PII Data Masking: How to Minimize Your Risk and Stay Out of Trouble

July 26, 2022
Written by
Bradley Chambers's Image

Bradley is an experienced IT professional with 15+ in the industry. At Cribl, he focuses ... Read Moreon building content that shows IT and security professionals how Cribl unlocks the value of all their observability data. Read Less

Categories: Learn

Consumers expect their personal information to be safe in your hands as they use your apps, services, and stores. Even in-person retailers collect customer data for loyalty programs, shopping history, and more. This collected information often includes personally identifiable information (PII) such as social security numbers, phone numbers, and credit card numbers. Protecting this sensitive data is not just a good business practice but a critical necessity. Let’s look at the important of PII data masking.

Data masking is a crucial yet often under-discussed data security technique that is vital in safeguarding PII. By transforming original data into masked data, data masking ensures that sensitive information is rendered unusable to unauthorized users while remaining useful for legitimate purposes. Industries that handle large volumes of PII, such as finance, healthcare, and retail, must prioritize data masking to protect their customers’ personal data.

In addition to consumers, regulators, and auditors require strict adherence to data protection regulations to ensure the security and privacy of personal data. Compliance with laws such as the General Data Protection Regulation (GDPR) is mandatory, and failing to protect PII can result in severe penalties. Data breaches can be extremely costly, not only financially but also in terms of reputational damage. The GDPR and other data protection regulations are forcing companies across all sectors to take data security seriously, emphasizing the importance of robust data protection measures.

While we’re at it, let’s add investors, board members, and partners to the list of people who expect all customer data to be secure at all times. Ensuring data integrity and protecting sensitive information involves robust data management practices. One crucial aspect of data governance is implementing effective data security standards. Data breaches can have disastrous consequences, both financially and reputationally, making it essential to prioritize data security.

In this blog, we’re going to look at why PII data masking needs to be at the center of your customer privacy stance. Data masking techniques transform original data into masked data, rendering it useless to unauthorized users while preserving its utility for legitimate purposes. PII masking is a vital tool in protecting sensitive information and maintaining compliance with data protection regulations.

By focusing on PII data masking, organizations can safeguard personal data and ensure they meet the expectations of all stakeholders. This approach not only helps in preventing data breaches but also enhances overall data governance and data management practices.

How Exactly Does Data Masking Protect PII?

Data masking is a powerful data protection technique designed to safeguard personally identifiable information (PII) by transforming sensitive data into an unreadable format for unauthorized users. Replacing original data with masked data ensures that while the data retains its format and utility for testing, analysis, or other legitimate purposes, it cannot be exploited for malicious activities. This process is essential in protecting sensitive information from potential breaches and unauthorized access.

There are several effective techniques used in data masking to protect PII:

  • Substitution: This method replaces sensitive data with realistic but fictitious data. For example, real names may be substituted with randomly generated names.
  • Shuffling: This technique rearranges the data within a column in a random order, making it difficult to trace back to the original values.
  • Encryption: Encryption transforms data into a coded format that can only be accessed or decrypted by those with the appropriate key.
  • Masking Out: This involves replacing part of the data with characters such as asterisks or Xs. For example, a social security number may be shown as XXX-XX-1234.
  • Null Values: This technique replaces the data with null values, effectively removing any identifiable information.

Each of these data masking techniques helps ensure that sensitive data, including PII data, remains secure while still allowing businesses to use the information for necessary functions like development and analysis. Implementing data masking techniques can help organizations reduce the risk of data breaches and comply with data protection regulations such as the General Data Protection Regulation (GDPR). This approach helps maintain the trust of customers, investors, board members, and partners by ensuring that personal data is protected under stringent data security standards.

By focusing on PII data masking, businesses can improve their overall data governance and data management practices, ultimately enhancing data integrity and protecting sensitive information.

When Should You Use PII Masking?

PII data masking is a critical technique that should be applied across various scenarios and industries to protect sensitive personal data from unauthorized access. Here are some key scenarios and examples of industries where PII masking is essential:

Scenarios for PII Masking

  1. Development and Testing Environments: Using real customer data when creating and testing new applications can pose significant risks. PII masking ensures that sensitive information is protected while allowing developers and testers to work with data that mimics the original.
  2. Data Analytics: Analysts often need access to large datasets to identify trends and insights. PII masking allows them to use this data without exposing sensitive information, ensuring that personal data remains protected.
  3. Third-Party Sharing: When sharing data with third-party vendors or partners for processing or analysis, PII masking ensures that the shared data does not include identifiable personal information, reducing the risk of data breaches.
  4. Training and Support: Organizations often use real data for training customer support staff or machine learning models. PII masking protects the data while still providing realistic scenarios for training purposes.

Industries Where PII Data Masking is Applied

  • Finance: Financial institutions handle a vast amount of PII, including social security numbers, credit card numbers, and account details. PII masking is crucial in protecting this sensitive data during transactions, fraud analysis, and when sharing data with regulatory bodies.

Example: A bank developing a new fraud detection system uses masked PII data in its testing environment to ensure customer information is secure.

  • Healthcare: Healthcare providers manage extensive personal data, including medical records, insurance information, and social security numbers. PII masking helps in maintaining patient confidentiality while allowing the use of data for research and operational purposes.Example: A hospital conducting a study on patient outcomes masks patient data before sharing it with research partners to comply with data protection regulations.
  • Retail: Retailers collect customer data for loyalty programs, purchase history, and marketing purposes. PII masking is essential to protect this information when analyzing customer behavior or sharing data with marketing agencies.Example: A retailer analyzing shopping trends masks customer PII to prevent unauthorized access while enabling data-driven decision-making.
  • Tech: Tech companies often handle user data, including email addresses, phone numbers, and login credentials. PII masking is used to protect user data during software development, data analysis, and when providing support services.Example: A tech company developing a new feature for its app uses masked user data to ensure privacy during the development and testing phases.

Challenges with Protecting PII Data

Until somebody gets hit with a nice big fine for millions of dollars for how they manage customer data. In reality, it’s a significant challenge for companies trying to keep up with all the new rules for properly storing and processing PII. It can feel like a game of musical chairs because of all the chaos and moving parts. You’ll want to make sure you have your ass in a seat or at least look like you know how to play the game when the music stops and an audit comes your way.

If you’re looking at it from a regulator’s point of view, the game looks less like musical chairs and more like Hungry Hungry Hippos with all of the penalty money being gobbled up. Compared to the less than $200 million in fines handed out in 2020, there were over $1.2 billion in 2021. If the trend continues, 2022 could be a tough year for many companies, and one of them could be yours.

In addition to the fines that get handed out like candy, organizations also face a reputational risk that can cause severe headaches. Imagine your company’s name in the headlines on the news for weeks, talking about how you don’t care enough about your customers to keep their data safe and following your story as your executives get dragged through all kinds of legal proceedings. Sounds like fun, right? Let’s look at avoiding a GDPR fine using a data masking solution.

Mask PII Data with Cribl Stream

With Cribl Stream as the middleman between your data collection and data storage tools, you can send each piece of data up and down as many modifications and storage paths as you want without being subject to a roll of the dice. Like chutes and ladders, Stream works with a series of pipelines and routes that process events in your system. You create the functions that determine which routes the data takes, all within Stream’s user-friendly interface.

Stream allows you to create copies of events to store the original within your security team’s infrastructure or in a low-cost observability lake, and depersonalize any copies you want to share with relevant parts of your organization. We also make it easy to identify data that you may not be masking but should. This way, you can make sure you get the most value out of your data without incurring any of the risks associated with GDPR. You’ll never ingest data that you’ll regret having later. Our docs section shows you exactly how to implement it, and we’ve also included a video below showing how it works.

How to Ensure Data is Accessible for Audits and Investigations?

Redacting PII and making sure that data ends up in proper storage is super important, but it’s also crucial for you to be able to recall the data if necessary – and all the better if recalling data is quick and painless. As part of GDPR, enterprises must be compliant, and they need to be able to demonstrate that compliance to auditors. The more quickly you can get this done, the faster you and your team can focus on value creation.

You can use Stream to send copies of data to low-cost storage, saving you the headache of trying to guess ahead of time which data to keep in “hot” or “warm” storage in the case of an unexpected investigation. By not overwhelming your SIEM and UEBA tools with extra data, you can keep them working as efficiently as possible. Then, use Stream to recall and replay any data you need straight to your analytics tools.

Stream’s replay feature lets you jump into critical logs, metrics, and traces as far back in time as you want so that you and your new auditor friends can see whatever they need to without issue or delay. What’s more, you have the option of replaying only the parts that pertain to a security incident if the time comes.

Prioritize Data Compliance

With the implementation of the General Data Protection Regulation (GDPR) and the constant creation of new data privacy laws worldwide, protecting personal data from unauthorized or unlawful processing has never been more critical. Ensuring data compliance is not just about avoiding hefty fines and legal repercussions; it is also about maintaining the trust and confidence of your customers. They rely on you to safeguard their sensitive information, including personally identifiable information (PII) such as social security numbers, phone numbers, and credit card numbers.

Using advanced tools and techniques like Stream, you can stay ahead of regulators and protect your data from potential breaches and cyber threats. Stream helps you implement robust data protection measures, including PII data masking, data governance practices, and compliance with data protection regulations. By masking PII data, you can transform original data into a secure, masked format, rendering it useless to unauthorized users while preserving its utility for legitimate purposes.

Data breaches can be devastating, leading to financial losses, legal consequences, and damage to your reputation. Staying ahead of hackers and being prepared to defend against cyber attacks is essential. Stream provides the necessary tools to enhance your data security standards, ensuring that sensitive data is always protected. By implementing effective data masking techniques and adhering to data management best practices, you can reduce the risk of data breaches and maintain the integrity of your data.

Moreover, prioritizing data compliance means being proactive rather than reactive. It involves continuously monitoring and updating your data protection strategies to align with evolving regulations and emerging threats. This proactive approach ensures that you are always ready to respond to any regulatory changes or security challenges that may arise.

Your customers’ trust depends on your ability to protect their personal data. By prioritizing data compliance and using tools like Stream to safeguard sensitive information, you demonstrate your commitment to data security and privacy. This helps you comply with regulations such as GDPR and builds a strong foundation of trust with your customers, investors, board members, and partners.


Cribl, the Data Engine for IT and Security, empowers organizations to transform their data strategy. Customers use Cribl’s suite of products to collect, process, route, and analyze all IT and security data, delivering the flexibility, choice, and control required to adapt to their ever-changing needs.

We offer free training, certifications, and a free tier across our products. Our community Slack features Cribl engineers, partners, and customers who can answer your questions as you get started and continue to build and evolve. We also offer a variety of hands-on Sandboxes for those interested in how companies globally leverage our products for their data challenges.

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