The Need to Switch From an Infrastructure to a Data-First Approach
Traditionally, organizations heavily relied on Cloud Security Posture Management (CSPM) solutions to fill the cloud security gap. These solutions are built for infrastructure. The solution scans cloud resources to discover misconfigurations using automated checks mapped to various security and compliance standards.
CSPM is inherently a data-agnostic solution. In other words, CSPM can't tell which misconfigured systems contain sensitive data.
It's a very efficient way of protecting data in the cloud, as security teams have to treat each misconfiguration of the data system as an equal priority risk. This means security teams with limited resources don't know which data system misconfiguration to fix first. Due to the inefficiencies of protecting data with CSPM, a lot of sensitive data remains exposed due to unresolved misconfiguration of data systems, thus giving an advantage to attackers and increasing the risk of data breaches.
The data breach survey mentioned earlier is a prime example illustrating why organizations need DSPM.
The “Mother of All Breaches” is yet another recent - more likely a historic - case that sheds light on the significance of embracing a data-centric approach to cloud data security.
The year 2024 began with a colossal incident known as the “Mother of All Breaches.” An unprecedented massive data breach resulted in the leak of 26 billion records containing sensitive and confidential data. The pervasive data breach included sensitive data from the world’s leading platforms and confidential records from government organizations in the US, Brazil, and the Philippines, to name a few.
The staggering volume of the breach has left millions of users globally vulnerable to threats like unauthorized access, identity theft, and other targeted attacks. Notably, it was reported that the cause of the breach was a firewall misconfiguration.
This incident draws the attention of the cloud data security community to one critical concern- how to protect data wherever it lives in public, private, or hybrid multi-cloud.
Bridging the Cloud Data Security Gap with DSPM
Unlike the traditional CSPM solution, where the focus is on the infrastructure, DSPM’s focus is data. As defined by Gartner, Data Security Posture Management is a process that provides “visibility as to where sensitive data is, who has access to that data, how it has been used, and what the security posture of the data store or application is.”
DSPM solutions are built to provide controls for tackling the challenges unique to cloud data protection. For instance,
- The solution evolves the ability to discover unknown or shadow data in the cloud. This is the data that is duplicated, copied, or backed up across different environments, but it is not controlled by any data management framework or security policies. This data may exist with no appropriate security configurations or access entitlements that put it at serious risk. Apart from security, shadow data also poses compliance risks, which may lead to regulatory fines.
- DSPM also helps teams identify security and privacy risks to data across the environment. It tracks and analyzes potential access and misconfiguration risks associated with sensitive data.
- In multi-cloud settings, data flow is dynamic. Copies of data are created across the cloud platforms, where some are duplicated, some are removed, and some are forgotten (shadow data). This presents a paramount challenge for organizations to effectively monitor and evaluate the security posture of the data across its lifecycle. DSPM enables teams to overcome this challenge through mapping and data lineage automation.
All in all, DSPM helps organizations ensure that sensitive data remain protected by providing comprehensive data intelligence, risk assessment, entitlements visibility, and data flow analysis - regardless of where data moves.
Because of these capabilities, DSPM is an ideal solution to reduce and mitigate the risks of data security breaches.
Mitigate the Risk of Breaches with DSPM
The following are the key DSPM capabilities and processes that efficiently tackle the unique challenges of cloud data protection and mitigate data breach consequences.
Discover & Catalog All Data Assets
The first step to protecting data is to understand where it is located, which is not possible without first discovering and cataloging the data assets across the environment.
While cloud service providers (CSPs) offer basic visibility into native data assets, it is challenging to track and catalog non-native or shadow data assets that are unknown to IT teams.
DSPM enables teams to discover, identify, and inventory all the assets across public environments, including IaaS and PaaS. It does so by leveraging native and non-native connectors across diverse systems.
Provide Sensitive Data Intelligence
Discovering sensitive data and classifying it accurately using labels and tagging is challenging. Organizations hold petabyte-scale data, which is further formatted across structured, semi-structured, and unstructured formats. Traditional classification tools fail due to a lack of scalability, inaccuracy, and false positives.
Advanced DSPM solutions use AI techniques, such as Natural Language Processing (NLP) algorithms, to classify sensitive data at scale accurately. Better data visibility makes it easier to understand how much sensitive data they have and what could be the risk if they get breached. This allows them to prioritize investments for data security.
Prioritize Data Misconfigurations
CSPM solutions may provide an understanding of the cloud infrastructure security posture but it is difficult to operationalize efficiently due to alert fatigue and false positives.
Together with DSPM, organizations can map system misconfiguration insights with data classification tags and labels. These insights enable teams to place appropriate controls, reduce false positives, and prioritize systems based on data sensitivity. Reducing misconfigured data systems with sensitive data prevents public exposure of sensitive data.
Govern Data Access by Identities
Implementing a robust zero-trust architecture is not feasible without automation and data classification insights. For efficient access governance, organizations need to understand the identities accessing data and the level of permission required for certain sensitive data sets.
DSPM helps organizations fine-tune access permissions with comprehensive access insights and automated controls. It streamlines secure data sharing through dynamic data masking based on sensitive data. Dynamic masking further protects data integrity and confidentiality in case of unauthorized access or any other data security breach consequences.
Access controls ensure that only the people and machines who need sensitive data access have those permissions. By reducing the number of people and machines with sensitive data access, you help reduce the attack surface. Security teams now need to make sure that these users and machines are adequately protected.
Honor People’s Data Privacy
In the event of a breach, it is important to understand the impact of the breach, the data sets impacted, and the individuals with whom the data is associated. However, as data is scattered across multi-cloud environments, organizations find it difficult to track and map data to the rightful individual.
A comprehensive Data Security Posture Management solution should offer an intelligence linking mechanism that maps data - no matter where it is - to the relevant individual. This intelligence further streamlines privacy operations related to data subject rights fulfillment, breach analysis and notification, and cross-border data transfers.
Ensure Consistent Security Controls Across Data Flows
To keep track of data transformations across its lifecycle, organizations must map their data processing and understand data lineage. These insights enable organizations to understand how data moves between data assets, copied, backed up, or transformed at different stages. By understanding this, organizations can automate appropriate controls and policies for data movement across the environment.
Data security controls across the flow ensure that each environment through which data flows is adequately protected. Ensures that there are no weak links for an attacker to exploit.
All in all, DSPM orchestrates better data security controls, enabling organizations to reduce the risk of data breaches. Organizations should integrate DSPM as a key component of their cloud security architecture alongside other data security solutions.
Go Beyond DSPM with Data Command Center
While most DSPM solutions can discover and catalog sensitive data across public clouds, they don’t cover security gaps in other environments.
Securiti Data Command Center offers a more comprehensive approach to protecting data everywhere, including public clouds, private clouds, data lakes and warehouses, SaaS applications, and even streaming data systems. The solution leverages real-time contextual data insights that improve security posture across hybrid multicloud environments with accurate data classification powered by AI.
The Data Command Center also supports Data Security Platform (DSP) functions, AI Security & Governance, and unified controls for Data Privacy, Governance, and Compliance.
A comprehensive, unified Data Command Center can help organizations:
- Discover cloud native and shadow data systems with support for thousands of data systems.
- Classify sensitive data at scale with high accuracy.
- Leverage hundreds of predefined policies to enhance the security posture of sensitive data.
- Enforce least-privilege data access controls and dynamic data masking.
- Automate privacy operations.
- Enable AI Trust, Risk, and Security Management (AI TRiSM) across machine learning models (MLMs) deployed in the cloud and SaaS apps.
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Frequently Asked Questions about DSPM Data Breaches