Data breach is a dreadful thought that causes 77% of CISOs worldwide to fear for their job. The fear is justified, as the cost of data breaches grows exponentially every year, causing security leaders severe anxiety.
As CISOs ramp up their security tech stack to combat existing or emerging (AI) security threats, they often find themselves at a crossroads of security acronyms: DLP, CNAPP, and DSPM. These acronyms represent an enhanced set of new strategies designed to protect the complex data environments that security teams face today.
Read on as this blog delves deeper into the definitions and core capabilities of Data Loss Prevention (DLP), Cloud Native Application Protection Platform (CNAPP), and Data Security Posture Management (DSPM). Also, learn why a unified data security approach is an optimal solution for overcoming today’s complex environments.
The cloud-native platforms industry is worth $7.45 billion in 2025 and is estimated to hit a whopping $62.72 billion mark by 2034, growing at 26.77% CAGR. As the cloud-native market blooms, attack vectors and vulnerabilities continue to grow at an equal pace. In a cloud-native app-driven industry, Cloud Native Application Protection Platform (CNAPP) is critical in safeguarding cloud-native applications during their entire lifecycle development across public cloud environments.
Gartner defines CNAPP as a “unified and tightly integrated set of security and compliance capabilities designed to protect cloud-native infrastructure and applications.” The solution unifies multiple proactive and reactive cloud security capabilities to enhance visibility into risks, misconfiguration detection and remediation, threat intelligence and response, cloud workload protection, permissions management, and compliance management, to name a few.
Traditional CNAPP solutions comprise a variety of components, but the core ones usually include the following:
- Cloud Security Posture Management (CSPM): CSPM solutions help organizations assess the overall security posture of their public cloud infrastructure. They provide insights into critical misconfiguration issues that could lead to cloud security breaches. The tool also allows remediation measures and compliance with security standards.
- Cloud Infrastructure Entitlement Management (CIEM): CIEM allows security teams to manage permissions configurations across their cloud footprint. It helps teams enforce the principle of least privilege access by scanning the environment for unauthorized access points, discovering access issues related to specific users or roles, and reporting it to concerned personnel for remediation.
- Cloud Workload Protection Platform (CWPP): CWPP lets teams detect and respond to security threats and risks across an organization’s cloud infrastructure workloads.
Data Loss Prevention (DLP)
Data exfiltration, or extrusion or exportation, is a common data security threat. To put things in perspective, the global market for this technique was worth $69.1 billion in 2021 and is estimated to reach $217.5 billion by 2031, growing at a 26.77% CAGR. Various factors, such as exposed employee credentials or an insider attack, can cause it. Organizations take a reactive approach to overcome these security threats by deploying data loss prevention (DLP) solutions.
Simply put, DLP solutions protect sensitive data from unauthorized access by preventing it from leaving an organization's secure boundary (environment). It inspects and controls data in motion or at rest across emails, cloud storages, or networks, enforcing predefined policies, such as encryption, to ensure data doesn’t fall into the wrong hands. DLP solutions offer a reactive approach to data leak protection since they mitigate known risks.
Traditional DLP tools offer the following capabilities:
- Data Classification: Data classification is one of the core capabilities of a DLP solution. The tool detects every piece of data across structured and unstructured formats and assigns labels based on the data sensitivity level. Though it is suggested to use a minimum number of markers for classification, there could be hundreds of markers depending on the business need.
- Encryption, Blocking, or Access Revoking: DLP reacts to certain rules based on a predefined set of policies. Based on those policies, the tool may choose to encrypt the data, block it completely, or revoke users’ access.
- Monitoring and Reporting: DLP tools continue to monitor the movement of sensitive data across endpoints, networks, or emails. If a rule is triggered, the tool may generate an alert and notify cybersecurity teams. Based on the assessment, the security team may decide whether the alert is a false positive or a security incident.
Data Security Posture Management (DSPM)
While DLP and CNAPP are capable cloud security tools, their limitations prevent them from offering a holistic security solution. This is where data security posture management (DSPM) comes into play.
The term DSPM was first introduced by Gartner in its 2022 Hype Cycle™ for Data Security report. Since then, DSPM has become one of the fastest-growing categories in cloud data security solutions, forecasted to be adopted by 75% of organizations by mid-2025.
Among the most pressing concerns organizations face today regarding data security are excessive data access and a lack of visibility into sensitive data. A staggering 83% of IT and cybersecurity leaders cite that lack of data visibility significantly impacts the overall security posture of their organization.
DSPM gives organizations detailed insights into their sensitive data, how it is being used, and by whom. It helps build a relationship map between users and data sources to reveal potential risks across public and private cloud, SaaS applications, and on-premise environments. The tool further helps establish effective entitlement policies and controls and ensures compliance with security frameworks by setting up security posture policies.
A robust DSPM solution includes the following capabilities:
- Data Discovery: The solution identifies and catalogs sensitive and regulated data in structured and unstructured formats across diverse data sources for complete visibility into the data landscape.
- Data Classification: DSPM classifies data based on its sensitivity level, business need, regulatory context, or any specific industry standards. Classification is necessary for DSPM as it helps apply appropriate security, governance, or compliance policies.
- Data Flow Mapping & Lineage Tracking: Data mapping and lineage tracking help governance and security teams track data movement between systems, networks, or applications. This allows organizations to gain insights into data transformation, such as how data is accessed, changed, or impacted throughout its lifecycle.
- Risk Assessment: DSPM enables teams to conduct risk assessments by monitoring data for vulnerabilities or misconfigurations. Teams assign risk scores to help prioritize remediation measures.
- Data Access Intelligence & Controls: DSPM further allows governance teams to monitor and gain insights into sensitive data access based on users, roles, permissions, and geographies. By monitoring specific parameters, such as inactive users or abnormal access usage, governance teams can implement a least privilege access model better.
- Security Control Implementation: Security controls are assigned accordingly based on the intelligence gathered via classification and risk scores. For instance, encryption or data masking policies may be implemented for sensitive data at rest or in motion.
- Secure AI Data Flows: Leading DSPM tools like Securiti’s DSPM solution go beyond traditional data protection and offer data and AI security. For instance, Securiti helps organizations gain insights into data and AI security and compliance posture. Teams can further gain insights into toxic combination risks via out-of-the-box tests.
