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How DSPM Reduces the Risk of Data Breaches

February 22, 2023
4
Min Read
Data Security

The movement of more and more sensitive data to the cloud is driving a cloud data security gap – the chasm between the security of cloud infrastructure and the security of the data housed within it. This is one of the key drivers of the Data Security Posture Management (DSPM) model and why more organizations are adopting a data-centric approach.

 

Unlike Cloud Security Posture Management (CSPM) solutions, which were purpose-built to protect cloud infrastructure by finding vulnerabilities in cloud resources, DSPM is about the data itself. CSPM systems are largely data agnostic – looking for infrastructure vulnerabilities, then trying to identify what data is vulnerable because of them. DSPM provides visibility into where sensitive data is, who can access that data, how it was used, and how robust the data store or application security posture is.

On a fundamental level, the move to DSPM reflects a recognition that in hybrid or cloud environments, data is never truly at rest. Data moves to different cloud storage as security posture shifts, then moves back. Data assets are copied for testing purposes, then erased (or not) and are frequently forgotten. This leaves enterprises large and small scrambling to track and assess sensitive data and its security throughout the data lifecycle and across all cloud environments.

The data-centric approach of DSPMs is solely focused on the unique challenges of securing cloud data. It does this by making sure that sensitive data always has the correct security posture - regardless of where it’s been duplicated or moved to. DSPM ensures that sensitive data is always secured by providing automatic visibility, risk assessment, and access analysis for cloud data - no matter where it travels.

Because of this, DSPM is well-positioned to reduce the risk of catastrophic data breaches and data exposure, in three key ways:

  1. Finding and eliminating shadow data to reduce the data attack surface:

    Shadow data is any data that has been stored, copied, or backed up in a way that does not subject it to your organization’s data management framework or data security policies. Shadow data may also not be housed according to your preferred security structure, may not be subject to your access control limitations, and it may not even be visible to the tools you use to monitor and log data access.

    Shadow data is basically data in the wrong place, at the wrong time. And it is gold for attackers – publicly accessible sensitive data that nobody really knows is there. Aside from the risk of breach, shadow data is an extreme compliance risk. Even if an organization is unaware of the existence of data that contains customer or employee data, intellectual property, financial or other confidential information – it is still responsible for it.

    Where is all this shadow data coming from? Aside from data that was copied and abandoned, consider sources like decommissioned legacy applications – where historical customer data or PII is often just left sitting where it was originally stored. And there is also data produced by shadow IT applications, or databases used by niche app. And what about cloud architecture changes? When data is lifted and shifted, unmanaged or orphaned backups that contain sensitive information often remain.

    DSPM solutions locate shadow data by looking for it where it’s not supposed to be. Then, DSPM solutions provide actionable guidance for deletion and/or remediation. Advanced DSPM solutions search for sensitive information across different security postures, and can also discover when multiple copies of data exist. What’s more, DSPM solutions scrutinize privileges across multiple copies of data, identifying who can access data and who should not be able to.
  2. Identifying over-privileged users and third parties:

    Controlling access to data has always been one of the basics of cybersecurity hygiene. Traditionally, enterprises have relied on three basic types of access controls for internal users and third parties:

    · Access Control Lists - Straight lists of which users have read/write access
    · Role Based Access Control (RBAC) - Access according to what roles the user has in the organization
    · Attribute Based Access Control (ABAC) – Access determined by the attributes a user must have - job title, location, etc.

    Yet traditional data access controls are tied to one or more data stores or databases – like a specific S3 bucket. RBAC or ABAC policies ensure only the right users have permissions at the right times to these assets. But if someone copies and pastes data from that bucket to somewhere else in the cloud environment, what happens to the RBAC or ABAC policy? The answer is simple: it no longer applies to the copied data. DSPM solves this by ensuring that access control policy travels with data, across both cloud environments. Essentially, DSPM extends access control across any environment by enabling admins to understand where data came from, who originally had access to it, and who has access now.
  3. Identifying data movement, making sure security posture follows:

    Data moves through the public cloud – it’s the reason the cloud is so efficient and productive. It lets people use data in interesting ways. Yet the distributed nature of cloud computing means that organizations may not understand exactly where all applications and data are stored. Third-party hosting places serious limits on the visibility of data access and sharing, and multi-cloud environments frequently suffer from inconsistent security regimes.

    Basically, similar to the access control challenges - when data moves across the cloud, its security posture doesn’t necessarily follow. DSPM solves this by noticing when data moves and how its security posture changes. By focusing on finding and securing sensitive data, as opposed to securing cloud infrastructure or applications, DSPM solutions first discover sensitive data (including shadow or abandoned data), classify data types using AI models, then determine whether the data has the proper security posture. If it doesn’t, DSPM solutions notify the relevant teams and coordinate remediation.

DSPM Secures Your Cloud Data

Data security in the cloud is  a growing challenge. And contrary to some perceptions – the security for data created in the cloud, sent to the cloud, or downloaded from the cloud is not the responsibility of the cloud provider (AWS, Azure, GCP, etc.). This responsibility falls squarely on the shoulders of the cloud customer.

More and more organizations are choosing the DSPM paradigm to secure cloud data. In this dynamic and highly-complex ecosystem, DSPM ensures that sensitive data always has the correct security posture – no matter where it’s been duplicated or moved to. This dramatically lowers the risk of catastrophic data leaks, and dramatically raises user and admin confidence in data security.

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Yair brings a wealth of experience in cybersecurity and data product management. In his previous role, Yair led product management at Microsoft and Datadog. With a background as a member of the IDF's Unit 8200 for five years, he possesses over 18 years of expertise in enterprise software, security, data, and cloud computing. Yair has held senior product management positions at Datadog, Digital Asset, and Microsoft Azure Protection.

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Ward Balcerzak
Ward Balcerzak
December 11, 2025
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US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

US State Privacy Laws 2026: DSPM Compliance Requirements & What You Need to Know

By 2026, American data privacy will look very different as a wave of new state laws redefines what it means to protect sensitive information. Organizations face a regulatory maze: more than 20 states will soon require not only “reasonable security” but also Data Protection Impact Assessments (DPIAs), explicit limits on data collection, and, in some cases, detailed data inventories. These requirements are quickly becoming standard, and ignoring them simply isn’t an option. The risk of penalties and enforcement actions is climbing fast.

But through all these changes, one major question remains: How can any organization comply if it doesn’t even know where its most sensitive data is? Data Security Posture Management (DSPM) has become the solution, making data visibility and automation central for meeting ongoing compliance needs.

Mapping the New Wave of State Privacy Mandates

Several state privacy laws going into effect in 2025 and 2026 are raising the stakes for compliance. Kentucky, Indiana, and Rhode Island’s new laws, effective January 1, 2026, require both security measures and DPIAs for handling high-risk or sensitive data. Minnesota’s law stands out even more: it moves past earlier vague “reasonable” security language and mandates comprehensive data inventories.

Other key states include Minnesota, which explicitly requires data inventories, Maryland with strict data minimization rules, and Tennessee, which gives organizations an affirmative defense if they’ve adopted a NIST-aligned privacy program. These requirements mean organizations now need to track what data they collect, know exactly where it’s stored, and show evidence of compliance when asked. If your organization operates in more than one state, keeping up with this web of laws will soon become impossible without dedicated solutions (US consumer privacy laws 2025 update).

Why Data Visibility is Now Foundational to Compliance

To meet DPIA, minimization, and security safeguard rules, you need full visibility into where sensitive or regulated data lives - and how it moves across your environment. Recent privacy laws are moving closer to GDPR-like standards, with DPIAs required not only for biometric data but also for broad categories like targeted advertising and profiling. Minnesota leads with its clear requirement for full data inventories, setting the standard that you can’t prove compliance unless you understand your data (US cybersecurity and data privacy review and outlook 2025).

This shift puts DSPM front and center: you now need ongoing discovery and classification of your entire sensitive data footprint. Without a strong data foundation, organizations will find it hard to complete DPIAs, handle audits, or defend themselves in investigations.

Automation: The Only Viable Path for Assessment and Audit Readiness

State privacy rules are getting more complicated, and many enforcement authorities are shortening or removing 'right-to-cure' periods. That means manual compliance simply won’t keep up. Automation is now the only way to manage compliance as regulations tighten (5 trends to watch: 2025 US data privacy & cybersecurity).

With DSPM and automation, organizations get ongoing discovery, real-time data classification, and instant evidence collection - all required for fast DPIAs and responsive audits. For companies facing regulators or preparing for multi-state oversight, this means you already have the proof and documentation you need. Relying on spreadsheets or one-time assessments at this point only increases your risk.

Sentra: Your Strategic Bridge to Privacy Law Compliance

Sentra’s DSPM platform is built to tackle these expanding privacy law requirements. The agentless platform covers AWS, Azure, GCP, SaaS, and hybrid environments, removing both visibility gaps and the hassle found in older solutions (Sentra: DSPM for compliance use cases).

With continuous, automated discovery and data classification, you always know exactly where your sensitive data is, how it moves, and how it’s being protected. Sentra’s integrated Data Detection & Response (DDR) catches and fixes risks or policy violations early, closing gaps before regulators - or attackers - can take advantage (Sensitive data exposure insight). Combined with clear reporting and on-demand audit documentation, Sentra helps you meet new state privacy laws and stay audit-ready, even as your business or data needs change.

Conclusion

The arrival of new state privacy laws in 2025 and 2026 is changing how organizations must handle sensitive data. Security safeguards, DPIAs, minimization, and full inventories are now required - not just nice-to-have.

DSPM is now a compliance must-have. Without complete data visibility and automation, following the web of state rules isn’t difficult - it’s impossible. Sentra’s agentless, multi-cloud platform keeps your organization continuously informed, giving compliance, security, and privacy teams the control they need to keep up with new regulations.

Want to see how your organization stacks up for 2026 laws? Book a DSPM Compliance Readiness Assessment or check out Sentra’s automated DPIA tools today.

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David Stuart
David Stuart
Gilad Golani
Gilad Golani
December 4, 2025
3
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Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Zero Data Movement: The New Data Security Standard that Eliminates Egress Risk

Cloud adoption and the explosion of data have boosted business agility, but they’ve also created new headaches for security teams. As companies move sensitive information into multi-cloud and hybrid environments, old security models start to break down. Shuffling data for scanning and classification adds risk, piles on regulatory complexity, and drives up operational costs.

Zero Data Movement (ZDM) offers a new architectural approach, reshaping how advanced Data Security Posture Management (DSPM) platforms provide visibility, protection, and compliance. This post breaks down what makes ZDM unique, why it matters for security-focused enterprises, and how Sentra provides an innovative agentless and scalable design that is genuinely a zero data movement DSPM .

Defining Zero Data Movement Architecture

Zero Data Movement (ZDM) sets a new standard in data security. The premise is straightforward: sensitive data should stay in its original environment for security analysis, monitoring, and enforcement. Older models require copying, exporting, or centralizing data to scan it, while ZDM ensures that all security actions happen directly where data resides.

ZDM removes egress risk -shrinking the attack surface and reducing regulatory issues. For organizations juggling large cloud deployments and tight data residency rules, ZDM isn’t just an improvement - it's essential. Groups like the Cloud Security Alliance and new privacy regulations are moving the industry toward designs that build in privacy and non-stop protection.

Risks of Data Movement: Compliance, Cost, and Egress Exposure

Every time data is copied, exported, or streamed out of its native environment, new risks arise. Data movement creates challenges such as:

  • Egress risk: Data at rest or in transit outside its original environment  increases risk of breach, especially as those environments may be less secure.
  • Compliance and regulatory exposure: Moving data across borders or different clouds can break geo-fencing and privacy controls, leading to potential violations and steep fines.
  • Loss of context and control: Scattered data makes it harder to monitor everything, leaving gaps in visibility.
  • Rising total cost of ownership (TCO): Scanning and classification can incur heavy cloud compute costs - so efficiency matters.  Exporting or storing data, especially shadow data, drives up storage, egress, and compliance costs as well.

As more businesses rely on data, moving it unnecessarily only increases the risk - especially with fast-changing cloud regulations.

Legacy and Competitor Gaps: Why Data Movement Still Happens

Not every security vendor practices true zero data movement, and the differences are notable. Products from Cyera, Securiti, or older platforms still require temporary data exporting or duplication for analysis. This might offer a quick setup, but it exposes users to egress risks, insider threats, and compliance gaps - problems that are worse in regulated fields.

Competitors like Cyera often rely on shortcuts that fall short of ZDM’s requirements. Securiti and similar providers depend on connectors, API snapshots, or central data lakes, each adding potential risks and spreading data further than necessary. With ZDM, security operations like monitoring and classification happen entirely locally, removing the need to trust external storage or aggregation. For more detail on how data movement drives up risk.

The Business Value of Zero Data Movement DSPM

Zero data movement DSPM changes the equation for businesses:

  • Designed for compliance: Data remains within controlled environments, shrinking audit requirements and reducing breach likelihood.
  • Lower TCO and better efficiency: Eliminates hidden expenses from extra storage, duplicate assets, and exporting to external platforms.
  • Regulatory clarity and privacy: Supports data sovereignty, cross-border rules, and new zero trust frameworks with an egress-free approach.

Sentra’s agentless, cloud-native DSPM provides these benefits by ensuring sensitive data is never moved or copied. And Sentra delivers these benefits at scale - across multi-petabyte enterprise environments - without the performance and cost tradeoffs others suffer from. Real scenarios show the results: financial firms keep audit trails without data ever leaving allowed regions. Healthcare providers safeguard PHI at its source. Global SaaS companies secure customer data at scale, cost-effectively while meeting regional rules.

Future-Proofing Data Security: ZDM as the New Standard

With data volumes expected to hit 181 zettabytes in 2025, older protection methods that rely on moving data can’t keep up. Zero data movement architecture meets today's security demands and supports zero trust, metadata-driven access, and privacy-first strategies for the future.

Companies wanting to avoid dead ends should pick solutions that offer unified discovery, classification and policy enforcement without egress risk. Sentra’s ZDM architecture makes this possible, allowing organizations to analyze and protect information where it lives, at cloud speed and scale.

Conclusion

Zero Data Movement is more than a technical detail - it's a new architectural standard for any organization serious about risk control, compliance, and efficiency. As data grows and regulations become stricter, the old habits of moving, copying, or centralizing sensitive data will no longer suffice.

Sentra stands out by delivering a zero data movement DSPMplatform that's agentless, real-time, and truly multicloud. For security leaders determined to cut egress risk, lower compliance spending, and get ahead in privacy, ZDM is the clear path forward.

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Charles Garlow
Charles Garlow
December 3, 2025
3
Min Read

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

Petabyte Scale is a Security Requirement (Not a Feature): The Hidden Cost of Inefficient DSPM

As organizations scramble to secure their sprawling cloud environments and deploy AI, many are facing a stark realization: handling petabyte-scale data is now a basic security requirement. With sensitive information multiplying across multiple clouds, SaaS, and AI-driven platforms, security leaders can't treat true data security at scale as a simple add-on or upgrade.

At the same time, speeding up digital transformation means higher and less visible operational costs for handling this data surge. Older Data Security Posture Management (DSPM) tools, especially those boasting broad, indiscriminate scans as evidence of their scale, are saddling organizations with rising cloud bills, slowdowns, and dangerous gaps in visibility. The costs of securing petabyte-scale data are now economic and technical, demanding efficiency instead of just scale. Sentra solves this with a highly-efficient cloud-native design, delivering 10x lower cloud compute costs.

Why Petabyte Scale is a Security Requirement

Data environments have exploded in both size and complexity. For Fortune 500 companies, fast-growing SaaS providers, and global organizations, data exists across public and hybrid clouds, business units, regions, and a stream of new applications.

Regulations such as GDPR, HIPAA, and rules from the SEC now demand current data inventories and continuous proof of risk management. In this environment, defending data at the petabyte level is now essential. Failing to classify and monitor this data efficiently means risking compliance and losing business trust. Security teams are feeling the strain. I meet security teams everyday and too many of them still struggle with data visibility and are already seeing the cracks forming in their current toolset as data scales.

The Hidden Cost of Inefficient DSPM: API Calls and Egress Bills

How DSPM tools perform scanning and discovery drives the real costs of securing petabyte-scale data. Some vendors highlight their capacity to scan multiple petabytes daily. But here's the reality: scanning everything, record by record, relying on huge numbers of API calls, becomes very expensive as your data estate grows.

Every API call can rack up costs, and all the resulting data egress and compute add up too. Large organizations might spend tens of thousands of dollars each month just to track what’s in their cloud. Even worse, older "full scan" DSPM strategies jam up operations with throttling, delays, and a flood of alerts that bury real risk. These legacy approaches simply don’t scale, and organizations relying on them end up paying more while knowing less.

 

Cyera’s "Petabyte Scale" Claims: At What Cloud Cost?

Cyera promotes its tool as an AI-native, agentless DSPM that can scan as much as 2 petabytes daily . While that’s an impressive technical achievement, the strategy of scanning everything leads directly to massive cloud infrastructure costs: frequent API hits, heavy egress, and big bills from AWS, Azure, and GCP.

At scale, these charges don’t just appear on invoices, they can actually stop adoption and limit security’s effectiveness. Cloud operations teams face API throttling, slow results, and a surge in remediation tickets as risks go unfiltered. In these fast-paced environments, recognizing the difference between a real threat and harmless data comes down to speed. The Bedrock Security blog points out how inefficient setups buckle under this weight, leaving teams stuck with lagging visibility and more operational headaches.

Sentra’s 10x Efficiency: Optimized Scanning for Real-World Scale

Sentra takes another route to manage the costs of securing petabyte-scale data. By combining agentless discovery with scanning guided by context and metadata, Sentra uses pattern recognition and an AI-driven clustering algorithm designed to detect machine-generated content—such as log files, invoices, and similar data types. By intelligently sampling data within each cluster, Sentra delivers efficient scanning while reducing scanning costs.

This approach enables data scanning to be prioritized based on risk and business value, rather than wasting time and money scanning the same data over and over again, skipping unnecessary API calls, lowering egress, and keeping cloud bills in check.

Large organizations gain a 10x efficiency edge: quicker classification of data, instant visibility into actual threats, lower operational expenses, and less demand on the network. By focusing attention only where it matters, Sentra matches data security posture management to the demands of current cloud growth and regulatory requirements.

This makes it possible for organizations to hit regulatory and audit targets without watching expenses spiral or opening up security gaps.Sentra offers multiple sampling levels, Quick (default), Moderate, Thorough, and Full, allowing customers to tailor their scanning strategy to balance cost and accuracy. For example, a highly regulated environment can be configured for a full scan, while less-regulated environments can use more efficient sampling. Petabyte-scale security gives the user complete control of their data enterprise and turns into something operationally and financially sustainable, rather than a technical milestone with a hidden cost. 

Efficiency is Non-Negotiable

Fortune 500 companies and digital-first organizations can’t treat efficiency as optional. Inefficient DSPM tools pile on costs, drain resources, and let vulnerabilities slip through, turning their security posture into a liability once scale becomes a factor. Sentra’s platform shows that efficiency is security: with targeted scanning, real context, and unified detection and response, organizations gain clarity and compliance while holding down expenses.

Don’t let your data protection approach crumble under petabyte-scale pressure. See what Sentra can do, reduce costs, and keep essential data secure - before you end up responding to breaches or audit failures.

Conclusion

Securing data at the petabyte level isn't some future aspiration - it's the standard for enterprises right now. Treating it as a secondary feature isn’t just shortsighted; it puts your company at risk, financially and operationally.

The right DSPM architecture brings efficiency, not just raw scale. Sentra delivers real-time, context-rich security posture with far greater efficiency, so your protection and your cloud spending can keep up with your growing business. Security needs to grow along with scale. Rising costs and new risks shouldn’t grow right alongside it.

Want to see how your current petabyte security posture compares? Schedule a demo and see Sentra’s efficiency for yourself.

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