Uncovering and Protecting Sensitive Data Across Cloud Environments with Exposure Command

Last updated at Fri, 28 Feb 2025 21:15:20 GMT

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 integrations, security teams can automate data classification ingestion, enhance risk assessment, and take proactive remediation steps to secure sensitive information in their cloud infrastructures.

We don’t just stop at support for native services, however, as we also offer the ability to ingest tags directly, whether from the Cloud Service Provider (CSP) or via IaC templates such as Terraform. With automated cloud-native tagging, organizations can establish a single source of truth for data classification, ensuring that security teams can quickly assess and respond to risks tied to sensitive information.

By taking a tag-based classification strategy, organizations can:

• Standardize classification across cloud resources with custom tag schemas for severity, data type, and compliance requirements.
• Ensure consistency by automating tag propagation across related resources.
• Leverage version control to track classification changes over time for audit and compliance purposes.
  

Infrastructure as Code Integration for Seamless Classification

Exposure Command makes it easy to implement and enforce consistent data classification directly within cloud infrastructure deployment workflows. With native Terraform resource tagging, automated tag inheritance, and customizable classification schemas, security teams can automate classification at scale. Version control ensures auditability and change tracking, helping organizations maintain a dynamic, risk-aware classification framework that evolves with their cloud environment.

Sensitive Data Discovery Meets Risk Prioritization

Exposure Command enables teams to take a data-centric approach to risk prioritization by incorporating insights into sensitive data exposures alongside Layered Context and Attack Path Analysis, ensuring that organizations focus on the risks that could lead to real-world breaches. By layering asset criticality, exploitability, and risk posture with insights into sensitive data exposure, security teams can focus on protecting crown jewel data assets.

Taking a Data-Centric Approach to Risk Prioritization with Layered Context

Layered Context is a multi-dimensional risk prioritization model that moves beyond traditional vulnerability management by integrating sensitive data insights, threat intelligence, and business impact analysis into a unified view of risk. Rather than prioritizing based solely on CVSS scores, this approach ensures security teams focus on the exposures that pose the highest real-world risk, not just those that appear severe on paper.

By layering in sensitive data awareness, Exposure Command allows teams to see not just which systems are vulnerable, but which ones expose high-value data whether it’s customer PII, financial records, intellectual property, or regulated information. This makes it possible to prioritize remediation based on both exploitability and potential business impact.

Understanding Paths for Lateral Movement and Unwanted Access to Sensitive Data

Attackers don’t just exploit vulnerabilities - they chain weaknesses together to reach high-value data. Exposure Command’s Attack Path Analysis goes beyond simply identifying risky assets; it maps how an attacker could move through the environment to access sensitive data. By visualizing lateral movement opportunities, privilege escalation paths, and gaps in data protection, security teams can preemptively block attack routes before they’re exploited.

Instead of just highlighting vulnerable systems, it maps how attackers could exploit weaknesses to access sensitive customer information, financial records, or intellectual property. This data-centric approach shifts remediation from a focus on CVSS scores to business impact-driven security, ensuring that teams address the most critical exposures first.

By revealing hidden exploitation paths, Exposure Command identifies chained vulnerabilities, lateral movement risks, and privilege escalation opportunities that could allow attackers to reach high-value data. A misconfiguration on a low-risk asset might seem harmless - until it's linked to a cloud storage bucket containing sensitive data. With attack path visualization, security teams can better understand attack scenarios, block lateral movement, and proactively shut down high-risk pathways before they can be exploited - moving from reactive patching to proactive breach prevention.

Why Data-Centric Risk Prioritization Matters

Traditional risk management often overlooks the nuances of sensitive data exposure, relying on static vulnerability metrics. By embedding sensitive data insights directly into risk prioritization workflows, Rapid7 Exposure Command shifts the paradigm to focus on what matters most: safeguarding critical data assets.

This approach ensures that security efforts are aligned with business priorities, enabling organizations to:

• Protect customer and proprietary information.
• Mitigate the risk of data breaches and non-compliance penalties.
• Enhance collaboration between security, IT, and risk management teams.

Take Command of Your Sensitive Data Risks

With sensitive data discovery now part of Exposure Command, Rapid7 is empowering organizations to bolster their security strategies. Whether you're a financial institution safeguarding customer data or a healthcare provider ensuring patient privacy, this innovation provides the tools you need to protect what matters most.

Ready to elevate your risk management program? Learn how Rapid7 Exposure Command can help you integrate data-centric risk prioritization into your security operations.