Modern organizations grapple with the complex task of securing sensitive data in sprawling hybrid and multi-cloud environments. Due to insufficient visibility and governance, data is often misplaced, duplicated, or left exposed. This fragmented environment makes it difficult for teams to accurately assess data exposure risks, comply with stringent privacy regulations, and continuously track sensitive data across locations, owners, and usage.
Without a consistent, holistic view of where sensitive data resides and how it is managed, organizations face significant security, compliance, and operational risks. To solve this challenge and make sense of their data security posture, organizations typically start by discovering and gaining visibility into data stored across their IT estate and work to classify the type of data and associated risk of exposure.
Modern enterprises typically rely on various data classification sources, including CSP-native detection services (such as Amazon Macie, MSFT Defender for Cloud, or GCP Security Command Center), third-party DSPM tools, custom classification policies, or by manually tagging native cloud resources. When discrepancies arise, security teams face a critical question: Which classification should they trust and how can they manage these classifications efficiently at scale? To help solve this persistent challenge, we’re excited to announce sensitive data discovery and data-centric risk prioritization in Exposure Command, empowering teams to implement data-centric risk prioritization as a cornerstone of their security strategy.
Automated Data Classification Leveraging Existing Tagging Frameworks
With this update, Exposure Command offers teams the ability to ingest data classifications and findings from native data security services offered by cloud providers such as AWS Macie, Microsoft Defender for Cloud, and Google Cloud Security Command Center. This enhancement enables organizations to centralize sensitive data insights across their cloud environments, providing a unified view of data risks and exposures. By leveraging these in ..
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