Demystifying Data Protection in the Cloud: Runtime vs. At Rest

Combining at-rest and runtime protection creates a holistic and resilient security posture, ensuring your organization’s data is fully protected in today’s complex cloud landscape.

In the dynamic landscape of data security, navigating the complexities of modern architectures requires a sophisticated approach. The exponential growth of data and the proliferation of cloud services require advanced security strategies that can adapt to rapidly changing conditions.

Traditional methods of data protection, while foundational, often fall short in addressing the needs of today’s fast-paced cloud environments. To achieve true full protection, organizations must embrace a dual approach that integrates both at-rest and runtime protection. This blog aims to elucidate these concepts, providing a deeper understanding of their importance and how they can be harmonized to enhance overall security and proactive threat mitigation.

Protecting Data at Rest: Is It Enough?

There’s an industry-wide myth that data can be fully protected by securing the infrastructure where it resides — i.e., by protecting data while it’s at rest. While this is crucial for preventing unauthorized access, ensuring compliance and maintaining basic security hygiene, it’s not enough to achieve full data security. You could say it’s like guarding the gate but not the treasure.

At-rest protection can only detect data within known and managed datastores. This means shadow data often goes undetected, leading to significant security gaps.

Let’s consider a few examples of how data could still be at risk under at-rest protection:

  • Third-party exposure: Data might be mapped in databases but can still leak from applications to third parties
  • Ineffective encryption: Database encryption may be enforced, while raw data may be leaking to the internet
  • Developer data leakage: Access to customer data may be hardened, but developers might use unsecured copies for testing

With data always on the move, data protection strategies must evolve accordingly. The figures speak for themselves: The average cost of a data breach in 2023 was $4.45 million USD, up from $4.24 million in 2022. Organizations took an average of 287 days to identify and contain a breach, and 83% experienced more than one breach in 2023. As adversaries continue to ramp up their operations, it’s time for protection to move at the speed of data.

Moving at the Speed of Data

Runtime protection, which offers real-time monitoring of data flows, is a significant advancement in data security. Unlike at-rest methods, which focus on static snapshots, runtime protection provides continuous visibility into data movement and interactions with various systems and services.

This real-time perspective allows organizations to detect and actively prevent data breaches, no matter where the data is. By monitoring data as it moves to SaaS applications, generative AI services and other third parties, runtime protection ensures data remains secure even outside managed environments.

With runtime protection, organizations gain deeper insights into their operational environments and can enhance their ability to prevent and respond to data breaches. This proactive approach ensures comprehensive protection and reduces the risk of security incidents.

The Cloud Data Dance-off: At Rest vs. Runtime

Discovery and Classification

At-rest protection offers a static view of known data repositories. In contrast, runtime protection dynamically discovers and classifies data as it traverses through systems, identifying unexpected data paths and interactions with external parties that traditional methods may miss. By integrating both approaches, organizations can gain a comprehensive understanding of their data landscapes, including compliance requirements and hidden risks.

At rest:

  • Static and predictable: At-rest scanning can identify data that is already known and stored in predefined locations. This may leave out unapproved services, newly added databases or shadow data.
  • Limited scope: This approach only reflects what is already cataloged, missing any dynamic changes or unexpected data movements.

Runtime:

  • Dynamic and comprehensive: Runtime protection provides real-time visibility into data flows, revealing both expected and unexpected data movements.
  • Full coverage: It classifies data as it moves, uncovering shadow data and constructing dynamic flow maps that provide complete visibility and context.
  • Cost efficiency: Full database scanning can be expensive. Continuous monitoring of data in motion means violations are identified when data is passed on the wire, reducing the need for periodic comprehensive scanning.

Security Posture Assessment

At-rest assessments provide valuable insights into security posture based on scheduled scans of static data. However, runtime protection enhances this with continuous monitoring and assessment. This ongoing visibility ensures security measures evolve in real time to address emerging threats and vulnerabilities, rather than relying on periodic snapshots that may quickly become outdated.

At rest:

  • Incomplete picture: At-rest methods scan known infrastructures and provide periodic assessments, potentially missing hidden vulnerabilities and risks between scans.
  • Delayed risk detection: Changes in the data environment between scans can lead to gaps in security posture assessment.

Runtime:

  • Accurate and current: By classifying data in real time, runtime protection provides an honest and up-to-date reflection of the security posture.
  • Continuous monitoring: This approach continuously uncovers hidden risks and vulnerabilities, adapting to rapid changes in the data environment.

Preventing Data Leaks and Breaches

Traditional at-rest approaches reactively identify risks during scheduled scans, potentially missing real-time data breaches or unauthorized data transfers. In contrast, runtime protection allows organizations to enforce policies based on live data transfers, detecting and mitigating risks as they occur. By monitoring data in motion, organizations can reduce the window of exposure and enhance overall data protection effectiveness. Preventing data breaches is a much more powerful story than merely finding data risks — proactive measures significantly reduce the chances of devastating security incidents.

At rest:

  • Reactive approach: At-rest protection identifies risks only during scans, which means data leaks and breaches may go unnoticed until the next scan.
  • Limited enforcement: Policies based on at-rest data may miss real-time leaks and newly emerged vulnerabilities.

Runtime:

  • Proactive protection: Runtime protection enforces policies based on real-time data transfers, allowing immediate response to potential leaks and breaches.
  • Real-time enforcement: By classifying and monitoring data in motion, runtime protection ensures reliable and comprehensive policy enforcement across all environments.

The Data Security Power Couple: Runtime and At-Rest Protection

At-rest and runtime protection methods form a powerful alliance in the realm of data security. While at-rest protection provides foundational security, runtime protection offers the dynamic edge needed for today’s fast-paced digital landscape.

At-rest protection:

  • Foundational insights: Delivers regular assessments to maintain baseline security
  • Compliance: Ensures adherence to regulatory standards
  • Managed perimeters: Monitors risks within known and controlled data zones

Runtime protection:

  • Real-time visibility: Continuously tracks data flows and interactions, offering a dynamic view of your data environment
  • Beyond known perimeters: Detects and safeguards data even as it moves to SaaS applications and third-party services, covering shadow data and unexpected data paths
  • Proactive threat detection: Identifies and mitigates risks as they occur, ensuring immediate response to potential breaches
  • Immediate response: Quickly reacts to security incidents, minimizing downtime and potential damage

By combining these approaches, organizations benefit from enhanced coverage and context, leading to more effective threat detection and response. This integrated strategy not only improves security but also reduces costs by optimizing resource use. Together, this duo creates a holistic and resilient security posture, ensuring your organization’s most valuable asset — its data — is comprehensively protected in today’s complex cloud landscape.

CrowdStrike’s Data Security Posture Management

CrowdStrike Falcon® Cloud Security offers a unified CNAPP solution with data security posture management (DSPM), uniquely preventing data leaks and breaches with advanced runtime capabilities. It tracks data in real time, providing accurate data flow maps for continuous discovery, classification and protection at every stage of the data lifecycle — at rest, in use or in motion. This empowers security teams to control data effectively, ensuring swift prevention of data breaches, misuse, exfiltration and compliance violations.

Additional Resources

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