From Detection to Orchestration: Using Data Attack Surface Management (DASM) to Power CTEM Workflows

The Problem: Exposure Insights Without Automation Don’t Reduce Risk

Most security programs today generate extensive insight into data exposure—sensitive files with broad access, anomalous activity across SMB and NFS shares, dormant identities retaining permissions. Yet despite this visibility, risk remains largely unchanged.

Why? Because insight without enforcement is not security.

Security and storage teams continue to face the same systemic challenges:

• Reporting without mitigation
  Exposure findings accumulate faster than teams can respond, creating backlog instead of reduction.
  
• Siloed tools and fragmented context
  SIEM, IAM, endpoint security, storage management, and ITSM systems operate independently, slowing coordinated response.
  
• Manual remediation workflows
  Risk decisions rely on human triage, ticket routing, and institutional knowledge.
  

Without automation tied directly to data-layer signals, CTEM devolves into a monitoring exercise rather than a control framework. Detection alone does not reduce exposure—orchestration does.

Why Data Attack Surface Management (DASM) Is the Missing Input for End-to-End CTEM

Effective CTEM cannot rely on a single telemetry source. True risk assessment requires correlating host attack surface intelligence with real data exposure.

Data Attack Surface Management (DASM) provides the data-layer context that most CTEM programs lack, while host and endpoint platforms contribute system-level exposure. Together, they form a complete and accurate risk picture.

CTEM shifts from periodic assessment to continuous enforcement—where host attack surface intelligence, combined with DASM telemetry, produces an accurate, data-driven risk assessment grounded in how data is actually exposed, accessed, and abused.

DASM delivers four essential categories of data-layer intelligence that infrastructure-only exposure platforms cannot provide.

1. Sensitivity Context

Risk without data context is incomplete.

DASM incorporates classification and sensitivity signals—regulated data, intellectual property, and high-value business content—ensuring exposure scoring reflects business impact, not theoretical access.

Traditional exposure platforms apply AI only to the data they can see. Without classification and sensitivity awareness, they cannot determine which exposures truly matter.

2. Behavioral Insights

Access does not equal risk—behavior validates intent.

Superna Data Security Edition (DSE) monitors real-time activity directly at the storage layer, identifying:

• Abnormal access frequency
  
• Irregular file operations
  
• Identities acting outside historical norms
  

When correlated with host-level attack surface telemetry, these signals distinguish benign access from active misuse, dramatically improving CTEM decision accuracy.

3. Permission and Access Path Analysis

Exposure is created by permission sprawl, not by identity count alone.

DASM evaluates actual access pathways across supported storage platforms, including:

• Inherited group permissions
  
• Share-level access expansion
  
• Dormant identities retaining access
  

This reveals how data is reachable in practice—not how access is assumed to work.

4. Environmental Exposure Conditions

Context determines urgency.

DASM accounts for situational exposure signals such as:

• Broadly accessible shares
  
• Low-activity data with lingering permissions
  
• Contextual signals from integrated security and infrastructure tools
  

This allows CTEM workflows to prioritize remediation based on real-world exposure conditions, not static findings.

First-Party Data: Why Superna Is Different

These insights originate directly from the storage and data layer. They are not inferred, sampled, or approximated.

Combined with host attack surface telemetry, this first-party perspective enables true data-layer CTEM—precision that endpoint, identity, and vulnerability tools alone cannot achieve.

From Detection to Enforcement: How the Zero Trust API Powers Orchestration

Visibility alone does not close risk. Enforcement does.

Superna’s Zero Trust API transforms DASM and DSE insights into real-time, machine-consumable signals that orchestration systems can act on immediately—closing the gap between detection and response.

Webhooks → SOAR Playbooks

DASM and DSE emit structured webhook alerts that SIEM and SOAR platforms can ingest without translation.

This enables:

• Automated investigation and enrichment
  
• Policy-driven decisioning
  
• Immediate response without manual triage
  

CTEM becomes continuous, coordinated, and outcome-driven.

Real-Time Restriction of Data-Layer Risk

When exposure exceeds policy thresholds, downstream systems can use Zero Trust API signals to:

• Restrict access pathways
  
• Pause risky sessions
  
• Apply compensating controls based on defined rules
  

This approach avoids direct ACL manipulation while still delivering meaningful access remediation.

Automated Ticketing and Evidence Capture

ITSM platforms receive complete, structured context:

• Data sensitivity indicators
  
• Behavioral signals
  
• Permission pathways
  
• Host and environmental exposure factors
  

Remediation becomes repeatable, auditable, and measurable across StorageOps and SecOps teams.

Ecosystem-First by Design

Superna integrates through webhooks and APIs with platforms such as:

• Splunk
  
• ServiceNow
  
• Leading SIEM and SOAR platforms
  

This extends CTEM automation across the enterprise without disrupting existing tooling.

Real CTEM Workflow Examples

Automatically Reducing Exposure on Sensitive Data

DASM identifies sensitive data with broad access. Host exposure context validates risk severity.

Zero Trust API signals trigger SOAR workflows to restrict exposure pathways and generate access review tasks.

Outcome: Immediate risk reduction with long-term governance.

Coordinated Incident Response with DSE

DSE flags abnormal access behavior. Host attack surface telemetry confirms potential compromise.

SIEM and SOAR systems initiate containment workflows and accelerate investigation.

Outcome: Faster response grounded in real data activity.

Reducing Risky Access Pathways at Scale

DASM identifies excessive inherited permissions and dormant identities.

Orchestration workflows restrict access and guide entitlement cleanup.

Outcome: Structural reduction of the data attack surface.

Architecture of a Continuous Feedback Loop

A mature CTEM program is self-correcting by design.

1. DASM Identifies Data Exposure
   Continuous scoring highlights sensitive data, broad access, and contextual risk.
   
2. Host Telemetry Confirms System Risk
   Attack surface data validates exploitability and compromise likelihood.
   
3. DSE Validates Behavior
   Storage-layer activity confirms misuse or benign access.
   
4. Orchestration Enforces Policy
   SIEM, SOAR, and ITSM systems act on Zero Trust API signals.
   
5. Metrics Measure Risk Reduction
   Exposure scores trend downward as controls take effect.
   

This is CTEM as a control plane—not a reporting function.

The Unified Superna Platform

Data Attack Surface Management (DASM), Data Security Edition (DSE), host exposure telemetry, and the Zero Trust API operate together as a unified, data-layer CTEM engine.

Visibility. Validation. Enforcement.

Outcome: A Self-Correcting Data Security Program

By integrating DASM telemetry with host attack surface intelligence and orchestration systems, organizations achieve:

• Fewer manual tasks through automated workflows
  
• Measurable exposure reduction, not theoretical scoring
  
• Accurate risk assessment grounded in real data and real access
  
• Continuous cyber resilience driven by data-aware control
  

The result is a CTEM program that doesn’t just find exposure—it systematically eliminates it.