How to Secure AWS Cloud Data With DSPM

In today’s hyper-connected digital landscape, AWS is a clear leader in the cloud provider space, powering over a third of the global market and hosting trillions of data objects for businesses large and small. Yet, with this staggering scale comes escalating risk—according to recent industry reports, over 60% of organizations storing sensitive data on public clouds have experienced a data-related security incident in the past year. The consequences are not just theoretical: high-profile breaches, such as the 2024 incident that exposed millions of customer records through misconfigured S3 buckets, underline an unsettling truth—traditional cloud security strategies are often no match for sophisticated threats. 

That’s where Data Security Posture Management (DSPM) steps in, offering organizations a proactive approach to discovering, monitoring, and securing sensitive data in AWS environments. In this blog, we’ll explore how you can harness DSPM to fortify your AWS cloud, turning vulnerable data silos into robust, well-guarded assets.

Why data security is a rising concern?

The volume of data breaches grew by 6% YoY in 2024¹ (across different platforms) and an alarming 40% of all breaches involved data distributed across multiple cloud environments.² With 4.19 million businesses currently using the AWS platform’s cloud computing services³—it has become a prime target for threat actors.

The inherent flexibility of cloud platforms like AWS can create security gaps if mishandled, especially since data in these environments exists across multiple locations. In an AWS environment, for example, sensitive information can live in databases like RDS and DynamoDB, while data used in generative AI apps (e.g. AWS Bedrock) may be stored in an S3 bucket. Keeping track of where data exists, who can access it, and whether the right security controls are in place becomes nearly impossible as a result. 

Key drivers behind data security challenges

• Data sprawl: Data in AWS environments is spread across various services, including S3, EC2, RDS, and DynamoDB. Each of these has its own security configurations and access controls, creating additional complexity.
• Shadow data: Shadow data, which is data residing outside a security team’s control, is a growing concern for modern organizations adopting cloud-first and AI strategies. These unmanaged data stores create blind spots in security coverage across AWS environments.
• Over-permissioned access: Often permissions granted to users, when creating or changing user roles, that exceeds what users need for their roles, create unnecessary exposure points. This excessive access widens the attack surface and increases the potential impact of compromised credentials.
• AI adoption: Organizations eager to harness the power of their data with AI, struggle to secure AI pipelines, access and remediate risk to sensitive data assets fueling their AI ecosystem. 

These challenges often lead to misconfigured storage buckets, excessive user permissions, and unsecured databases—all of which become costly attack vectors after a data breach.
 

Real-world examples

These challenges aren’t theoretical—they’re happening across enterprises today. In our recent webinar, Zscaler experts shared real-world DSPM discoveries from actual AWS environments.
 

Open S3 buckets with sensitive data

Companies are discovering that S3 buckets holding confidential data—like customer information or internal documents—have been unintentionally left open due to misconfigurations. DSPM has been able to detect these exposures in real time and guide teams through locking them down before a breach occurs. 
 

Excessive access to unstructured data

Many organizations realize too late that sensitive files—such as employee records, financial reports, or exported data—are accessible to far more users than necessary. DSPM has been able to identify these overexposed assets and enforce least-privilege access, significantly reducing the risk of insider threats or accidental leaks.
 

Unknown shadow data fueling AI pipelines
As companies move quickly to adopt generative AI, some are finding that ungoverned or unapproved datasets are flowing into model training—sometimes without any oversight. DSPM has been able to surface these unmanaged data sources, flag sensitive content, and ensure only compliant, authorized datasets are used in AI development.
 

What is DSPM, and why is it essential for data security?

Traditional, perimeter-based security tools weren't designed for dynamic, cloud-native environments like AWS. Many only monitor specific services without providing visibility across the full AWS environment. And while these tools may identify some sensitive data, they often fail to provide context about its usage and risk level. Moreover, they don’t support granular controls or real-time enforcement across multiple accounts and services.

Take AWS Macie, for instance. While Macie offers native data discovery capabilities, its limited coverage and lack of advanced access controls and policy configuration make it insufficient for enterprise security needs. DSPM addresses these gaps by revealing where sensitive data lives, who can access it, how it’s being used, and whether it’s properly secured—anywhere in your AWS environment.

Unlike traditional security approaches, DSPM centers on the data itself. It uses intelligent automation to identify vulnerabilities, enact safeguards, and perform system tests within your cloud infrastructure so you always know the security posture of your stored data.

How Zscaler DSPM secures AWS data

Zscaler DSPM offers a complete approach to protecting sensitive data across AWS environments while addressing the biggest security challenges modern organizations face. Our fully-integrated solution provides:
 

Comprehensive AI-powered data discovery, classification and inventory

Zscaler DSPM offers granular visibility into sensitive data stored across your AWS environment—from S3 buckets to databases and applications. With AI powered classification it systematically classifies data according to type and sensitivity level, and creates an inventory of all data assets. Without this end-to-end visibility, organizations risk exposing sensitive customer or company data to the public.
 

Automated risk detection and policy enforcement

Zscaler DSPM detects misconfigurations in real-time and provides detailed instructions on how to fix issues before they become security threats. The platform provides a Risk Score that highlights vulnerabilities in your AWS data posture, which your teams can use to prioritize remediation efforts where they'll have the greatest impact.

It also automates policy enforcement, reducing the burden on security teams. They can quickly create and deploy policies—such as requiring certain data types to reside only in specific regions—and enforce these rules throughout your AWS environment.
 

Proactive compliance & least-privilege access control

Complying with regulations like the General Data Protection Regulation (GDPR), the Health Insurance Portability and Accountability Act (HIPAA) and more is difficult without DSPM. Zscaler DSPM provides visibility into your data compliance posture with a dynamic view of compliance status, configuration drifts, and policy violations across AWS services. It also implements least-privilege access principles to limit data access to authorized users only—preventing accidental exposure or malicious activity.
 

Secure AI adoption 

As more organizations integrate generative AI into their workflows, securing the data that powers these models is critical. Zscaler DSPM helps teams identify where AI training data resides, assess its sensitivity, and ensure it meets compliance requirements before use. By detecting shadow data and enforcing strict access policies, DSPM enables responsible, secure AI adoption across your AWS environment without slowing innovation.

Learn more about how to protect your AWS data with DSPM

Protecting data in AWS environments requires a proactive, data-centric approach. Zscaler DSPM provides the visibility, automation, and compliance capabilities needed to safeguard cloud data effectively.

Watch the full webinar today to get more in-depth insights on AWS security challenges and how Zscaler DSPM can help you solve them, or book a demo to see our products in action.

Sources:

1. Infosecurity Magazine, Over 16.8 Billion Records Exposed as Data Breaches Increase 6%, March 18, 2025.
2. IBM, 2024 Cloud Threat Landscape Report: How does cloud security fail?, January 22, 2025.
3. HGInsights, The AWS Ecosystem in 2025, April 19, 2025.