What Is Shadow Data? Examples, Risks and How to Detect It

Recently there has been a significant shift from standalone Data Security Posture Management (DSPM) solutions to comprehensive Data Security Platforms (DSPs). These platforms integrate DSPM functionality, but also encompass access governance, threat detection, and data loss prevention capabilities to provide a more holistic data protection solution. Additionally, the critical role of data in AI and LLM training requires holistic data security platforms that can manage data sensitivity, ensure security and compliance, and maintain data integrity.

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This consolidation will improve security effectiveness and help organizations manage the growing complexity of their IT environments. Originally more of a governance/compliance tool, DSPs have evolved into a critical necessity for organizations managing sensitive data in sprawling cloud environments. With the explosion of cloud adoption, stricter regulatory landscapes, and the increasing sophistication of cyber threats, DSPs will continue to evolve to address the monumental data scale expected.

DSP Addressing Modern Challenges in 2025

As the threat landscape evolves, DSP is shifting to address modern challenges. New trends such as AI integration, real-time threat detection, and cloud-native architectures are transforming how organizations approach data security. DSPM is no longer just about assuring compliance and proper data governance, it’s about mitigating all data risks, monitoring for new threats, and proactively resolving them in real time.

Must-Have DSP Features for 2025

Over the years, Data Security Platforms (DSPs) have evolved significantly, with a range of providers emerging to address the growing need for robust data security in cloud environments. Initially, smaller startups began offering innovative solutions, and in 2024, several of these providers were acquired, signaling the increasing demand for comprehensive data protection. As organizations continue to prioritize securing their cloud data, it's essential to carefully evaluate DSP solutions to ensure they meet key security needs. When assessing DSP options for 2025, certain features stand out as critical for ensuring a comprehensive and effective approach to data security.

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Below are outlined the must-have features for any DSP solution in the coming year:

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1. Cloud-Native Architecture

Modern DSPs are built for the cloud and address vast data scale with cloud-native technologies that leverage provider APIs and functions. This allows data discovery and classification to occur autonomously, within the customer cloud environment leveraging existing compute resources. Agentless approaches reduce administrative burdens as well.
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2. AI-Based Classification

AI has revolutionized data classification, providing context-aware accuracy exceeding 95%. By understanding data in its unique context, AI-driven DSP solutions ensure the right security measures are applied without overburdening teams with false positives.
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3. Anomaly Detection and Real-Time Threat Detection

Anomaly detection, powered by Data Detection and Response (DDR), identifies unusual patterns in data usage to spotlight risks such as ransomware and insider threats. Combined with real-time, data-aware detection of suspicious activities, modern DSP solutions proactively address cloud-native vulnerabilities, stopping breaches before they unfold and ensuring swift, effective action.
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4. Automatic Labeling

Manual tagging is too cumbersome and time consuming. When choosing DSP solutions, it’s critical to make sure that you choose ones that automate data tagging and labeling, seamlessly integrating with Data Loss Prevention (DLP), Secure Access Service Edge (SASE), and governance platforms. This reduces errors and accelerates compliance processes.
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5. Data Zones and Perimeters

As data moves across cloud environments, maintaining control is paramount. Leading DSP solutions monitor data movement, alerting teams when data crosses predefined perimeters or storage zones, ensuring compliance with internal and external policies.
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6. Automatic Remediation and Enforcement

Automation extends to remediation, with DSPs swiftly addressing data risks like excessive permissions or misconfigurations. By enforcing protection policies across cloud environments, organizations can prevent breaches before they occur.

The Business Case for DSP in 2025

Proactive Security

Cloud-native DSP represents a shift from reactive to proactive security practices. By identifying and addressing risks early, and across their entire data estate from cloud to on-premises, organizations can mitigate potential threats and strengthen their security posture.
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Regulatory Compliance

As regulations such as GDPR and CCPA continue to evolve, DSPM solutions play a crucial role in simplifying compliance by automating data discovery and labeling. This automation reduces the manual effort required to meet regulatory requirements. In fact, 84% of security and IT professionals consider data protection frameworks like GDPR and CCPA to be mandatory for their industries, emphasizing the growing need for automated solutions to ensure compliance.
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The Rise of Gen AI

The rise of Gen AI is expected to be a main theme in 2025. Gen AI is a driver for data proliferation in the cloud and for a transition between legacy data technologies and modern ones that require an updated data security program.
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Operational Efficiency

By automating repetitive tasks, DSPM significantly reduces the workload for security teams. This efficiency allows teams to focus on strategic initiatives rather than firefighting. According to a 2024 survey, organizations using DSPM reported a 40% reduction in time spent on manual data management tasks, demonstrating its impact on operational productivity.

Future-Proofing Your Organization with Cloud-Native DSP

To thrive in the evolving security landscape, organizations must adopt forward-looking strategies. Cloud-native DSP tools integrate seamlessly with broader security frameworks, ensuring resilience and adaptability. As technology advances, features like predictive analytics and deeper AI integration will further enhance capabilities.

Conclusion

Data security challenges are only becoming more complex, but new Data Security Platforms (DSPs) provide the tools to meet them head-on. Now is the time for organizations to take a hard look at their security posture and consider how DSPs can help them stay protected, compliant, and trusted. DSPs are quickly becoming essential to business operations, influencing strategic decisions and enabling faster, more secure innovation.
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Ready to see it in action?
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Request a demo to discover how a modern DSP can strengthen your security and support your goals.

In today’s fast-evolving cybersecurity landscape, organizations must not only deploy sophisticated security tools but also empower users to self-protect. Operationalizing this data security requires a proactive approach that integrates automation, streamlined processes, and user education. A recent discussion with Sapir Gottdiner, Cyber Security Architect at Global-e, highlighted key strategies to enhance data security by addressing alert management, sensitive data exposure, and user-driven security measures.

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As a provider of end-to-end e-commerce solutions that combine localization capabilities, business intelligence, and logistics for streamlined international expansion, Global-e makes cross-border sales as simple as domestic ones. The chosen partner of leading brands and retailers across the USA, Europe and Asia, Global-e sets the standard of global e-commerce. This requires a strong commitment to security and compliance, and Global-e must comply with a number of strict regulations.

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Automating Security Tasks for Efficiency

“One of the primary challenges faced by any security team is keeping pace with the volume of security alerts and the effort required to address them”, said Sapir. Automating human resource-constrained tasks is crucial for efficiency. For example, sensitive data should only exist in certain controlled environments, as improper data handling can lead to vulnerabilities. By leveraging DSPM which acts as a validation tool, organizations can automate the detection of sensitive information stored in incorrect locations and initiate remediation processes without human intervention.

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Strengthening Sensitive Data Protection

A concern identified in the discussion was data accessible to unauthorized personnel in Microsoft OneDrive, that may contain sensitive information. To mitigate this, organizations should automate the creation of support tickets (in Jira, for instance) for security incidents, ensuring critical and high-risk alerts are addressed immediately. Assigning these incidents to the relevant departments and data owners ensures accountability and prompt resolution. Additionally, identifying the type and location of sensitive data enables organizations to implement precise fixes, reducing exposure risks.

Risk Management and Process Improvement

Permissioning is equally important and organizations must establish clear procedures and policies for managing authentication credentials. Different actions for different levels of risk to ensure no business interruption is applicable in most cases. This can vary from easy, quick access revocation for low-risk cases while requiring manual verification for critical credentials.

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Furthermore, proper data storage is an important protection factor, given sovereignty regulations, data proliferation, etc. Implementing well-defined data mapping strategies and systematically applying proper hygiene and ensuring correct locations will minimize security gaps. For the future, Sapir envisions smart data mapping within O365 and deeper integrations with automated remediation workflow tools to further enhance security posture.

Continuous Review and Training

Sapir also suggests that to ensure compliance and effective security management, organizations should conduct monthly security reviews. These reviews help define when to close or suppress alerts, preventing unnecessary effort on minor issues. Additionally, policies should align with infrastructure security and regulatory compliance requirements such as GDPR, PCI and SOC2. Expanding security training programs is another essential step, equipping users with the knowledge on proper storage and handling of controlled data and how to avoid common security missteps. Empowering users to self-police/self-remediate allows lean security teams to scale data protection operations more efficiently.

Enhancing Communication and Future Improvements

Streamlined communication between security platforms, such as Jira and Microsoft Teams, can significantly improve incident resolution. Automating alert closures based on predefined criteria will reduce the workload on security teams. Addressing existing bugs, such as shadow IT detection issues, will further refine security processes. By fostering a culture of proactive security and leveraging automation, organizations can empower users to self-protect, ensuring a robust defense against evolving cyber threats.

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Operationalizing data security is an ongoing effort that blends automation, user education, and process refinement. By taking a strategic user-enablement approach, organizations can create a security-aware culture while minimizing risks and optimizing their security response. Since implementing Sentra’s DSPM solution, Global-e has seen significant improvement in the strength of its data security posture. The company is now able to protect its cloud data more effectively, saving its security, IT, DevOps and engineering teams time, and ensuring it remains compliant with regulatory requirements. Empowering users and data owners to take responsibility for their data security, and providing the right tools to do so easily, is a game changer to the organization.

We know that Google Workspace (formerly known as G Suite) and its assortment of services, including Gmail, Drive, Calendar, Meet, Docs, Sheets, Slides, Chat, and Vids, is a powerhouse for collaboration.

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But the big question is: Do you know where your Google Workspace data is—and if it’s secure and who has access to it?

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While Google Workspace has become an indispensable pillar in cloud operations and collaboration, its widespread adoption introduces significant security risks that businesses simply can't afford to ignore. To optimize Google Workspace data protection, enterprises must know how Google Workspace protects and classifies data. Knowing the scope, gaps, limitations, and silos of Google Workspace data protection mechanisms can help businesses strategize more effectively to mitigate data risks and ensure more holistic data security coverage across multi-cloud estates.

The Risks of Google Workspace Security

As with any dynamic cloud platform, Google Workspace is susceptible to data security risks, the most dangerous of which can do more than just undercut its benefits. Primarily, businesses should be concerned about the exposure of sensitive data nested within large volumes of unstructured data. For instance, if an employee shares a Google Drive folder or document containing sensitive data but with suboptimal access controls, it could snowball into a large-scale data security disaster. 

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Without comprehensive visibility into sensitive data exposures across Google Workspace applications, businesses risk serious security threats. Besides sensitive data exposure, these include exploitable vulnerabilities, external attacks, human error, and shadow data. Complex shared responsibility models and unmet compliance policies also loom large, threatening the security of your data. 

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To tackle these risks, businesses must prioritize and optimize data security across Google Workspace products while acknowledging that Google is rarely the sole platform an enterprise uses.

How Does Google Store Your Data?

To understand how to protect sensitive data in Google Workspace, it's essential to first examine how Google stores and manages this data. Why? Because the intricacies of data storage architectures and practices have significant implications for your security posture. 

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Here are three-steps to help you understand and optimize your data storage in Google Workspace:

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1. Know Where and How Google Stores Your Data

• Google stores your files in customized servers in secure data centers.
• Your data is automatically distributed across multiple regions, guaranteeing redundancy and availability.

2. Control Data Retention

• Google retains your Workspace data until you or an admin deletes it.
• Use Google Vault to manage retention policies and set custom retention rules for emails and files.
• Regularly review and clean up unnecessary stored data to reduce security risks.

3. Secure Your Stored Data

• Enable encryption for sensitive files in Google Drive.
• Restrict who can view, edit, and share stored documents by implementing access controls.
• Monitor data access logs to detect unauthorized access.

How Does Google Workspace Classify Your Data?

Google’s built-in classification tools are an acceptable starting point. However, they fall short of securing and classifying all unstructured data across complex cloud environments. This is because today's cloud attack surface expands across multiple providers, making security more complex than ever before. Consequently, Google's myopic classification often snowballs into bigger security problems, as data moves. Because of this evolving attack surface across multi-cloud environments, risk-ridden shadow data and unstructured data fester in Google Workspace apps. 

The Issue of Unstructured Data

It’s important to remember that most enterprise data is unstructured. Unstructured data refers to data that isn’t stored in standardized or easily manageable formats. In Google Workspace, this could be data in a Gmail draft, multimedia files in Google Drive, or other informal exchanges of sensitive information between Workspace apps. 

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For years, unstructured data has been a nightmare for businesses to map, manage, and secure. Unstructured document stores and employee GDrives are hot zones for data risks. Native Google Drive data classification capabilities can be a useful source of metadata to support a more comprehensive external data classification solution. A cloud-native DSP solution can map, classify, and organize sensitive data, including PHI, PCI, and business secrets, across both Google Workspace and cloud platforms that Google's built-in capabilities do not cover, like AWS and S3.

How Does Google Workspace Protect Your Data?

Like its built-in classification mechanisms, Google's baseline security features, such as encryption and access controls, are good for simple use cases but aren't capable enough to fully protect complex environments. 

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For both the classification and security of unstructured data, Google’s native tools may not suffice. A robust data loss prevention (DLP) solution should ideally do the trick for unstructured data. However, Google Workspace DLP alone and other protection measures (formerly referred to as G Suite data protection) are unlikely to provide holistic data security, especially in dynamic cloud environments.

Google Native Tool Challenges

Google’s basic protection measures don't tackle the full spectrum of critical Google Workspace data risks because they can't permeate unstructured documents, where sensitive data may reside in various protected states.

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For example, an employee's personal Google Drive can potentially house exposed and exploitable sensitive data that can slip through Google's built-in security mechanisms. It’s also important to remember that Google Workspace data loss prevention capabilities do nothing to protect critical enterprise data hosted in other cloud platforms. 

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Ultimately, while Google provides some security controls, they alone don’t offer the level of protection that today’s complex cloud environments demand. To close these gaps, businesses must look to complement Google’s built-in capabilities and invest in robust data security solutions.

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Only a highly integrable data security tool with advanced AI and ML capabilities can protect unstructured data across Google Workspace’s diverse suite of apps, and further, across the entire enterprise data estate. This has become mandatory since multi-cloud architectures are the norm today.

A Robust Data Security Platform: The Key to Holistic Google Workspace Data Protection 

The speed, complexity, and rapid evolution of multi-cloud and hybrid cloud environments demand more advanced data security capabilities than Google Workspace’s native storage, classification, and protection features provide. 

It is becoming increasingly difficult to mitigate the risks associated with sensitive data.

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To successfully remediate these risks, businesses urgently need robust data security posture management (DSPM) and data detection and response (DDR) solutions - preferably all in one platform. There's simply no other way to guarantee comprehensive data protection across Google Workspace. Furthermore, as mentioned earlier, most businesses don't exclusively use Google platforms. They often mix and match services from cloud providers like Google, Azure, and AWS.

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In other words, besides limited data classification and protection, Google's built-in capabilities won't be able to extend into other branches of an enterprise's multi-cloud architecture. And having siloed data security tools for each of these cloud platforms increases costs and further complicates administration that can lead to critical coverage gaps. That's why the optimal solution is a holistic platform that can fill the gaps in Google's existing capabilities to provide unified data classification, security, and coverage across all other cloud platforms.

Sentra: The Ultimate Cloud-Agnostic Data Protection and Classification Solution 

To truly secure sensitive data across Google Workspace and beyond, enterprises need a cloud-native data security platform. That’s where Sentra comes in. It hands you enterprise-scale data protection by seamlessly integrating powerful capabilities like data discovery and classification, data security posture management (DSPM), data access governance (DAG), and data detection and response (DDR) into an all-in-one, easy-to-use platform.

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By combining rule-based and large language model (LLM)-based classification, Sentra ensures accurate and scalable data security across Workspace apps like Google Drive—as well as data contained in apps from other cloud providers. This is crucial for any enterprise that hosts its data across disparate cloud platforms, not just Workspace. To classify unstructured data across these platforms, Sentra leverages supervised AI training models like BERT. It also uses zero-shot classification techniques to zero in on and accurately classify unstructured data. 

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Sentra is particularly useful for anyone asking business-, industry-, or geography-specific data security questions such as “Does Google Workspace have HIPAA compliance frameworks?” and “Is my organization's use of Google Workspace GDPR-compliant?” The short answer to these questions: Integrate Sentra with your Google Workspace apps and you will see. 

Boost Your Google Workspace Data Protection with Sentra

By integrating Sentra with Google Workspace, companies can leverage AI-driven insights to distinguish employee data from customer data, ensuring a clearer understanding of their information landscape. Sentra also identifies customer-specific data types, such as personally identifiable information (PII), protected health information (PHI), product IDs, private codes, and localization requirements. Additionally, it detects toxic data combinations that may pose security risks.

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Beyond insights, Sentra provides robust data protection through comprehensive inventorying and classification of unstructured data. It helps organizations right-size permissions, expose shadow data, and implement real-time detection of sensitive data exposure, security breaches, and suspicious activity, ensuring a proactive approach to data security.

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No matter where your unstructured data resides, whether in Google Drive or any other cloud service, Sentra ensures it is accurately identified, classified, and protected with over 95% precision.

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If you’re ready to take control of your data security, book a demo to discover how Sentra’s AI-driven protection secures your most valuable information across Google Workspace and beyond.