What is DSPM? Data Security Posture Management Guide

Cybercrime costs are projected to hit $10.5 trillion annually by 2025. This alarming statistic, and many others, reflects the critical need to reinforce your organization’s data security strategy. However, challenges like growing multi-cloud complexities, the ever-evolving data privacy laws, the limited capabilities of traditional DLP or CNAPP tools, and emerging GenAI threats pose significant obstacles.

Here, data security procurement management (DSPM) comes into play—as a data-centric approach to reinforcing data security.

This article will explore DSPM and how this technology can address your organization's specific data security objectives. We will cover the core concepts, key capabilities, and critical features to consider when selecting a DSPM solution.

What is Data Security Posture Management (DSPM)?

Data Security Posture Management (DSPM) gives visibility into sensitive data, i.e., where it exists across an enterprise environment, who can access it, and how it is used. It further provides comprehensive insights into security posture, risks, and the controls or policies to mitigate them.

DSPM was first introduced and defined by Gartner in its 2022 Hype Cycle™ for Data Security report. Later, in 2024, GigaOm further defined DSPM in its GigaOm Radar report as a solution that provides

“visibility into where sensitive data is, who has access to it, and how it is being used. DSPM gives a comprehensive view of an organization’s data security posture, its compliance position, security and privacy risks, and, crucially, how to deal with them.”

DSPM aligns with the latest security frameworks (such as the CIS Critical Security Controls and the NISt framework), treating data security as a top priority. It addresses the regulatory needs of ubiquitous data protection laws like the GDPR and the CPRA to implement strict security measures to protect personal and sensitive data.

Going back to GigaOm’s definition, DSPM helps organizations answer the most concerning questions that make up the backbone of a robust data security ecosystem:

• What sensitive data do we have, and where is it located?
• Who has access to the data?
• How has the data been used?
• What is the security posture of the data store or application?

A DSPM framework must address these concerns to be effective and inclusive.

Why DSPM is Important?

Here are some of the reasons why it is important.

Manage & Secure Data in Complex Environments

Hybrid and multi-cloud deployments are now the major focus of most organizations globally. To put that in perspective, CISCO cites in its 2022 Global Hybrid Cloud Trends Report that 82% of IT leaders flocked toward hybrid cloud adoption in 2022. Both hybrid cloud and multi-cloud environments are known for their speed, efficiency, and scalability.

However, the innate complexities of these environments render many organizations unable to ensure a consistent security posture of their data landscape. DSPM helps effectively manage and protect data in such environments by providing comprehensive visibility of sensitive data and controls over sensitive data access, governance policies, and cloud security posture.

Identify & Mitigate Data Security Risks

The benefits of the multi-cloud often triumph over the complexities, but it can certainly lead to many security risks. The lack of a centralized view of corporate data assets, sensitive data environment, and appropriate controls often challenges security teams.

Teams don’t have a complete view of sensitive data and where it exists. Additionally, each cloud service provider provides different security configurations. DSPM helps identify and mitigate cloud data security risks by helping teams analyze various parameters, including the visibility of sensitive data, its access control, data flow (data transformation), and infrastructure errors or misconfigurations.

Help Businesses Meet Compliance Requirements

Almost every industry is subject to some form of data privacy and security compliance, such as the National Institute of Standards and Technology (NIST), Payment Card Industry Data Security Standard (PCI DSS), or Sarbanes-Oxley (SOX). Compliance with national and international data protection laws like the GDPR or CPRA becomes more challenging. Every regulatory compliance has different requirements, which can be challenging without 360-degree insights into sensitive data.

For instance, PCI DSS doesn’t impose strict requirements for cross-border transfers of sensitive data. However, it does require entities to take appropriate security measures. However, GDPR imposes several strict restrictions concerning sensitive data transfer outside the EU borders.

Businesses subject to multiple regulations may find it difficult to categorize data as sensitive or personal, and depending on it, they may have to prioritize and establish security controls. DSPM provides visibility into the sensitive data and maps the data to different regulatory requirements. With appropriate tagging and classification, businesses can effectively ensure that appropriate controls are in place about security, cross-border transfer, and access policies and thus further establish compliance.

The Benefits of Implementing DSPM

Let’s take a look at some of the following benefits.

Protect Data Across Multiple Clouds

It provides complete visibility and control over an organization's data landscape. It enables the discovery and classification of sensitive data and security measures across multi-cloud environments, such as access controls and sanitization. With continuous monitoring of data access and usage, DSPM can detect unauthorized activities that threaten sensitive data, secure that data from potential breaches, and provide insights to help security teams optimize prevention strategies in the future.

Enhanced Risk Mitigation

It continuously evaluates the security posture of data assets and AI applications by assessing risk scores based on identified vulnerabilities. This helps security teams prioritize and address the most critical risks first, reducing potential threats and improving overall data security.

It further helps organizations reduce their attack surface by mapping data and AI flows and identifying weak points where data might be vulnerable due to misconfigurations, overprivileged access, and outdated security measures. Its ability to detect and automatically respond to security incidents helps organizations rapidly contain and remediate threats, reducing the potential impact of an incident on the organization and its data.

Improved Compliance and Regulatory Alignment

Businesses operating globally may find it difficult to categorize data as sensitive or personal per overlapping or conflicting compliance requirements. With appropriate tagging and classification, businesses can ensure that the right controls regarding security, access, and cross-border transfer policies are in place and establish compliance with various overlapping or conflicting regulations.

Prevention of Sensitive Data Exposure

It is estimated that up to 74% of cybersecurity breaches are caused by human error. Mitigating the risk of public exposure of sensitive or personal data due to insider mistakes, misconfigurations, or inadequate security controls is essential. DSPM enables security teams to swiftly detect and correct misconfigured data assets, prioritizing those containing sensitive information. This prioritization helps minimize security vulnerabilities, breach incidents, and operational disruptions, maintaining a secure data environment.

Secure Adoption of AI

Organizations are increasingly turning to AI learning models for enhanced operational efficiency and accelerated growth. However, Generative AI, such as large language models (LLMs), requires considerable data for training and fine-tuning. This introduces many risks, from sensitive data exposure to data poisoning or excessive agency. Advanced DSPM solutions help organizations safely embrace AI by providing capabilities like AI asset discovery, AI pipeline data flow security, and limited access entitlements.

Increased Agility and Centralized Control Over Data

DSPM enhances organizational agility by providing real-time insights into data security and enabling rapid responses to emerging threats. This allows organizations to adapt quickly to changes in the data environment. By having centralized control over data security policies, security professionals can ensure consistent enforcement across all environments, strengthening the security posture of the entire organization.

Cost Efficiency and Resource Optimization

DSPM enables organizations to identify and eliminate redundant, obsolete, or trivial (ROT) data by providing comprehensive visibility into data usage patterns. This improved insight prevents costly overprovisioning while enhancing data lifecycle management and facilitating efforts to archive or delete outdated data, further reducing storage costs. Additionally, the continuous compliance monitoring capability helps teams avoid costly fines and penalties associated with data breaches or noncompliance while reducing the manual effort required for auditing and reporting, further lowering costs.

The Key Capabilities of DSPM - How it Works

DSPM provides a holistic approach to data security, integrating several key capabilities to ensure data management, compliance, and protection across diverse multi-cloud, on-premises, and hybrid environments.

GigaOm’s definition begins with identifying sensitive data, which is the first fundamental step in understanding how it works. The GigaOm Radar report further provides a detailed list of key capabilities a robust DSPM solution should offer.

Data Discovery

Data discovery involves scanning and identifying all data assets within an organization’s data estate, including multi-cloud environments, on-premises systems, and hybrid infrastructures. The solution automates locating structured and unstructured data assets, ensuring no data source is overlooked. This process helps organizations create a comprehensive inventory of what data they possess and where it is stored.

Data Classification

Once data is discovered, DSPM tools classify it based on its sensitivity, the regulatory requirements that pertain to it, its business importance, and according to policies relevant to the specific industry or internal policies determined by the organization. In the process of classification, the data may be tagged into categories like personally identifiable information (PII), financial records, or intellectual property (IP), as well as by regulations like GDPR, CPRA, Payment Card Industry Data Security Standard (PCI DSS), Sarbanes-Oxley Act (SOX), and Health Insurance Portability and Accountability Act (HIPAA). This critical step enables security teams to apply the right controls over the data and prioritize the protection of the most sensitive data.

Data Flow Mapping

Data flow mapping tracks how data moves within and between systems, applications, and networks. As data flows to and from various environments, tracking data movements and maintaining robust security measures becomes more challenging. Teams across the enterprise need to visualize how data moves between systems to accurately assess whether privacy and security controls apply consistently to the data. DSPM tools visually represent data flows, highlighting where data is accessed, transmitted, and stored. Understanding data flows helps teams trace data transformations, track duplicates for remediation, identify potential vulnerabilities more effectively, and ensure that security measures are applied consistently throughout the data lifecycle.

Risk Assessment

Once organizations identify, classify, and visualize data at rest and in motion, they need to analyze the data assets and flows to determine potential security threats and vulnerabilities. The solutions enable organizations to conduct effective risk assessments by continuously monitoring data environments for vulnerabilities like unauthorized access and misconfigurations. It can also assign risk scores to data assets, helping security teams prioritize remediation efforts and allocate resources to address the most critical risks.

Data Access Intelligence & Controls

DSPM monitors and tracks insights into sensitive data access based on users, roles, and geographies. Using sensitive data insights where data is mapped with regulatory insights, it sets up access policies, such as which user or role can have what level of permission to access certain data, systems, or applications. Governance teams can effectively implement a least privileged access model by monitoring specific access parameters, such as inactive users or overtime access usage.

Security Control Implementation

Building upon risk assessment capabilities, DSPM helps organizations enforce security controls to protect data based on its classification and risk scores. These controls may include access controls to restrict who is allowed to view or modify data, encryption to protect data in motion and at rest, and data masking to obscure sensitive information. By automating policies around these security controls, the solution helps organizations ensure that the controls are applied consistently across all environments, reducing the risk of human error.

Data Lineage Tracking

Data transformation occurs at any given instance, from creation and analysis to retention. Tracking data lineage at scale can be challenging for security teams, creating further security gaps. Robust DSPM solutions should allow data and security teams to track changes to the data over time to understand better how it is impacted, accessed, and changed down the line.

Monitoring and Auditing

Continuous monitoring is essential for mitigating threats to sensitive data, determining what data might be at risk across systems, and spotting potential security issues in real-time before the data is compromised. The solution comprehensively monitors data access, usage patterns, and security configurations, ensuring that any deviations are promptly identified. Additionally, it maintains detailed records of all data interactions in accordance with regulatory requirements for compliance.

Breach Response and Remediation

The solution can automatically respond to data breaches to mitigate their impact when they are detected. Automated response capabilities may include isolating the affected systems, revoking compromised access credentials, and initiating a breach notification process. In particular, the solution assists in assessing the incident's impact by determining the amount of data exposed, identifying whose data was compromised, and evaluating potential regulatory fines. It also automates the required notifications as mandated by law while providing a comprehensive analysis to enhance security measures and refine response strategies for future threats.

Seamless Integration with Enterprise Stack

A good solution should offer smooth integration with existing stacks, such as incident response tools, SIEM, etc. This important operational aspect ensures that the tool works seamlessly with existing workflows and helps maximize the current stack's value.

Secure AI Data Flows

As data moves through various stages of AI development, it is exposed to multiple risks, ranging from sensitive data exposure and oversharing to poor-quality training data and excessive agency. The solutions should provide advanced capabilities to organizations, enabling them to accelerate the safe adoption of AI, such as data sanitization, cleansing, redaction, and masking.

Best Practices to Implement DSPM

Getting started with DSPM requires a structured approach that ensures effective deployment throughout your organization and seamless integration within your existing infrastructure. These steps are critical for building a unified and efficient data security environment that ensures continuous protection and compliance.

DSPM Deployment

Identify Your Organization’s Security Requirements: Start by thoroughly understanding your organization’s security needs and objectives. Assess your data assets, compliance requirements, security policies, and the top risks to your sensitive data. Involve key stakeholders, especially from IT, compliance, governance, and legal teams, to gain alignment on your cybersecurity objectives from the beginning.

Select the Best Solution for Your Business Needs: After clearly understanding your security requirements, evaluate and select a DSPM solution that best fits your business needs. Consider factors like scalability, integration with other systems in your tech stack, breadth of security features, and customer support.

Empower Your Security Team to Work with DSPM: Provide necessary training for your new solution, ensuring that key members of the organization understand its functionalities and how to leverage them effectively. Foster collaboration between your cybersecurity teams and other departments involved to integrate best practices into your broader organizational workflow from the start.

Deploy and Configure the DSPM and Start Monitoring: Set up your DSPM technology according to your organization’s specific requirements and data environment. This involves configuring data discovery and classification processes, defining policies, setting up access controls, and defining monitoring parameters. Once deployed, initiate continuous monitoring to gather insights into your security posture and detect any potential threats.

Integrate the DSPM with Your Other Security Tools: Integrate the tool into your existing security stack, which may include SIEM, IAM, and incident response tools (see the “DSPM Integrations” section below). Regularly updating and fine-tuning the setup based on feedback and evolving security needs will be necessary to maintain and optimize its effectiveness and value.

DSPM Integrations

1. Identity and Access Management (IAM): DSPM integration enhances IAM security by enabling organizations to enforce least-privilege access to sensitive data. The solutions can leverage IAM integration to understand identity attributes, such as user job role, location, and departments, to help define scalable attribute-based access controls.
2. Cloud Access Security Brokers (CASBs): CASBs control access to cloud systems, while DSPM offers more detailed information about the data within the applications, such as data sensitivity and usage. The solution can complement CASBs to lead to more refined and effective security policies.
3. Security Information and Event Management (SIEM): DSPM enhances SIEM with the contextual data intelligence needed to correlate data-related events with other security logs. This offers a more complete view of potential threats and improves incident response capabilities.
4. Data Loss Prevention (DLP): DSPM provides accurate updates about where sensitive data is located, improving the accuracy of DLP policies and reducing false positives.
5. Intrusion Detection and Prevention Systems (IDPS): DSPM integration with IDPS improves the monitoring, detection, and prevention of intrusions that threaten sensitive data. This makes IDPS more data-aware and focused on protecting the most critical information.
6. Security Analytics: DSPM feeds valuable data insights into security analytics platforms, enriching the analysis with detailed information about data sensitivity, access patterns, and potential risks. This allows for more sophisticated threat detection and risk assessment.

What to Look for in a DSPM Solution

Following are some of the extended capabilities that you must also look for:

1. Rapid, Agentless Visibility into Critical Data: Ensure your solution provides agentless visibility into critical data across the entire environment. This capability allows you to quickly discover and map all data assets without the need for intrusive agents, enabling immediate insights and reducing complexities in the deployment process.
2. Centralized Dashboard and Reporting: A unified interface that aggregates data security metrics and generates comprehensive reports, simplifies monitoring, enhances decision-making, and ensures that all stakeholders have access to critical security information in real-time.
3. Continuous Detection and Prioritization of Critical Data Exposure: Ensure your solution can identify the most significant threats to your data security and enable efficient remediation efforts to protect sensitive data.
4. Data Lineage Mapping: Data lineage capabilities should be a core component of your solution. It enables data and security teams to track changes to sensitive data over time to better understand how and by whom it is processed. Security teams can identify gaps, detect unauthorized access, and establish optimal security policies.
5. Automated Remediation: Real-time remediation is a crucial feature to look for in your solution. The ability to automatically respond to security incidents as they occur minimizes the impact of data breaches and helps maintain the integrity and confidentiality of your data.
6. Automated Compliance Assessments: Automating your compliance assessment processes is critical for continuously adhering to regulatory standards. To simplify compliance management and reduce the risk of noncompliance violations or penalties, look for a solution that continuously evaluates your data security practices against relevant regulations.
7. Extend to AI: Choose a solution that extends its capabilities to generative AI-driven data environments. As GenAI systems handle increasingly sensitive data, the ability to apply DSPM principles to these environments is more critical.
8. Scalability and Performance: Large organizations with extensive data environments must have a DSPM solution that scales to accommodate growing data volumes while maintaining high performance. It should also consistently provide reliable data security management as the organization evolves.

DSPM vs. CSPM: An Overview of Differences

Cloud Security Posture Management (CSPM) and Data Security Posture Management (DSPM) involve multi-cloud protection but differ in focus. However, it is common for some organizations to face difficulty distinguishing between CSPM and DSPM.

CSPM is a set of tools designed to discover, alert, and remediate cloud misconfiguration issues and compliance risks. CSPM tools scan cloud infrastructure configurations against best practices framework to identify and remediate security gaps immediately. Overall, CSPM primarily focuses on cloud infrastructure, emphasizing a cloud-first approach.

For example, if an Amazon S3 bucket is publicly accessible through a configuration setting, a CSPM solution will always alert the user that it’s a security risk. However, if the S3 bucket contains non-sensitive data, such as marketing images for a website’s front end, then making the data publicly accessible is actually the correct behavior.

Due to their lack of intelligence around data, CSPM solutions can generate many false positive data security alerts, diverting security attention toward issues that don’t need to be fixed. When this happens, there is a risk that security owners or developers might ignore alerts, allowing a real misconfiguration, such as a public S3 bucket with sensitive customer PII, to slip through and increase the risk of a security breach.

DSPM complements CSPM with its deep intelligence around an organization’s data everywhere within cloud infrastructure services and SaaS applications. DSPM takes a “data-first” approach by prioritizing the discovery of sensitive data in the environment to identify potential security and compliance misconfiguration risks.

In the example above, the tool will only generate an alert if the S3 bucket contains sensitive data, such as customer PII, that should be protected based on company security policy. Besides identifying and auto-remediating security misconfiguration risks, it also helps establish data access control policies. Organizations can streamline their security, governance, and compliance functions with deep visibility into sensitive data and appropriate controls.

What is the Difference Between DSPM and DLP?

DLPs are good at detecting data being extracted from an environment. However, they are not good at data classification. DLP solutions use regex-based classification and generate classification labels that may not be accurate, resulting in false alarms about data being stolen. The solutions can integrate with DLP to provide more accurate AI-based classification to help organizations get the most out of DLP.

Mistakes to Avoid When Implementing DSPM

Organizations seeking a DSPM solution should be aware of critical challenges that could hinder the tool’s implementation.

Lack of Collaboration Between Data Teams

Organizations often have a myriad of teams, such as IT security, legal, and business teams, that operate in silos. This piecemeal data management approach can lead to significant data protection and compliance gaps. Since data security is a cross-functional responsibility, stakeholders from all key departments must collaborate to ensure the successful implementation of DSPM.

Classifying Data Differently in Different Environments

Another major challenge in most organizations is inconsistent data classification rules in different environments. Varying classification standards can result in significant errors and inconsistencies, impacting an organization's overall data security posture. For instance, a dataset tagged as "internal use only" in one environment might be labeled as "sensitive" in another, leading to inadequate access controls and sensitive data exposure. Organizations must seek DSPM solutions that work seamlessly across on-premise, hybrid, SaaS, and multi-cloud environments. This enables standardized classification and ensures consistent security policies and controls.

Not Thinking Beyond Data Classification

Organizations must not limit DSPM to classification only. Though data classification is critical, it is just a first step in the overall DSPM strategy. When organizations limit their DSPM strategy to only classifying data into personally identifiable information (PII) or financial data, it tends to fail when it comes to implementing broader security measures. DSPM should go beyond classification and include more comprehensive security controls like access intelligence and controls, real-time threat detection, or automated incident response.

Not Testing for False Positives at Scale

False positives happen when a security tool marks a harmless event, action, or activity as a security threat. When DSPM tools are not tested for false positives and send such alerts, security teams may not trust the systems and ignore them. Consequently, genuine threats could go unnoticed. Organizations must test their DSPM solution for false positives at scale to overcome this mistake. Adequate testing will ensure that alerts are accurate and reliable.

Not Automating Remediations & Actions

Manual processes, especially concerning incident detection and mitigation, slow down response time, which could escalate security incidents. Organizations must consider automating remediation to deal with threats in real-time as they are detected to reduce manual effort and the risk of data breaches.

How Securiti Can Help

Despite the promise of DSPM technology, not all solutions are created equal. In its Hype Cycle™ for Data Security 2022 report, Gartner cites that having meaningful data insights and risk assessments is impossible if organizations continue to view different controls, such as sensitive data context, access governance policies, data transformation, and security configuration, through separate lenses. A lack of a centralized view will eventually create more security, governance, and compliance risks. Therefore, organizations must unify these controls into a comprehensive view of their data risks to establish effective data management and protection strategies.

Securiti’s Data Command Center replaces the fragmented Data Security Posture Management approach with a unified framework, providing deeper intelligence and visibility into an organization’s data landscape. This solution offers unified controls over data across all environments. Unifying data discovery, classification and cataloging, data lineage, access governance and control, and cloud security posture management enables teams to streamline their data obligations across security, governance, privacy, and compliance.

Securiti goes beyond typical DSPM solutions that support only the public cloud by delivering a solution that secures data across public clouds, private clouds, data clouds, and SaaS. It offers best-in-class DSPM capabilities by unifying intelligence around data (structured and unstructured, at rest and in motion), access governance policies and controls, data transformation insights, data mapping automation, and the ability to reduce misconfigured data systems.

In addition, Securiti helps organizations manage risk effectively in the unfortunate event of a data breach by automatically discovering impacted users, identities, and data.

Moreover, Securiti’s Data Command Center enables organizations to implement privacy and governance controls more intelligently without scanning and classifying data multiple times for each team (security, privacy, and governance). The siloed approach is cost-prohibitive and hampers team collaboration, making it impractical. With Securiti, organizations can unify their security, privacy, governance, and compliance controls into a common view, enabling a comprehensive understanding of their data risks and obligations.

Securiti stands out in the space as the #1 DSPM solution, as rated by GigaOm and Gartner Customer Choice report. Securiti’s approach to DSPM is integrated into the overall platform as a critical capability in a single, centralized, and comprehensive Data Command Center.

Schedule a personal demo to address your organization’s unique needs and objectives.

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