Data Security Posture Management (DSPM)

Data Security Posture Management (DSPM) is designed to discover, classify, and protect sensitive data across cloud, on-prem, and hybrid environments. Because data security is a business-critical priority, DSPM has emerged as the fastest-growing security category, with 75% of organizations saying they will adopt DSPM by mid-2025. 

The primary reason for this adoption is that companies lack visibility into their most valuable asset: their data. Security teams struggle to answer essential questions, like:

• Where is our sensitive data stored?
• Who has access to it?
• Is it properly secured?
• Are we meeting compliance requirements?

Traditional security models focus on protecting networks, endpoints, and cloud configurations. While these measures are important, they don’t provide a clear understanding of where sensitive data lives or how it is exposed. This is like building a castle to protect treasure despite not knowing where that treasure even is.

As data constantly moves between cloud environments, on-premises systems, and SaaS applications, organizations need a data-first approach to security. 

This is where DSPM comes in.

Defining Data Security Posture Management (DSPM)

The newest generation of DSPM, called AI-native (as it was invented in the age of AI), provides data visibility at unprecedented scale, precision, and speed. With AI-native DSPM, organizations can discover and classify massive datasets faster than ever before. 

Unlike other security tools that focus on perimeter defense, firewalls, data movement, or configurations, DSPM focuses on the data itself, helping you fully understand your kingdom’s treasure, which ultimately, enables you to build a more effective castle to protect it. 

Why DSPM is Different from Traditional Security Tools

Traditional security tools were designed for company-controlled environments, emphasizing network perimeters (firewalls, VPNs), endpoint protection (antivirus), and data movement controls (DLP)

While these methods remain important, without clear data visibility, they are far less effective than they could be. That’s because data no longer stays within a defined perimeter. It flows across multi-cloud environments, third-party applications, remote workforces, and on-prem storage systems.

AI-native DSPM is built to address this reality, providing:

• End-to-end visibility across cloud, SaaS, and on-prem storage.
• Automated classification of sensitive data, eliminating manual classification entirely.
• Proactive risk assessment to detect exposure risks before they are exploited.
• Monitoring to identify risks as they arise and track how data is accessed and used.
• Automated remediation to enforce security policies dynamically.

By shifting to a data-centric security model, organizations can eliminate blind spots, reduce attack surfaces, and demonstrate compliance—all while unlocking innovation for AI initiatives. Because data is the fuel for AI, it’s imperative that organizations understand what data is being pulled into (and pulled out of) their AI tools and systems. 

The Growing Data Security Challenge: Cloud, On-Prem, and Compliance Risks

Organizations are generating and storing more data than ever. But with this data explosion comes significant risks, such as: 

Data sprawl, which occurs when data is shared and multiplies across environments, creating a larger, more obscure attack surface.

Shadow data, which occurs when sensitive data slips through the cracks, gets forgotten about, and otherwise becomes unmanaged and unmonitored.  copies of sensitive data, increasing the risk of accidental exposure.

Excessive access, which occurs when accounts (human and non-human) are overpermissioned, meaning that users or applications can access data they should not be able to.

Regulatory compliance challenges, which occurs when data fails to meet regulatory requirements across laws and frameworks like the GDPR, HIPAA, PCI DSS, and more.  

Cloud Data Security vs. On-Prem Data Security: A Unified Approach is Required

While cloud security has increased in priority in recent years, many organizations still rely on on-premises infrastructure for mission-critical data. As a result, organizations are looking to protect both cloud-based and on-prem data with a single security platform.

That said, the challenges of data security in the cloud are different from those on-prem. Cloud security is fast-moving but requires strict governance to prevent misconfigurations and access risks. On-prem security is resource-heavy, slow to scale, and vulnerable to outdated defenses.

DSPM bridges this gap, providing a unified data security posture across cloud, SaaS, and on-prem environments. Organizations gain full visibility into their data, helping to reduce security risks and maintain compliance without operational overhead.

How DSPM Works: A Step-by-Step Breakdown

AI-native DSPM provides a novel approach to data security that simply wasn’t possible before the advent of AI. Here’s how it works:

1. Data Discovery and Classification

The first step in securing data is knowing where it’s located and what the data is. DSPM does this automatically by:

• Scanning cloud, on-prem, and SaaS environments to locate sensitive data, even the shadow data you don’t know about. 
• Classifies structured, semi-structured, and unstructured data based on a multitude of characteristics.
• Provides context about the data, enabling organizations to truly understand what the data is and how it’s being used.   

This eliminates the need for manual data classification, giving security teams visibility into their sensitive information without requiring endless data tagging that’s out of date as soon as it’s done.

2. Risk Assessment and Security Posture Analysis

Once data is classified, DSPM assesses its security posture to identify potential risks, such as:

• Overexposed or publicly accessible data that could be exploited.
• Misconfigured permissions granting unauthorized access.
• Shadow data or unmonitored copies that pose compliance risks.

Organizations using DSPM are notified of these risks in a prioritized fashion, helping them identify which security, privacy, or compliance gaps need immediate attention.

3. Monitoring and Threat Detection

Security risks evolve constantly. DSPM continuously discovers and classifies data as it moves throughout your environments. By doing so, your security posture is always up to date. 

4. Automated Remediation 

Once risks are identified, DSPM helps automate actions, such as dynamically masking data, or integrating with your security systems to trigger remediating actions.  

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Why Organizations Need DSPM Now

Companies that fail to adopt a data-centric security approach face significant risks:

• Increased likelihood of data breaches, with an average breach costing roughly $4.8 million.
• Regulatory fines for non-compliance with data protection laws.
• Reputation damage, leading to loss of customer trust.
• Inability to adopt AI and other strategic data-driven initiatives.

DSPM helps organizations:

• Gain full visibility into their data.
• Automate risk detection and remediation.
• Strengthen compliance and governance across all environments.
• Leverage data to its full potential for AI and other initiatives.

Key Benefits of AI-Native DSPM

AI-native DSPM provides organizations with greater visibility and control over sensitive data across cloud, on-prem, and SaaS environments. It shifts data security from a reactive approach to a proactive one, preventing security incidents before they happen. After all, you can’t protect what you can’t see. 

Full Visibility into Sensitive Data

One of the biggest challenges organizations face is a lack of insight into where their sensitive data is stored. Sensitive information is often scattered across multiple cloud platforms, third-party applications, and internal systems. Without a centralized way to monitor data, organizations risk accidental exposure, insider threats, and compliance violations.

AI-native DSPM helps solve this by automatically scanning and inventorying all sensitive data across cloud and on-prem environments. Security teams gain a single source of truth for data security, making it easier to enforce policies, detect risks, and protect information from unauthorized access. 

The best DSPM solutions help you decode your data DNA, giving you visibility into data attributes, such as: 

• Owner
• Location
• Encryption status
• Backup status
• Hashed data
• Masked data
• Data Category
• Data Type
• Sensitivity Level
• Synthetic Data
• Applicable Regulations and Frameworks
• Data Subject Residency 
• Data Protection Measures
• Data Subject Type
• Business Context
• and much more…

Proactive Risk Assessment 

Traditional security tools often rely on signature-based threat detection, which means they can only respond to known threats. This reactive model fails to address emerging risks, such as new misconfigurations, unintentional data exposure, or insider threats.

DSPM provides proactive risk assessment, detecting misconfigured security settings, excessive access permissions, and unauthorized data storage (and other risks) before they can be exploited. Organizations leveraging DSPM can prioritize high-risk security gaps and remediate them automatically, reducing the likelihood of a breach.

Faster Compliance Reporting

Regulatory compliance is a growing challenge for businesses handling sensitive information. Laws and frameworks, such as GDPR, HIPAA, CCPA, and PCI DSS, require strict data protection, auditing, and reporting measures. However, most organizations rely on manual compliance audits, which are time-consuming and prone to errors.

DSPM streamlines compliance by automating data discovery, classification, and policy enforcement. Organizations can track compliance status much more easily, generating audit-ready reports and confirming that security controls align with regulatory requirements. This reduces the burden on security teams while improving compliance efficiencies.

Stronger Access Controls and Governance

Many data breaches occur due to overpermissioned accounts, when employees, partners, and third-party applications have more access to sensitive data than necessary, increasing the risk of insider threats or accidental exposure.

DSPM helps organizations enforce least privilege access policies, ensuring that only the right users have access to the right data at the right time. Consider this, do you know who has access to your most sensitive data? If you do not have clear data visibility, you probably can’t answer this question confidently. 

Faster Incident Response 

Security teams are overwhelmed with alert fatigue, making it difficult to prioritize critical threats and respond in time. Oftentimes, when an incident occurs, it’s hard for most organizations to know what data was compromised. It takes millions of dollars and large-scale consulting efforts to help provide an answer to the question: was this a material data breach? 

DSPM helps organizations respond quickly by providing clearer visibility into what data was impacted (and if it matters).

How DSPM Compares to Other Security Solutions

Many organizations already use various security tools to protect their data, but DSPM offers a data-centric approach. AI-native DSPM takes this a step further by leveraging AI to discover and classify data in ways that were previously impossible.

How DSPM is Different from Cloud Security Posture Management (CSPM)

CSPM secures cloud configurations but lacks deep data visibility. DSPM complements it by helping security teams prioritize misconfigurations that impact sensitive data.

How DSPM is Different from Data Loss Prevention (DLP)

Data Loss Prevention (DLP) tools prevent unauthorized data movement by blocking or restricting the flow of data. However, high false positive rates due to inaccurate classifications means that many DLP tools are often ineffective (or not even turned on). 

DSPM provides precise data classification, and these insights can be used to reduce false positive rates and help DLP tools live up to their promise. 

How DSPM is Different from Cloud Infrastructure Entitlement Management (CIEM)

Cloud Infrastructure Entitlement Management (CIEM) solutions help organizations identify, analyze, and remediate excessive or misconfigured permissions across cloud identities (both human and machine). 

While CIEM is critical for managing cloud identities and entitlements, it doesn;t address data risk directly. It focuses on who has access, but not necessarily what they are accessing and whether that access is appropriate or risky. 

How to Evaluate a DSPM Solution

With the growing adoption of DSPM, organizations need to carefully evaluate which platform best fits their security and compliance requirements.

Key Features to Look For in a DSPM Solutions

When choosing a DSPM solution, consider five critical factors:​

• Speed: Prioritize platforms that offer rapid deployment and quick results, often through agentless integration.
• Scale: Ensure the DSPM solution can effortlessly scale across expansive, complex environments.
• Precision: Opt for platforms with high classification precision, utilizing sophisticated AI-based methods beyond regular expressions. 
• AI-Native: Choose DSPM solutions created in the age of AI, capable of leveraging advanced AI and machine learning to discover and classify data that legacy providers miss.
• Context: Select platforms that provide deep insights into data, offering context such as data origin, associated regulations, and risk levels.​

Organizations that adopt AI-native DSPM will gain a strategic advantage, reducing security risks and unleashing innovation while ensuring data remains protected at all times.

Why DSPM is the Future of Data Security

As we’ve discussed, as data security threats grow more sophisticated, traditional perimeter-based defenses are no longer enough. With data sprawl accelerating, organizations need deeper data visibility. AI-native security solutions are becoming essential, offering enhanced visibility, automated risk assessment, and proactive protection. Meanwhile, regulatory frameworks—especially those governing data and AI—are rapidly evolving, making compliance a top priority.

By adopting DSPM now, organizations can strengthen their security posture, stay ahead of compliance requirements, and protect sensitive data across both cloud and on-prem environments.

Taking the Next Step with DSPM

Organizations can no longer rely on traditional security tools alone. As data becomes more distributed across cloud, SaaS, and hybrid environments, a data-first approach to security is essential.

DSPM provides the visibility, automation, and intelligence needed to protect sensitive information. Now is the time to take control of your data security posture.

Schedule a demo with Cyera to see how this technology can enhance your security strategy, prevent data breaches, and simplify compliance.

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FAQs

What is the difference between DSPM and DLP?

Data Security Posture Management (DSPM) and Data Loss Prevention (DLP) both focus on securing sensitive data, however, they serve different purposes.

DLP is primarily designed to prevent data from leaving an organization’s network by monitoring and controlling data movement. It enforces rule-based policies to block unauthorized data movement. However, DLP struggles in modern multi-cloud and SaaS environments, where data moves dynamically across applications and storage locations.

DSPM, on the other hand, provides visibility into where sensitive data resides, how it’s accessed, and whether it’s properly protected. It doesn’t block data movement but identifies security risks, excessive permissions, misconfigurations, and policy violations before they lead to a breach.

In short: DLP focuses on restricting data movement, while DSPM ensures data is secure at rest, regardless of where it resides.

What is a data security platform?

A data security platform is a comprehensive security solution that helps organizations protect sensitive data from unauthorized access, breaches, and compliance violations. These platforms typically include DSPM technology and other capabilities across:

• Data Loss Prevention (DLP)
• Identity
• Privacy
• Governance, Risk, and Compliance (GRC)
• Data Lineage
• AI Security

DSPM is often considered the most critical pillar of a data security platform. 

What is data security posture?

Data security posture is an organization's state in regard to protecting its data across all environments—cloud, on-premises, and hybrid. It involves continuously identifying sensitive data, detecting vulnerabilities, enforcing security policies, and responding to threats. 

A strong data security posture reduces the risk of breaches, prevents unauthorized access, and ensures regulatory compliance by integrating technologies like DSPM (Data Security Posture Management) and DLP (Data Loss Prevention) to safeguard critical information.

What is the difference between DSPM and CASB?

Cloud Access Security Brokers (CASB) and Data Security Posture Management (DSPM) both help organizations protect data, but they operate differently.

• CASB focuses on controlling and securing access to cloud applications. It monitors and enforces security policies when users interact with SaaS applications like Microsoft 365, Google Workspace, or Salesforce.
• DSPM focuses on securing data itself, regardless of where it is stored or accessed. It provides visibility into sensitive data locations, tracks security risks, and automates compliance enforcement.

In short: CASB secures cloud access and user behavior, while DSPM secures the actual data across all environments.

Is DSPM part of CNAPP?

Cloud-Native Application Protection Platforms (CNAPP) are security solutions designed to secure applications, workloads, and infrastructure in cloud environments. CNAPP includes components such as CSPM (Cloud Security Posture Management), CIEM (Cloud Infrastructure Entitlement Management), and workload security.

DSPM is not strictly part of CNAPP, but it complements CNAPP by adding a critical layer of data security. While CNAPP focuses on securing cloud configurations, applications, and user access, DSPM ensures that sensitive data stored in cloud environments is always protected.

Many organizations use both CNAPP and DSPM together for comprehensive cloud security.

Can DSPM fit into broader security strategies?

Yes, DSPM fits seamlessly into broader security strategies by enhancing data protection, risk management, and compliance efforts. Many organizations view it as the foundation of their data security strategy, integrating DSPM with:

• Zero Trust security models to enforce strict access controls.
• Cloud security solutions like CSPM, CNAPP, and CASB.
• Identity and Access Management (IAM) solutions to prevent unauthorized access.
• SIEM and SOAR platforms to improve threat detection and response.

DSPM acts as the missing piece in many security strategies by providing visibility into data security risks and ensuring continuous compliance.

What is data encryption?

Data encryption is a security capability that converts readable data into an unreadable format using cryptographic algorithms. This ensures that only authorized users with the correct decryption key can access the original information.

There are two primary types of encryption:

• At-rest encryption: Protects data stored in databases, cloud storage, and on-prem systems.
• In-transit encryption: Protects data moving between applications, networks, and cloud services.

Encryption is a critical component of data security. DSPM provides visibility into which data is encrypted and which isn’t but should be.