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JSonar Introduces AI-Driven Sensitive Data Management and Database Security Threat Prevention

Provides tighter Splunk integration and expands database sources covered to over 60 databases.

Note: TDWI’s editors carefully choose press releases related to the data and analytics industry. We have edited and/or condensed this release to highlight key features but make no claims as to the accuracy of the author's statements.

Modern database security provider jSonar has announced major updates to its database security and compliance platform with the launch of jSonar 4.2. JSonar has extended its expertise beyond data monitoring, auditing, and security by adding an AI-powered “Learn from Me” sensitive data management (SDM) system to help users more effectively classify and manage sensitive data and a library of customizable playbooks to help users take preventive action and automate the response to security events.

The patent-pending “Learn from Me” system utilizes AI to build an institutional knowledge base that continuously reduces the work required for labeling, tagging, and communicating where your sensitive data lives by automatically incorporating historical actions into the decision process. This enables organizations to significantly reduce manual efforts associated with recurring scans.

The second major innovation in this release is the introduction of prebuilt database security playbooks. The playbooks are collections of procedures that users can run in response to various events, either as part of an automated process or when human operations trigger orchestrated processes. They enable users to respond to outliers, anomalies, and threats, as well as automate communication about these events to the proper team members. Prebuilt playbooks reduce the time required to write code into tools for new detection and response procedures. Unlike traditional SOAR solutions, the jSonar approach is specifically focused on integrations and actions critical to database risk management.

Additional significant updates:

  • Splunk Application Reduces Indexing Costs by 95 Percent. Over time, the ineffectiveness of native logging and data activity monitoring tools has forced Splunk to act as the primary repository of raw data and driven up indexing costs. JSonar customers that use Splunk needed a way to capture and retain all raw data but publish only the intelligent, actionable data that has value to Splunk. JSonar now serves as a pre-processor that reduces Splunk indexing costs by 95 percent, extracts intelligence from the raw data, and pushes the enriched data to the SOC team. jSonar presents security alerts to the SOC team in an easy to understand format, and if users need to dig deeper, they still have seamless access to all the raw data in the system. Security analysts can then triage the issue and run a jSonar playbook, all without leaving the Splunk UI.
  • Increased Data Sources. JSonar has expanded the platform for database security to cover more sources with native interfacing with over 60 databases now supported.

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