The Evolution of Data Security: From Traditional DLP to DSPM

By Hari Prasad Mariswamy - Director, Product Management

February 20, 2025 5 Minute Read

Overview

Data security has always been a paramount concern for enterprises. However, the rapid digitization of businesses and the increasing complexity of data environments have made traditional security measures inadequate. To address these challenges, a new approach to data security has emerged: Data Security Posture Management (DSPM).

What is DSPM?

DSPM is a comprehensive approach to managing and securing an organization’s data assets. It involves gaining visibility into data, assessing its security posture, and implementing measures to protect it from threats. By automating data security workflows, DSPM enables organizations to proactively identify and mitigate risks, ensuring that data is always protected.

Why is DSPM important?

The importance of DSPM can be underscored by its ability to address the following critical use cases:

1. Data Discovery and Classification: DSPM solutions continuously scan for data across environments to create a comprehensive inventory, tagging and classifying data based on sensitivity, risk level, and compliance requirements. This visibility ensures that organizations know precisely what data they hold and where it resides.
2. Access Governance: Understanding who has access to sensitive data is a cornerstone of DSPM. By analyzing permissions and monitoring access patterns, DSPM helps organizations enforce least-privilege access policies and ensures compliance with data protection regulations.
3. Risk Analysis and Security Posture Assessment: DSPM continuously evaluates security posture by analyzing data vulnerabilities, misconfigurations, and access anomalies. This ongoing assessment provides real-time insight into risks, allowing organizations to prioritize and address vulnerabilities as they arise.
4. Automated Remediation and Policy Enforcement: DSPM solutions enable automated policy enforcement to promptly address security and compliance issues. Whether by adjusting access controls or encrypting sensitive data, automated workflows ensure that risks are addressed efficiently without requiring constant manual oversight.

Traditional DLP vs. DSPM

Traditional DLP solutions focus primarily on preventing data exfiltration by monitoring and controlling data movement across endpoints, networks, cloud applications, and emails. DLP enforces predefined policies to block unauthorized data transfers, ensuring sensitive information does not leave an organization’s controlled environment. However, DLP operates based on known risks and predefined rules, often requiring significant administrative effort to classify data and manage policies effectively.

DSPM, on the other hand, takes a more proactive and comprehensive approach to data security. Instead of just preventing data loss, DSPM provides deep visibility into where sensitive data resides, who has access to it, and how it is being used across multi-cloud and on-prem environments. It identifies misconfigurations, security gaps, and compliance risks in real time, enabling organizations to take corrective actions before a data breach occurs. While DLP focuses on data movement and policy enforcement, DSPM emphasizes data discovery, risk assessment, and security posture enhancement, making it a critical tool for modern cloud-first enterprises.

The Role of SSE in DSPM

Integrating DSPM with Security Service Edge (SSE) Solutions

Recent DSPM acquisitions by major SSE players suggest that organizations expect to see DSPM as part of a comprehensive security offering. As more vendors integrate DSPM into their SSE suites, a fully combined SSE-DSPM solution becomes more appealing for companies looking to consolidate and streamline their security operations.

SSE, which integrates Secure Web Gateway (SWG), Cloud Access Security Broker (CASB), Zero Trust Network Access (ZTNA), and other advanced security capabilities, acts as the enforcement engine that strengthens DSPM outcomes by providing:

• Data Visibility & Protection Across All Channels: SSE ensures that sensitive data is continuously monitored and protected whether it resides in SaaS, IaaS, endpoints, or private applications. CASB and SWG deliver inline security controls to prevent unauthorized data exposure, while on-demand scanning detects risks in cloud storage and collaboration tools.
• Proactive Risk Mitigation with User & Entity Behavior Analytics (UEBA): DSPM identifies potential data exposure risks, but UEBA in SSE takes it a step further by detecting anomalies in user behavior. If a user suddenly downloads an unusually large volume of sensitive data or accesses restricted files, risk-based policies can trigger alerts or automated responses.
• Continuous Compliance & Security Posture Management (CSPM): DSPM relies on CSPM to monitor cloud misconfigurations and policy violations, ensuring that sensitive data is not left exposed due to improper access controls or misconfigured storage buckets. SSE helps enforce remediation measures in real time, ensuring continuous compliance with regulatory frameworks.
• Zero Trust Access Controls with ZTNA: ZTNA ensures that access to critical data is granted based on identity, device posture, and contextual risk. DSPM helps identify overexposed data, while ZTNA enforces least-privilege access, reducing the risk of unauthorized access or insider threats.
• Activity Monitoring & Data Risk Profiling: DSPM’s effectiveness is enhanced when paired with continuous activity monitoring and user risk profiling from SSE. By correlating data access patterns, application usage, and user risk scores, organizations gain a holistic view of security posture and can enforce adaptive policies to prevent potential data breaches.

Emerging Role of AI in DSPM: AI Security Posture Management (AI-SPM)

As enterprises increasingly incorporate AI services, an emerging sub-field, AI Security Posture Management (AI-SPM) has evolved to address unique risks posed by AI. AI-SPM focuses on visibility and control over how enterprise data interacts with AI models, preventing sensitive information from being inadvertently processed by unvetted or unprotected AI services. AI-SPM offers:

• Visibility of AI Interactions: AI-SPM monitors data usage across various AI services, ensuring compliance with data security policies.
• Data Risk Analysis in AI Workflows: By assessing how data is handled in AI workflows, AI-SPM identifies risks such as unauthorized sharing or storage, ensuring sensitive information remains protected.

Why SSE Providers are Well-Positioned to Extend DSPM Capabilities

While DSPM identifies and assesses data risks, SSE acts as the enforcement layer that prevents misuse, enforces policies, and enables secure access. Together, they provide a comprehensive approach to protecting sensitive data across hybrid and multi-cloud environments, ensuring that organizations stay ahead of evolving security threats while maintaining regulatory compliance.

By leveraging SSE capabilities like SWG, CASB, ZTNA, CSPM, UEBA, and risk-based monitoring, organizations can turn DSPM insights into actionable security controls, ensuring that sensitive data remains protected no matter where it resides or how it is accessed.

These SSE-backed features empower organizations to extend DSPM beyond basic data monitoring, allowing for more in-depth data protection and risk management.

Conclusion

DSPM is a critical component of a comprehensive data security strategy. By understanding the core principles of DSPM and leveraging advanced technologies like SSE and AI-SPM, organizations can effectively protect their valuable data assets. As a leading SSE solution provider, Skyhigh Security is committed to helping customers embark on their DSPM journey and achieve a robust data security posture.

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