Zscaler’s December 2, 2024 announcement describes new DSPM capabilities for finding unmanaged cloud data, classifying it, and showing teams how access and exposure may put it at risk. The additions it names are AWS shadow-account discovery, Amazon DynamoDB, and Google Cloud. These are vendor-described features, not independently tested outcomes; because the announcement is dated, confirm current availability and coverage with Zscaler before planning a deployment.
What “shadow data” means in cloud security
Zscaler uses “shadow data” for data held in unmanaged cloud sources that may sit outside an organization’s normal security visibility. Such data can be difficult to protect if a security team does not know where it is, what it contains, or who can reach it.
Data discovery is only the first step: finding a store does not prove that its contents are secure. Teams also need to understand sensitivity, permissions, and exposure, then decide what action to take.
What Zscaler says its DSPM innovations do
Discover AWS shadow accounts and their data
Zscaler says its service can automatically discover AWS shadow accounts through zero-touch deployment and provide visibility into data location and classification across data stores. The stated aim is to help teams identify what data is hosted in cloud accounts and consolidate shadow accounts. The announcement does not specify deployment prerequisites or independently validate how discovery performs in a customer environment.
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Connect sensitive data to access and exposure
The announcement describes AI-supported IAM analysis intended to identify excessive or risky access paths, relate sensitive data to public exposure, show historical access, and guide remediation. Together, these capabilities are meant to give teams context for prioritizing issues rather than treating every discovered data store alike. Zscaler does not report independent testing or a measured reduction in risk.
Extend named cloud coverage
The announcement names Amazon DynamoDB as an added AWS service and Google Cloud as an added platform. It describes Zscaler DSPM more broadly as covering structured and unstructured stores across public clouds and SaaS. This is not a complete integration matrix: verify the exact services, data types, and deployment conditions currently supported for your environment with Zscaler.
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Where DSPM fits alongside other cloud security tools
In Zscaler’s current explainer, data security posture management (DSPM) focuses on discovering and classifying sensitive data, assessing its risk and exposure, and monitoring or helping remediate issues. Zscaler contrasts that data-centered focus with cloud security posture management (CSPM), which focuses on cloud infrastructure posture, and SaaS security posture management (SSPM), which focuses on SaaS application posture. This is the vendor’s framing of the categories; the labels describe different emphases, not a reason to assume one tool replaces the others.
For a DSPM evaluation, compare products on the practical capabilities that matter to your data environment:
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- Coverage: Which cloud platforms, SaaS services, and individual data stores are supported?
- Discovery and classification: Can the service find structured and unstructured data and classify sensitive content?
- Access and exposure context: Does it connect sensitive data to identities, risky permissions, or public exposure?
- History and remediation: Can teams review historical access and follow a usable remediation workflow?
- Deployment and availability: What setup is required, and are the specific capabilities available for your region, edition, and environment?
The December 2024 announcement addresses some of these capability areas but does not establish current availability, complete coverage, or deployment requirements.
How to assess the announcement before deployment
- Inventory your data sources. List the AWS accounts, databases, cloud platforms, and SaaS services that matter. Identify unmanaged accounts or stores you especially need to bring into view.
- Check exact coverage with Zscaler. Ask whether the current service supports each named platform and data store in your environment, including the specific structured or unstructured data you need to discover.
- Validate the access and exposure views. Confirm what IAM analysis, public-exposure context, and historical access information are available for your sources, and how the service presents evidence for a finding.
- Review remediation and deployment details. Establish which actions are guided or automated, what your team must do, and what deployment prerequisites apply. The announcement does not provide enough detail to determine these for a particular organization.
- Test against your own requirements. Use an evaluation to check discovery, classification, access context, and remediation workflows against representative data and permissions. Do not treat the announcement’s feature descriptions as proof of results in your environment.
How to read the breach statistics in the announcement
Zscaler’s December 2, 2024 article attributes several figures to IBM research: 35% of breaches “this year” involved data stored in unmanaged sources; breaches involving shadow data took 26.2% longer to identify and 20.2% longer to contain, averaging 291 days; and the average breach cost where shadow data was involved was $5.27 million. These are secondary attributions in Zscaler’s article. “This year” refers to the article’s 2024 publication context, not 2026, and the figures should not be treated as current statistics or evidence that shadow data alone caused the outcomes without checking the underlying IBM publications.
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