Next DLP Debuts Security Data Flow, Offering Data Lineage Tracking for SaaS Apps

Next DLP, a leader in insider risk and data protection, is debuting Secure Data Flow, a new feature of the Reveal Platform—a flexible, cloud-native, AI- and ML-powered solution built for today's threat landscape—that illuminates the specificities of data origins, movements, and modifications. This latest capability aims to replace legacy data protection technologies—which only effectively apply to a small range of text-based data types—to bring customers a comprehensive, false-positive-free security solution.

The launch of Secure Data Flow targets the limitations and complexities of legacy Data Loss Prevention (DLP), enabling enterprises to go beyond simple pattern matching, regular expressions, user-applied tags, and fingerprinting. Secure Data Flow delivers origin-based data identification, manipulation detection, and data egress controls, helping security analysts more easily—and more effectively—tackle data theft and misuse, according to Next DLP.

“Secure Data Flow is a novel approach to data protection and insider risk management,” said Ken Buckler, research director at Enterprise Management Associates. “It not only boosts detection and protection capabilities but also streamlines the overall data management process, enhancing the fidelity of data sensitivity recognition and minimizing endpoint content inspection costs. This advancement is particularly vital given the limitations and inefficiencies of traditional legacy DLP solutions, providing a much-needed capability to more effectively safeguard sensitive data in today’s diverse technological environments."

Both powerful and easy to use, Secure Data Flow introduces the following capabilities:

  • Comprehensive data tracking that protects the flow of critical data from any SaaS application, including Salesforce, Workday, SAP, and GitHub
  • Enhanced data protection by leveraging data origin and sensitive data identification, safeguarding intellectual property and sensitive data from incidental loss and malicious theft
  • Insightful investigations with contextual information regarding data origin, manipulation, and lineage, increasing the accuracy of data security risks and incidents

"In current IT environments, Intellectual Property (IP) commonly resides in an organization’s SaaS applications and cloud data stores. The risk here is that high-impact data in these locations cannot be easily identified based on its content,” said John Stringer, head of product at Next DLP. “With Secure Data Flow, we help organizations protect their IP by capturing the data’s origin and using that information to track data movement and prevent data theft.”

To learn more about Next DLP, please visit