The Data Security Power Couple: How DSPM Intelligence Powers DLP

Jul 29, 2026

It's the kind of Friday security teams dread. 4:47pm. An employee, Ana, who gave notice that morning decides to share a file from corporate cloud storage to her personal Gmail. The file name looks mundane: August expense report. But inside is a customer database filled with contact details, retainer fees, and payment history. Critical sensitive data leaving on someone's way out the door.

You know this data matters. Your Data Security Posture Management (DSPM) solution told you what it is, why it matters to the business, who can reach it, and how it's used. Understanding is the foundation. To reduce risk, you have to enforce on that same intelligence DSPM created, closing the distance between knowing and doing.

This is the closed-loop model Cyera designed. For data at rest, DSPM delivers actionable data intelligence. Omni DLP extends it into protection the moment data moves or is used. Both run on the same shared data intelligence, in a single platform. In the walkthrough below, we follow that Friday incident from the first alert to a contained, documented response.

Why DSPM and DLP must share intelligence

Data security spans data at rest, in motion, and in use. DSPM owns data at rest, what sensitive data you have and where the risk is. DLP owns data in motion and in use, whether it should be moving and how to stop it. They each offer significant value in isolation, but together, they're much more powerful.

When posture and enforcement are disconnected, you get:

Fragmented visibility → you connect the dots between tools by hand while the clock runs.
Undefined IP → your crown jewels slip through cracks undetected, because no rule was ever written to catch them.
AI-amplified data debt → years of overpermissive access and unclassified files become immediate exposure.
Noisy policies → alert fatigue, with real risk buried underneath.

Every one traces back to the same root cause: the system that understands the data and the system that protects it aren’t talking to each other.

The shared data intelligence created by Cyera DSPM is the connective tissue, including:

Data context: the type, sensitivity, and business meaning of the data
Identity context: role, privilege changes, and termination signals
Destination context: sanctioned versus unsanctioned apps and destinations
Behavior context: what is normal for the identity, and what is anomalous

So a policy doesn't trigger on every regex match. It triggers because the system knows the context: this is a customer contract, this identity shouldn't be moving it, and this destination is unsanctioned.

Only a true understanding of data makes this possible.

How it works with Cyera: one investigation, start to finish

Step 1: Triage the alert and understand why it matters

Back to that Friday incident. Ana shared an Excel file from corporate cloud storage to her personal Gmail. The file name looked harmless ("August expense report"), but the contents were a critical customer database.

There was an alert to catch it only because Cyera made one possible. Off-the-shelf DLP policies watch for known patterns, a credit card number, a Social Security number, not a business-specific customer database dressed up as an expense report. Cyera closed that gap ahead of time, using DSPM's learned classifications to build the Purview policy that flagged the file. So the moment Ana moved it, Purview raised an alert, but rated it low criticality. But Cyera saw what Purview couldn't. It re-scored the alert to Critical and shows exactly why:

Each signal alone is explainable. Together, they are exfiltration. The Cyera alert that fired wasn’t based on a hand-written regex pattern. It was built on data intelligence derived from DSPM, then through AI analysis, Cyera automatically sifted through the noise to uncover the true intent of the malicious insider.

Step 2: Pull the full picture on the identity

Now that real risk is uncovered, it’s time to investigate the identity. One click on her name and the full picture comes into view: Ana can reach roughly 4 million sensitive records across the environment, spanning customer, financial, and even patient health data, including a production datastore of medical records a logistics analyst has no business touching. She's also keeping a confidential customer database in her personal Gmail, and her identity already carries a stack of open exposure issues. The alert told you what she did in this moment. The identity view through DSPM tells you how much more she could be taking, and how exposed you still are.

Step 3: Use DSPM to find the root cause and fix it

Cyera surfaced the root cause: Ana had far more access than her role required. And Cyera doesn't just provide a “recommended fix”. You can revoke access directly from the finding, moving from investigation to remediation without opening a second tool.

Step 4: Build the evidence record with Access Trail

Cyera aggregates all activities tied to Ana’s identity into one timeline: what she accessed, what she moved, where it went, and when (even delegated actions that Copilot took on her behalf). In most environments that means manually stitching together access logs. Cyera centralizes the evidence so HR, legal, or an investigator has everything they need as soon as they need it.

‍What we showed: One low-severity signal that was initially missed became a critical incident. We connected it to the identity behind it, showed the full scope of what she could reach, a root cause that was fixed on the spot, and an evidence record that was ready to export. One connected story, start to finish.

A Unified Data Security Platform

Cyera delivers DSPM and DLP in one unified platform today, alongside AI and Agent Security solutions. The data intelligence DSPM produces flows directly into the policies DLP enforces. In practice, it's a single loop: