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20/08/2026 5:46 pm
TL;DR: Security stacks that rely on separate DLP, EDR, SIEM, and identity tools often miss the full data path because they were built around infrastructure rather than data, according to Sentra. A data-first model that combines DSPM, DLP, DAG, and DDR can improve visibility, access control, and response, but only if those functions share the same sensitivity and identity context.
NHIMG editorial — based on content published by Sentra: data-first security architecture for DSPM, DLP, DAG, and DDR
Questions worth separating out
A: Start by giving every control the same data classification and identity context.
Q: Why do service accounts and other non-human identities increase breach impact?
A: Service accounts and other non-human identities increase breach impact because they often carry broad, persistent access and bypass interactive controls like MFA.
Q: What do organisations get wrong about data sovereignty and DSPM?
A: They often treat a green residency dashboard as proof of sovereignty.
Practitioner guidance
- Unify sensitivity labels across the stack Make DSPM the source of truth for data classification and propagate those labels into DLP, DDR, and access review workflows so each control acts on the same context.
- Review non-human identity access to sensitive datasets Inventory service accounts, service principals, and AI-connected workloads that can read, copy, or export regulated data, then remove permissions that are not tied to a specific task or dataset.
- Test whether tools can correlate the same event end to end Run a controlled scenario where a dataset is discovered, accessed, and exported across cloud, SaaS, and endpoint layers to confirm that the stack preserves identity and data context throughout.
What's in the full article
Sentra's full article covers the operational detail this post intentionally leaves for the source:
- How DSPM, DLP, DAG, and DDR are connected in a working cloud-native architecture
- Examples of policy mappings such as data labels, access rules, and runtime response triggers
- Integration touchpoints with SIEM, SOAR, IAM, ITSM, Purview, and AI gateways
- The vendor's view of where its platform sits in a data-first security stack
👉 Read Sentra's analysis of a data-first architecture for DSPM, DLP, DAG, and DDR →
DSPM, DLP and DAG: where data-first security stacks still fail?
Explore further
20/08/2026 6:28 pm
Data-first security is becoming an identity problem as much as a data problem. Once service principals, human users, and AI systems all interact with the same sensitive data estates, access governance becomes part of data protection rather than a separate discipline. That means teams cannot treat DAG as a niche control. It is the mechanism that tells the rest of the stack which identities can turn data visibility into data loss. Practitioners should design data governance and identity governance together.
A question worth separating out:
A: They should treat the event as a governance failure, not just a detection issue. Containment should combine access review, identity revocation, policy tightening, and investigation of the path the data took. If the stack cannot explain the movement, the next step is to close the identity and classification gaps that allowed it.
👉 Read our full editorial: Data-first security stacks need unified controls across data and access
