Why Modern SIEM Architecture Abandoned Raw Ingestion

Date: Jan 28, 2026
Read time: 4 minutes

Andrew MacKay

Chief Technology & Strategy Officer

Security teams didn’t stop ingesting raw logs because they wanted fewer tools.

They stopped because centralized analysis was economically and analytically unsustainable.

Modern SIEMs evolved into correlation and orchestration platforms that rely on domain-specific intelligence to do what centralized systems could not:

Analyze raw telemetry locally
Apply deep domain context
Eliminate noise before ingestion
Forward only confirmed events and IOCs

This shift reduced cost, improved signal quality, and made SIEM operational again.

But it also revealed something uncomfortable.

Correlation was only as good as the inputs it received.

The Missing Input: The Data Layer

As endpoint, network, identity, and cloud domains matured, each developed specialized platforms capable of producing high-confidence intelligence.

The data layer did not.

The result is a security architecture where:

Endpoint behavior is understood
Network movement is visible
Identity misuse is detected
But data exposure, blast radius, and destruction remain opaque

This is why breaches continue to succeed even in well-instrumented environments.

Attackers don’t need to evade correlation — they only need to operate in a domain the SIEM cannot see.

That domain is the data attack surface.

What Is the Data Attack Surface?

The data attack surface is not just where data resides.

It is the combination of:

Exposed shares, exports, and buckets
Over-permissive access paths
Sensitive and business-critical datasets
Identity-driven access relationships
Lateral movement paths through data

Unlike network attack surface, data attack surface is dynamic:

It grows as access is granted
It shifts as permissions change
It expands silently without generating alerts

Most importantly:

The data attack surface defines blast radius.

Why SIEM and SOAR Cannot Act on Data They Don’t Have

SOAR automation assumes context.

But when the SIEM doesn’t know:

Which data was accessible to a compromised identity
Which datasets were exposed
Whether the data was sensitive or regulated
How far access could propagate

Response actions become:

Over-reactive
Under-reactive
Or dangerously delayed

This is why organizations often contain the attacker — yet still suffer massive data loss.

The data signal never entered the correlation engine.

Data Attack Surface Intelligence Must Be Domain-Specific

The security industry already accepts that:

Endpoint detection belongs to endpoint platforms
Network detection belongs to network platforms
Identity analytics belong to identity platforms

Data security is no different.

Cyberstorage platforms are uniquely positioned to:

Understand file and object semantics
Map access relationships
Detect destructive behavior with context
Calculate blast radius in real time
Reduce attack surface before compromise

Expecting SIEMs to infer this from logs alone is no different than expecting them to replace EDR or IDS.

From Raw Storage Events to Actionable Intelligence

The future of SIEM is not broader ingestion — it is higher-fidelity intelligence.

The correct model is clear:

Cyberstorage platforms analyze raw data telemetry locally
Data attack surface and blast radius are continuously assessed
Only confirmed data-threat intelligence is forwarded
SIEM correlates across endpoint, identity, network, cloud, and data
SOAR executes precise, data-aware response

This improves outcomes without reintroducing the cost and noise that broke centralized analysis.

Data Attack Surface as a First-Class Security Domain

SIEM does not replace endpoint security.

It does not replace network detection.

It does not replace identity analytics.

It should not be expected to replace data-threat intelligence.

Until the data attack surface becomes a first-class security domain feeding verified intelligence into SIEM and SOAR, organizations will continue to respond to breaches without understanding what was truly at risk.