By PJ Bradley
Data breaches are no small threat to organizations: in 2024, they cost an average of 4.88 million USD, according to IBM’s annual Cost of a Data Breach report, a figure that is only the latest and highest in a long upward trend. Protecting sensitive data can be a daunting undertaking for organizations. Still, it is one of the most important factors in preventing not only financial losses but a wide range of other consequences.
Modern digital environments are large and sprawling, making many traditional data protection tools less effective against the constantly evolving risks in an increasingly perilous threat landscape. Data Security Posture Management (DSPM) has emerged in response to the challenges of safeguarding data across complex cloud environments, presenting a data-focused approach to cloud security.
Data Security Challenges in the Cloud
Of the breaches counted in IBM’s report, a full one-third involved unknown or undiscovered data, often referred to as shadow data. In complex and multi-cloud environments, data stores are often spread out across many different platforms. Traditional data discovery tools are often ill-equipped to find all that data, and other solutions and security teams cannot protect data if they do not know where it is.
The nature of sprawling cloud environments also makes it more complicated to secure data against attacks, even once it is discovered. A traditional “castle and moat” approach to security, which delineates the edge of the digital environment and focuses on keeping the wrong people out of the organization, does not account for the modern widespread use of cloud platforms, many of which are hosted externally.
There is a wide range of tools available for the many steps involved in protecting sensitive data, from discovery to incident response, but many solutions are not designed to address modern data security needs. They are often built to search and secure only specific “devices, endpoints, systems, apps, and APIs” rather than discovering and protecting data throughout the entire digital environment across all cloud platforms, including IaaS, SaaS, and PaaS.
DSPM Functions and Features
Developed with data security at front of mind, DSPM offers a variety of functions traditionally covered by standalone legacy tools. The key functions of DSPM platforms include:
- Data Discovery and Classification: Discovering data wherever it resides across all cloud platforms and classifying it based on its sensitivity.
- Risk Assessment and Prioritization: Evaluating risks to data security according to factors like access level and threat intelligence and determining which threats are the most pressing to address.
- Continuous Monitoring and Logging: Monitoring the data security environment for risks and vulnerabilities to prevent threats proactively.
- Configuration, Policy, and Compliance Management: Identifying security misconfigurations, misaligned policies, and places where data security measures are not in line with laws and regulations.
- Reporting and Alerting: Providing thorough reports and dashboards to offer detailed insights on the organization’s data security posture that security teams can use to make informed decisions.
- User and Entity Behavior Analytics: Analyzing the behaviors of users and entities to understand what normal activity looks like and identify anomalous behaviors that could represent security risks.
- Automation: Automating many of the time-consuming, repetitive, and intensive processes involved in data protection, using advanced technologies like artificial intelligence (AI) and machine learning (ML) to streamline operations effectively.
Benefits of DSPM for Data Protection
Implementing DSPM tools can help organizations protect the sensitive data they have stored across various cloud platforms. DSPM is primarily built to help organizations strengthen the security posture of their data stores in complex cloud environments, protecting data against constantly evolving threats. Traditional measures for discovering, classifying, and protecting sensitive data would require tech stacks to cover what DSPM does in one platform.
DSPM has many advantages. It effectively provides comprehensive visibility into where data is stored and contextual information on how data is accessed and used and by whom. The classification and prioritization capabilities of DSPM tools also offer significant context that many legacy tools cannot detect, enabling security teams to address the most pressing security tasks first.
With features for configuration and policy management, compliance checking, and reporting and alerting, DSPM solutions can also greatly alleviate the difficulties of cross-referencing regulatory requirements and industry standards, checking that configurations and policies are secure and effective, and aligning security measures with applicable regulations. This allows security teams to focus on proactively hunting and preventing threats to data security rather than painstakingly worrying about the minutiae of compliance and security configurations.
Conclusion
Today, organizations must take steps to secure their sensitive data against a wide range of threats, many of which can even come from internal actors. Protecting data has never been more complicated or crucial for organizations of all types in all sectors. The broad attack surfaces, sophisticated threats, and multi-cloud environments all mean that legacy tools tend to fall short.
DSPM solutions are designed to account for advanced threats and complex cloud environments by taking a “data first” approach. By covering a range of functions, leveraging innovative technologies, providing comprehensive visibility into data stores, and ensuring regulatory compliance, DSPM can go a long way toward protecting your organization’s sensitive data.