What is Data Security Posture Management (DSPM)?

Ensuring the robustness of your corporate data's cybersecurity foundation has become more crucial than ever before. This heightened importance stems from the rising number of cyber breaches, the increasing complexities of the multi-cloud environment, the constantly evolving data privacy laws, and the fragile nature of customer trust. This is where data security posture management (DSPM) comes into the picture.

The data security posture of your organization refers to its protective stance towards your data landscape, particularly sensitive data. Just as a martial artist's stance determines their ability to defend against incoming attacks, your organization's data security posture determines its strength and effectiveness in warding off cybersecurity threats.

However, establishing an optimal security posture entails more than just configuring firewalls, implementing encryption, or installing anti-malware software. In fact, it necessitates in-depth visibility into your entire data environment, data flow patterns, access governance policies, and configuration risks.

This blog will delve into the emerging need for data security posture management, its relationship with cloud security posture management, how it operates, and the imperative to reconsider the traditional piecemeal approach to posture management.

What is Data Security Posture Management?

Considering the escalating adoption of multi-cloud solutions and the growing incidence of cyberattacks, it comes as no surprise that Gartner emphasizes the importance of robust data security measures. Recognizing the urgency, Gartner has introduced a new category of Data Security Posture Management (DSPM) in its Hype Cycle™ for Data Security 2022 report.

In this report, Gartner defines DSPM as a process that provides:

Visibility regarding the location of sensitive data, the individuals with access to that data, how it has been utilized, and the security posture of the data store or application.

DSPM prioritizes a data-centric approach to safeguarding cloud data. It shifts the prevailing tendency of organizations that treat data as the final frontier and places a higher priority on protecting networks, systems, and resources.

DSPM complements contemporary security frameworks like the Center for Internet Security's Critical Security Controls, elevating data security to a top priority. Furthermore, even data protection regulations like the European Union's General Data Protection Regulation (GDPR) and the California Privacy Rights Act (CPRA) emphasize the implementation of stringent security measures to safeguard personal and sensitive personal data.

Overall, DSPM charts a strategic path for proactively assessing all factors that potentially impact an organization's data landscape's overall security posture. Most importantly, it enables organizations to address the most critical questions that form the backbone of a robust data security ecosystem:

• What sensitive data do we possess, and where is it located?
• Who has access to the data, and what level of permissions do they hold?
• What is the lineage of the data, and how has it evolved over time?
• What misconfigurations exist in our multi-cloud environment, and how can we detect and rectify them?

For a DSPM framework to be effective and comprehensive, it must be capable of addressing all the concerns mentioned above.

Comparison between Cloud Security Posture Management (CSPM) and Data Security Posture Management (DSPM)

Gartner classifies the maturity level of data security posture management (DSPM) as 'embryonic,' indicating that DSPM is still in its early stages. As a result, some organizations may find it challenging to differentiate between DSPM and cloud security posture management (CSPM). While both practices involve continuous protection in multi-cloud environments, there are differences in their focus.

Cloud security posture management encompasses a set of tools designed to identify, notify, and address cloud misconfiguration issues and compliance risks. Each cloud service has specific settings or configurations that dictate its appropriate use. In the fast-paced cloud environment, it is common for teams to misconfigure services, inadvertently increasing security risks.

Cloud providers and various security standards, such as CIS or NIST, offer best practices to guide the correct configuration of cloud services. CSPM tools scan the configurations of cloud infrastructure against these best practices to promptly identify and rectify security gaps. Overall, CSPM tools primarily concentrate on securing the cloud infrastructure, adhering to the cloud-first approach.

However, CSPM solutions have a limitation in that they lack contextual information about data stored within a cloud service. Without this context, security teams find it difficult to determine whether a configuration setting poses a security risk or not. For example, if an Amazon S3 bucket is configured for public access, a CSPM solution will always flag it as a security risk. However, in some cases, the S3 bucket might contain non-sensitive data like marketing images supporting a website's front end, where public accessibility is actually intended.

Due to the absence of data intelligence, CSPM solutions can generate numerous false positive data security alerts, diverting security attention to issues that do not require immediate fixing. Consequently, security owners or developers may ignore alerts, leading to a real misconfiguration, such as a publicly accessible S3 bucket containing sensitive customer personally identifiable information (PII) slipping through and increasing the risk of a security breach.

Data security posture management complements CSPM by providing deep intelligence on an organization's data across cloud infrastructure services and SaaS applications. DSPM adopts a 'data-first' approach, prioritizing the identification of sensitive data within the environment to pinpoint potential security and compliance misconfiguration risks.

In the previous example, a DSPM tool would generate an alert only if the S3 bucket contains sensitive data, such as customer PII that needs protection according to company security policies. Besides identifying and automatically remediating security misconfiguration risks, a DSPM solution also helps establish data access control policies. With comprehensive visibility into sensitive data and appropriate controls, organizations can streamline their security, governance, and compliance functions.

Essentially, CSPM focuses broadly on all cloud services providing computing, storage, and network solutions, ensuring their correct configuration. On the other hand, DSPM tools encompass all data systems and services within the cloud, as well as SaaS applications, ensuring their proper configuration and enforcement of appropriate data access controls. Both solutions should be employed simultaneously as part of an organization's layered defense.

The Importance of Data Security Posture Management

Before the advent of DSPM, CSPM was treated as a distinct security function. However, DSPM offers a comprehensive approach to the overall security of a corporate data landscape by prioritizing the protection of sensitive data and extending to the security of the data systems hosting that data.

The Benefits of DSPM

DSPM provides several benefits, including:

Managing and Securing Data in Complex Environments: Hybrid and multi-cloud deployments have become the primary focus for many organizations worldwide. For instance, according to Cisco's 2022 Global Hybrid Cloud Trends Report, 82% of IT leaders embraced hybrid cloud adoption in 2022.

Hybrid and multi-cloud environments offer speed, efficiency, and scalability, but their inherent complexities often make it challenging to ensure a consistent security posture for the data landscape. DSPM helps effectively manage and protect data in such environments by providing comprehensive visibility of sensitive data, as well as controls over data access, data governance policies, and cloud security posture.

Identifying and Mitigating Data Security Risks: While the benefits of the multi-cloud outweigh the complexities, they can also introduce various security risks. The lack of a centralized view of corporate data assets, the sensitive data environment, and appropriate controls can pose challenges for security teams.

They may not have a complete overview of sensitive data and its locations, making it difficult to effectively monitor access to that data. Additionally, each cloud service provider has different security configurations. DSPM assists in identifying and mitigating cloud data security risks by analyzing various parameters, including sensitive data visibility, access control, data flow, and infrastructure errors or misconfigurations.

Meeting Compliance Requirements: Virtually every industry is subject to data privacy and security compliance regulations, such as NIST, PCI DSS, or SOX, with the added complexity of national and international data protection laws like GDPR or CPRA. Each regulatory compliance framework has unique requirements, which can be challenging to meet without a 360-degree understanding of sensitive data.

DSPM provides visibility into sensitive data and maps it to different regulatory requirements. With appropriate tagging and classification, businesses can ensure the implementation of necessary controls related to security, cross-border data transfer, and access policies, thereby establishing compliance.

The benefits of DSPM go beyond these examples and extend to cost efficiency, reputation management, prevention of data breaches, and the retention of customer trust.

How DSPM Works - Key Functionalities

The operational mechanism of DSPM is centered around several essential capabilities. According to Gartner, the first and foremost capability of DSPM is the identification of sensitive data. Without a clear understanding of the data present in the environment and its sensitivity, effective protection becomes challenging. Thus, DSPM initiates by conducting data discovery and classification.

What sensitive data exists, and where is it located?

Discovery, Classification & Cataloging of Data

Data is scattered across hybrid or multi-cloud environments, spanning various cloud service providers, SaaS applications, IaaS systems, data lakes, data warehouses, and other micro services. The complexity is further compounded by the exponential growth of data in both structured and unstructured formats.

DSPM recognizes the monolithic nature and intricacies of the multi-cloud environment. It begins by discovering sensitive data throughout the corporate ecosystem, including structured and unstructured formats. Subsequently, the data is classified to provide accurate contextual information regarding its sensitivity.

Classification enables security teams to prioritize their focus on safeguarding data with high sensitivity levels, such as confidential or sensitive data, in compliance with data protection laws like GDPR or HIPAA. After classification, DSPM creates a precise data catalog or a single source of truth.

This catalog presents a comprehensive view of all existing data elements across the environment, along with their business context, intended use, and a glossary. The data is further aligned with relevant industry standards and regulatory jurisdictions.

Who has access to the data, and what permissions do they possess?

Insights into Data Access Governance

Managing access to sensitive data was relatively simpler in on-premise infrastructures compared to multi-cloud settings. Multi-cloud environments entail numerous data stores, with potentially thousands of data objects within them. This high volume of data is spread across multiple cloud services, with each data store and object potentially associated with multiple users, roles, and permissions.

While every cloud provider offers native Identity and Access Management (IAM) capabilities, these tools often have limited scope. Additionally, most cloud-native IAM tools lack sensitive data context, making data protection more challenging. The lack of insights into sensitive data access is not the only concern; other access governance issues prevail in the cloud, such as excessive privileged access, dormant users, publicly accessible storage containing sensitive data, and more.

DSPM monitors and tracks insights into sensitive data access based on users, roles, and geographical factors. Leveraging sensitive data intelligence and regulatory insights, DSPM establishes access policies to determine which users or roles can have specific levels of permission to access certain data, systems, or applications. Governance teams can effectively implement a least privileged access model by monitoring access parameters like inactive users or excessive access usage.

What is the data lineage, and how has it transformed over time?

Data Lineage

Data undergoes a transformation throughout its lifecycle, starting from creation and analysis to retention. For example, consider customer transaction data. When a customer makes a purchase, they provide details such as credit card numbers, names, addresses, etc. This raw data is the initial source. It is then captured by the point of sale (PoS) system. The captured data undergoes processing for transactions like tax calculations or credit card validation.

The processed data is stored in a database within the multi-cloud environment and extracted for analysis by customer experience or business intelligence teams. At some point, the same data might be shared with external business partners for advertising purposes. Finally, the data is retained for a specific period for business or legal compliance purposes.

This transformation process applies to just one dataset. Large-scale businesses experience hundreds or thousands of such transactions daily, and all the data is stored and accessed within the multi-cloud. Tracking the lineage of this data can be challenging for security teams, potentially leading to security gaps related to unauthorized data access or lack of authorization.

Data lineage is a crucial component of DSPM. It enables data and security teams to trace the changes to the data over time, providing a better understanding of how it is processed and who processes it throughout the lifecycle. Security teams can identify gaps, detect unauthorized access, and establish optimal security policies.

What misconfigurations exist within our multi-cloud environment, and how can we identify and resolve them?

Configuration Risk Management

As mentioned earlier, multi-cloud environments consist of services from different cloud providers such as AWS, Google Cloud, Azure, or Oracle Cloud Infrastructure (OCI). Each cloud service has its unique system settings and configurations. Additionally, each service provider may offer a Cloud Security Posture Management (CSPM) tool, but the tool's scope may be limited.

A single cloud environment can have numerous misconfigurations or errors, including publicly exposed storage buckets, open inbound or outbound ports, default passwords, disabled logging, and more. Now, multiply that by multiple clouds with various misconfigurations, lacking a centralized view.

An effective DSPM solution would seamlessly integrate with a wide range of IaaS and SaaS services like Azure, AWS, GCP, Snowflake, Workday, or Office 365. It would leverage custom policies or built-in rules from a library of standard security frameworks such as CIS, NIST, or PCI DSS to identify misconfigurations related to identity access controls, encryption, network settings, publicly accessible storage, and more.

Once the rules and policies are established, the DSPM tool can automatically remediate or mitigate the identified issues. For instance, if the tool detects that a GCP Cloud Storage containing sensitive data elements is publicly accessible, it will trigger the policy to update access control settings and prevent public access.

Integrate DSPM's Core Capabilities with Securiti DataControls Cloud

According to Gartner's Hype Cycle™ for Data Security 2022 report, gaining meaningful insights into data and managing risks becomes impossible if organizations view different controls, such as sensitive data context, access governance policies, data transformation, and security configuration through separate lenses.

The absence of a centralized view creates additional security, governance, and compliance risks. Therefore, it is crucial for organizations to consolidate these controls into a unified framework to obtain a comprehensive understanding of their data risks and establish effective data management and protection strategies.

Securiti DataControls Cloud has been developed to replace the fragmented approach to data security posture management with a cohesive framework. DataControls Cloud provides in-depth intelligence and visibility into an organization's data landscape, along with unified controls over their data across all cloud environments.

This consolidation of data discovery, classification and cataloging, data lineage, access governance and control, and cloud security posture management allows teams to streamline their data obligations across security, governance, privacy, and compliance functions.

In addition to integrating security controls such as misconfiguration and access, DataControls Cloud also incorporates breach response management. In the unfortunate event of a data breach, Securiti DataControls Cloud assists organizations in effectively managing risks. The tool can automatically identify affected users/identities and impacted data, determine global jurisdictions for compliance, and facilitate incident response based on regulatory facts and data-driven insights.

Furthermore, Securiti DataControls Cloud empowers organizations to implement privacy, and governance controls more efficiently, eliminating the need for scanning and classifying data multiple times for each team (security, privacy, and governance).

The isolated approach is cost-prohibitive and hinders team collaboration, making it impractical. With DataControls Cloud, organizations can consolidate their security, privacy, governance, and compliance controls into a unified view, enabling a comprehensive understanding of their data risks and obligations.