DSPM vs Legacy Security Tools: Filling the Data Security Gap

Legacy tools like CSPM, DLP, and SIEM were designed to secure infrastructure, networks, and events but they often lack visibility into the data layer itself. Without understanding where sensitive data lives, how it flows, or who has access, these tools leave gaps that attackers can exploit. That’s why breaches still occur, even with heavy investments in multiple point solutions.

A data-centric approach, powered by DSPM, shifts the focus from just protecting infrastructure to securing the data itself. By continuously discovering sensitive data, classifying it, and correlating risks across environments, organizations gain context-driven protection. This allows them to identify toxic risk combinations and remediate issues before they lead to costly incidents.

No. DSPM is not a replacement, it’s a complement. Enterprises typically run dozens of tools, but DSPM enhances them by adding data context. For example, CSPM may flag a misconfigured cloud bucket, but DSPM shows whether that bucket actually contains PHI, PII, or financial records. This helps prioritize risks and make existing security investments more effective.

DSPM integrates with existing workflows and federated systems like ServiceNow, Jira or Slack to orchestrate remediation. It automates fixes for common risks, while complex issues are routed to the right owners with full context. This reduces time-to-remediation, avoids alert fatigue and ensures critical risks don’t slip through the cracks.

The rise of GenAI, SaaS apps, and multicloud environments has expanded the attack surface dramatically. At the same time, data breaches remain costly, with the average breach reaching nearly $5M. Security leaders recognize that traditional, siloed tools can’t keep pace, and are adopting DSPM to unify visibility, strengthen compliance, and secure AI adoption without slowing innovation.