaced with text indicating why the attribute was dropped. For example, if the obfuscation rule is applied to the message field, and the CPU per-minute limit is reached, the resulting log will look like this:

{

...

"message": "<OBFUSCATION> The account is over its obfuscation per-minute limit, attribute dropped",

...

}

This is to prevent PII or other sensitive data from being ingested inadvertently.

In addition, the following `NrIntegrationError' will be logged to the account:

{

"category": "RateLimit",

"level": "error",

"limitName": "Log API obfuscation per account per minute",

"message": "You’ve exceeded our limit of per-account obfuscation time per-minute for the Log ingestion pipeline. Please reduce your usage or contact New Relic support.",

"name": "ObfuscationTimeLimitReached",

"newRelicFeature": "Logs",

"rateLimitType": "ObfuscationTimePerMinute",

"timestamp": 1678819264283

}

To evaluate how well your obfuscation rules are working and see which ones are being skipped, go to Logs Obfuscation > Health. Obfuscation rules are CPU intensive, so these charts can help you decide which rules are most impacted by any resource limitations.

Obfuscation expressions

You can create, read, update, or delete obfuscation expressions by using the New Relic UI or by using NerdGraph, our GraphQL Explorer.

Use either of these options to create an obfuscation expression:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Click Create regex.

  3. Enter a name for your new obfuscation rule, as well as a regular expression matching the sensitive data you want to capture. Use RE2 syntax.

    The following example shows a basic obfuscation expression that will match credit card numbers:

Using NerdGraph:

Use the logConfigurationsCreateObfuscationExpression mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

Important

You must escape regular expressions when using them in NerdGraph. For example: ((?:(?:4\\d{3})|(?:5[1-5]\\d{2})|6(?:011|5[0-9]{2}))(?:-?|\\040?)(?:\\d{4}(?:-?|\\040?)){3}|(?:3[4,7]\\d{2})(?:-?|\\040?)\\d{6}(?:-?|\\040?)\\d{5})

Use either of these options to query an obfuscation expression:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.
  2. Select the Expressions tab to view all the available obfuscation expressions and their definitions.

Using NerdGraph:

Use the obfuscationExpressions fetcher under actor.account.logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

Use either of these options to update an obfuscation expression:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Select the Expressions tab.

  3. Click the ellipsis icon ... at the right side of the obfuscation expression you want to edit, and click Edit.

  4. Modify fields as needed, and click Update.

Using NerdGraph:

Use the logConfigurationsUpdateObfuscationExpression mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

Important

You must escape regular expressions when using them in NerdGraph. For example: ((?:(?:4\\d{3})|(?:5[1-5]\\d{2})|6(?:011|5[0-9]{2}))(?:-?|\\040?)(?:\\d{4}(?:-?|\\040?)){3}|(?:3[4,7]\\d{2})(?:-?|\\040?)\\d{6}(?:-?|\\040?)\\d{5})

You do not need to specify all the fields of an obfuscation expression when updating it, only the id (mandatory) and the fields that you wish to modify.

Important

You will not be able to delete an obfuscation expression if it is currently being used by an obfuscation rule.

Use either of these options to delete an obfuscation expression:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Select the Expressions tab.

  3. Click the ellipsis icon ... at the right side of the obfuscation expression you want to delete, and click Delete.

  4. Confirm you want to delete the expression by clicking Delete.

Using NerdGraph:

Use the logConfigurationsDeleteObfuscationExpression mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

The mutation will return a snapshot of the expression before being deleted.

Sample expressions

Below, we've provided some sample regex expressions to obfuscate some of the most common sensitive data types. Obfuscation expressions must be created for each New Relic account where those expressions will be in use.

Tip

The following examples are regular expressions you could use in the UI. To use these in GraphQL, you'd need to escape them as shown in this example.

Expression:

(\d{3}[-\s\.]?\d{2}[-\s\.]?\d{4})

Expression:

((?:(?:4\d{3})|(?:5[1-5]\d{2})|6(?:011|5[0-9]{2}))(?:-?|\040?)(?:\d{4}(?:-?|\040?)){3}|(?:3[4,7]\d{2})(?:-?|\040?)\d{6}(?:-?|\040?)\d{5})

Expression:

((?:\d{2})?\d\d(?:\\)?(?:\/)?\d\d(?:\\)?(?:\/)?\d{2}(?:\d{2})?)

Expression:

([a-zA-Z0-9!#$'*+?^_`{|}~.-]+(?:@|%40)(?:[a-zA-Z0-9-]+\.)+[a-zA-Z0-9-]+)

Expression:

^([0-9]{1,3})\.([0-9]{1,3})\.([0-9]{1,3})\.([0-9]{1,3})$

Expression:

/\d{1,}(\s{1}\w{1,})(\s{1}?\w{1,})/g

Expression:

(^[\+]?[1]?[\W]?[(]?[0-9]{3}[)]?[-\s\.]?[0-9]{3}[-\s\.]?[0-9]{4})

Expression:

([a-zA-Z]?\d?\d{5,8})

Expression:

([a-zA-Z]{2}[-\s]?\d{2}[-\s]?\d{2}[-\s]?\d{2}[-\s]?[a-dA-D])

Expression:

([a-zA-Z]?[-\s]?\d{7,8}[-\s]?[a-zA-Z])

Expression:

^([a-zA-Z]){5}([0-9]){4}([a-zA-Z]){1}?$

Expression:

^([2-9]{1}[0-9]{3}\s\d{4}\s\d{4})$

Expression:

(\d{3}[-\s\.]?\d{3}[-\s\.]?\d{3})

Expression:

(\d{10})

Expression:

(d{4}\sd{4}\sd{4})

Obfuscation rules

You can create, read, update, or delete obfuscation rules by using the New Relic UI or by using NerdGraph, our GraphQL Explorer.

Use either of these options to create an obfuscation rule:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Click Create obfuscation rule.

  3. Enter a name for your new obfuscation rule, as well as a matching criteria (in NRQL format) to capture the target set of logs you want to obfuscate.

  4. Add a new actions (the first one is added automatically) to specify the obfuscation expression (regex) to capture each set of attributes, as well as whether to MASK or HASH them.

    • Multiple attributes can be specified comma-separated.
    • MASK will replace all matching characters with Xes. If you use MASK, you will not be able to query for a particular obfuscated value later.
    • HASH will replace sensitive data with the SHA-256 hash value. If you use HASH, you will be able to query them using our hashing tool, provided you know its cleartext value.

    Your rule should look something like this:

  5. Click Create rule to create and activate your obfuscation rule.

Using NerdGraph:

Use the logConfigurationsCreateObfuscationRule mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

Important

You must specify the obfuscation expressionId in order to link it to a given obfuscation action. To retrieve this id, you can query the obfuscationRules.

Use either of these options to query an obfuscation rule:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Select the Rules tab (default) to view all the available obfuscation rules and their definitions.

Using NerdGraph:

Use the obfuscationRules fetcher under actor.account.logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql

Use either of these options to update an obfuscation rule:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Select the Rules tab (default).

  3. Click the ellipsis icon ... at the right side of the obfuscation rule you want to edit, and click Edit.

  4. Modify the fields as needed, and click Update rule.

Using NerdGraph:

Use the logConfigurationsUpdateObfuscationRule mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

Important

You must specify the obfuscation expressionId in order to link it to a given obfuscation action. To retrieve this id, you can use the obfuscationRules, as described in [query the obfuscationRules]](#rules-read).

You do not need to specify all the fields of an obfuscation rule when updating it, only the id (mandatory) and the fields that you wish to modify. Here is an example to only update the name.

Use either of these options to delete an obfuscation rule:

Using the logs UI:

  1. Go to one.newrelic.com > All capabilities > Logs and from the left nav, select Obfuscation.

  2. Select the Rules tab (default).

  3. Click the ellipsis icon ... at the right side of the obfuscation rule you want to delete, and click Delete.

  4. Confirm you want to delete the expression by clicking Delete.

Using NerdGraph:

Use the logConfigurationsDeleteObfuscationRule mutation under logConfigurations. Refer to the populated example in GraphiQL as well as the related documentation in api.newrelic.com/graphiql.

The mutation will return a snapshot of the rule before being deleted.

Log obfuscation: Hash or mask sensitive data in your logs (2024)

FAQs

Log obfuscation: Hash or mask sensitive data in your logs? ›

If you use MASK , you will not be able to query for a particular obfuscated value later. HASH will replace sensitive data with the SHA-256 hash value. If you use HASH , you will be able to query them using our hashing tool, provided you know its cleartext value.

What are the sensitive information in logs? ›

Logs act as significant repositories of sensitive data. When fall into the wrong hands, they can pose substantial security risks. These logs often contain personally identifiable information (PII), financial details, authentication credentials, and other sensitive data.

What is the difference between data masking and data obfuscation? ›

In short, there are two major differences between data masking and data obfuscation methods like encryption or tokenization: Masked out data is still usable in its obfuscated form. Once data is masked, the original values cannot be recovered.

What is log masking? ›

Masking lets you hide fields completely or partially in log messages, for example, fields such as password . Note: Log processing rules are applied only to the logs that are ingested after you create and enable these rules.

How to mask data in logs in Spring Boot? ›

How to mask sensitive data in logs
  1. Create the regex patterns representing the sensitive data in question within the logback. xml configuration file — this is the blueprint for what will get masked.
  2. Create a Layout class that comprehends these regex patterns and diligently applies them to the log messages.
May 2, 2024

What are examples of sensitive data? ›

Answer
  • personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs;
  • trade-union membership;
  • genetic data, biometric data processed solely to identify a human being;
  • health-related data;
  • data concerning a person's sex life or sexual orientation.

What are three types of sensitive information? ›

What Are Some Types of Sensitive Information? Sensitive information typically falls into three categories: sensitive PII, business information, and classified information.

What is the difference between hash and obfuscation? ›

Hashing is a one-way algorithm; cannot be reversed. Obfuscation is similar to encryption but doesn't require any "secret" to understand (ROT13 is one example) Encryption is reversible but a "secret" is required to do so.

What is an example masking data? ›

Characters are reorganized in random order, replacing the original content. For example, an ID number such as 76498 in a production database, could be replaced by 84967 in a test database. This method is very simple to implement, but can only be applied to some types of data, and is less secure.

What is masking sensitive data? ›

Data masking is the process of hiding data by modifying its original letters and numbers. Due to regulatory and privacy requirements, organizations must protect the sensitive data they collect about their customers and operations.

What is hash masking? ›

The hash data masking policy generates an integer hash value that is based on the value of the source column that you specified. The output column can be different from the source column, but the input link must contain a column with the same name as the output column.

What is log obfuscation? ›

What is log obfuscation? Our log management service automatically masks number patterns that we identify as likely being sensitive items, such as credit card or Social Security numbers.

Is data masking same as encryption? ›

Masking is clearly more secure than encryption but it renders data useless. Masked data has no value for anyone who intercepts or steals it. This information cannot be used for anything other than to run tests on software in a development state. Hackers don't want or care about masked development data.

How to mask sensitive data in Java Spring Boot? ›

Custom Log Appender or Layout: You can create a custom log appender or layout that processes log messages before they are written to the log files. Within this custom logic, you can mask or obfuscate sensitive information. You would then configure this custom layout in your logback. xml or logback-spring.

How to mask sensitive JSON data in Java? ›

Using JsonMaskingConfig allows customizing the masking behaviour of types, keys or JSONPath or mix keys and JSON paths. After creating the JsonMasker instance, it can be used to mask a JSON as following: String maskedJson = jsonMasker. mask(json);

How to improve logging in Spring Boot? ›

The primary method for configuring Logback in Spring Boot is through the logback-spring. xml file, which should be placed in the src/main/resources directory. This XML file is where you define loggers, appenders, and layouts. This configuration sets up a basic console appender.

What is log sensitivity? ›

Log sensitivity filters work by allowing developers to pass structured objects into the logging framework, and for the logging framework to decide how to render that content appropriately.

What does sensitive information include? ›

Sensitive information is personal information that includes information or an opinion about an individual's: racial or ethnic origin. political opinions or associations. religious or philosophical beliefs.

What information is contained in security logs? ›

Security logs contain events related to security, such as login attempts, object access, and file deletion. Administrators determine which events to log, in accordance with their audit policy.

What information is stored in the log file? ›

A log file is a computer-generated data file that contains information about usage patterns, activities and operations within an operating system, application, server or another device. Log files show whether resources are performing properly and optimally.

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