Organizations can no longer rely on perimeter-based security to protect their most valuable asset: data. As information moves across cloud platforms, users and services, the ability to control and secure data itself has become the defining factor in effective cyber protection.
This shift is already playing out in real-world environments. Modern organizations operate across technology environments that are far more distributed than ever before. Cloud adoption and hybrid work patterns continue to expand, and the wider use of interconnected digital services means data now moves across many trust boundaries and locations before reaching its intended destination.
As this trend accelerates, the security measures that once relied on traditional network controls provide less protection than many assume. You can no longer rely on a firewall to stop attackers if they can access data through stolen credentials, misconfigured storage, or weak controls governing how information is shared. Attackers no longer need to breach a perimeter if data can be accessed through compromised credentials, unmonitored storage locations, or weak controls governing how information is shared.
To address these important challenges, the concept of data-centric security has emerged. Instead of focusing on the infrastructure that surrounds information, it prioritizes safeguards that apply directly to the data itself, regardless of where it travels or who attempts to use it. The objective is to ensure your data remains protected even when traditional security layers fail or when infrastructure is outside your direct control.
Data-centric security emphasises protecting the data itself rather than relying on the systems that host or transport it. This means applying controls that remain effective even as data moves between applications, locations or users.
In practice, a data-centric approach means:
Using encryption helps ensure that information cannot be read without the appropriate permissions, while strong identity and access controls limit who can access sensitive material. Classification policies guide how data should be handled throughout its lifecycle, and monitoring tools provide visibility into how information is being accessed or shared. Collectively, these measures focus protection on the asset that matters most, reducing security's dependence on the reliability of surrounding infrastructure.
In this context, a major blind spot for many organizations is a continued reliance on security measures that seek to contain threats at a defined boundary. This model assumes attackers will try to break in from the outside. In reality, they often just log in. The approach works less effectively as infrastructure becomes more distributed and as data moves across cloud platforms, remote locations and external services. Attackers can now bypass traditional perimeter controls by using compromised credentials or by exploiting weaknesses in systems that sit outside the direct oversight of security teams.
A further challenge is the perennial issues presented by zero-day malware. Traditional antivirus tools depend on known signatures and behavioural indicators, meaning they may not detect new or modified threats. Sandboxing provides another layer of defence, but it can be evaded through delayed activation or techniques designed to avoid analysis. This leaves you reacting to threats after they have already entered the environment.
Insider activity and configuration errors also contribute to the problem. In many cases, data exposure occurs not through deliberate misuse but through incorrect settings or inconsistent policy application. As environments expand, these mistakes become harder to spot and easier to exploit, creating additional opportunities for attackers to gain access without breaching a perimeter.
As a result, many organizations face the same recurring issues:
Instead, a data-centric approach depends on strong identity and access governance. At its core are technologies and processes that ensure only verified users and devices can access sensitive information. This limits the damage credential theft can cause and reduces the risk of unauthorised access.
Policy-based control is also critical. By setting rules for how information should be handled in different contexts, organizations can apply consistent safeguards as data moves between systems or is shared with external parties. These policies guide storage, transfer, and use to help prevent accidental exposure.
Continuous visibility adds another layer of assurance. Monitoring how data is accessed or modified provides early warning of unusual behaviour and supports investigations if an issue arises. This level of insight becomes essential as cloud platforms and distributed applications increase the number of potential access points.
And crucially, proactive threat removal is essential for reducing reliance on reactive detection tools. Ensuring files are safe before they enter your environment removes opportunities for attackers to exploit hidden threats or structural weaknesses. This strengthens overall resilience and complements other elements of a data-centric strategy.
For government and private sector organizations driven by a Zero Trust approach to security, a data-centric model supports this by ensuring that protection applies directly to the information being accessed. When controls follow the data, verification becomes more consistent and less dependent on network boundaries.
This has a direct impact on how organizations limit movement within their environments. If access to data is tightly governed, attackers hit dead ends sooner. They may gain access to an endpoint or system, but their ability to reach sensitive information is far more limited.
Data-centric security also supports Zero Trust by maintaining protection across different locations. As information moves between cloud platforms, remote users or external services, the same rules and safeguards apply. This reduces the risk that data will be exposed when it leaves a controlled network or passes through infrastructure not managed by the organization.
In many data-centric strategies, file-based threats remain a significant weakness. Attackers frequently use common document formats to deliver hidden malware or exploit structural vulnerabilities that are difficult to detect through traditional tools. These issues can arise even in well-governed environments, as files often originate from external sources or pass through systems that fall outside direct organizational control. Treating every file as untrusted is essential for reducing this risk.
Glasswall’s Content Disarm and Reconstruction (CDR) technology addresses this by validating and rebuilding files to a known good standard. Instead of attempting to identify malicious content, the process focuses on ensuring that each file conforms to its manufacturer’s specification. Any deviations are removed, and the resulting file is delivered in a clean, fully functional state. This shifts protection from detection to prevention.
Glasswall CDR is particularly effective when:
By integrating proactive file protection into a data-centric model, organizations can close a gap that is often exploited by attackers and strengthen alignment with Zero Trust principles.
For organizations everywhere, a shift toward data-centric security reflects the realities of how they now operate. Information moves through a wide range of environments, and traditional perimeter measures offer limited protection when threats can emerge from many different points. Attackers target data, not infrastructure.
By focusing on controls that apply directly to the data, organizations can maintain stronger oversight and reduce the opportunities available to attackers.
See how Glasswall CDR enforces Zero Trust at the file level. Book a demo.
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David is a technology copywriter with over 25 years’ experience. Passionate about technology and solving real-world challenges, he excels at weaving customer stories into compelling narratives that resonate and inspire action.
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