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Does your DLP solution protect data using a Zero Trust model?

An essential component of any organization’s data loss prevention process is the implementation of a robust Data Loss Prevention (DLP) strategy. One component of an effective DLP strategy is the application of a DLP solution that can scan areas where data resides, analyzing content and monitoring channels and endpoints to ensure that sensitive data is not shared outside of the corporate network.

If you have already implemented a DLP solution as part of your DLP strategy, you may assume that it will perfectly align with your organization’s compliance with the Zero Trust framework. After all, shouldn’t a DLP solution be secure by default?

Unfortunately, many of the assumptions made about DLP solutions are false. Here are some common misconceptions about DLP solutions, why DLP solutions alone aren’t enough to ensure an organization’s compliance with Zero Trust, and how to ensure that your overall DLP strategy better aligns with a Zero Trust model.

DLP isn’t secure by default

Traditional DLP solutions alone fail to adhere to a Zero Trust framework, as data is not secured by default. The Zero Trust framework requires that users are never automatically trusted with access to data and are not given individual control over data. They must only be able to work with data that is controlled.

DLP, by contrast, assumes that users accessing data are trusted. So instead of securing the data at its source, DLP solutions rely on rules that will stop, allow, or encrypt the transfer of this data outside of a specific environment. These rules must be updated continuously as users find new and creative ways to access sensitive data. This can create huge gaps and oversights in security over time.

Implementing a true Zero Trust DLP strategy requires the application of extremely precise controls that go beyond username and password. These controls must secure data at the source, which is extremely difficult if the data has not been properly uncovered, tagged, and classified. This leads us to the next common misconceptions.

DLP isn’t a single tool

A robust DLP strategy doesn’t consist of a single tool. Instead, effective DLP is a set of tools, processes and overall strategies designed to work together to protect your organization’s most critical and sensitive data. Most DLP solutions focus on data in motion. This means they are actively monitoring data that is currently being accessed. Few, however, have the ability to secure data at rest, a key part of applying a Zero Trust model. Ensuring complete data protection requires the addition of a data discovery tool.

By implementing an automated DLP solution with accurate data discovery, your organization can monitor and secure both data at rest and data-in-motion. A solution that facilitates the process of discovering, classifying, and remediating data across your organization will also help you adhere to numerous other compliance regulations.

DLP can be easily disabled or worked around

Are your employees trying to disable your DLP solution? A surprising number of them probably are, based on Google search volume for “how to disable DLP.” A Verizon 2022 Data Breach Investigation Report found that employees and other insiders are responsible for 82% of security incidents at organizations.

However, there are many common reasons that employees want to disable an organization’s DLP, and most are procedural as opposed to nefarious. Here are areas where many DLP solutions fall short:

  • Falsely identifying PII or other sensitive information in a spreadsheet or document and quarantining it, blocking a user’s ability to send non-sensitive data and causing frustration
  • Inability to effectively monitor cloud applications, letting users create and share information outside of a DLP-controlled environment
  • Cannot accurately distinguish between legitimate activity and activity with malicious intent, slowing down user productivity through the increasingly byzantine application of numerous rules

However, if a DLP solution secures at the data level, then it becomes less likely (if not impossible) for access rules to be changed at the user level. Clearly, there is a desire within organizations to change or disable DLP settings due to internal frustrations with this solution.

With accurate discovery and classification working hand-in-hand with your DLP solutions, sensitive information will be properly tagged and restrictions applied, while non-sensitive data will not be blocked, causing headaches that lead employees to turn to Google in a desperate attempt to disable DLP.

How to align a DLP solution with the Zero Trust model

As you can see, there is more to implementing a Zero Trust compliant DLP strategy than simply picking up a DLP solution off the shelf.

Before launching a new DLP solution, organizations who want their overall DLP strategy to adhere to the Zero Trust framework must first execute data discovery and classification. This is because data discovery locates all of an organization’s data across the enterprise and labels it according to predetermined categories, from “not sensitive” to “highly sensitive.” Data cannot be protected at the source without knowing what one has and where it resides.

Does your DLP solution align with a Zero Trust model?

To protect organizations from widespread data loss, Spirion’s data discovery and classification tools find structured and unstructured sensitive data of all kinds, including PII and IP, no matter where it resides. Spirion’s software integrates with many leading DLP solutions and adds these essential data loss prevention capabilities:

  • Identifies sensitive data — Searches for all sensitive and confidential information across an organization’s infrastructure, including images, databases, hosted and on-premise email applications, cloud storage, and network devices.
  • Performs data classification and continuously monitors data — Delivers highly accurate classification automatically. Additionally, because data is continuously being received and created, a successful DLP strategy will include a method of continuously monitoring the enterprise for new instances of sensitive data in real-time.
  • Remediates data — Data remediation allows organizations to reduce their sensitive data footprint by performing data encryption, shredding unneeded information, redacting bad data, or quarantining files to more secure locations.

If you have questions about how to implement a DLP strategy that adheres to the Zero Trust model, Spirion’s security experts are here to provide expert guidance.