Provably Better Data: AI SOC Data Quality

New research from Corelight reveals that data quality strongly impacts AI performance in the SOC, proving your AI is only as good as the data you feed it. Learn how:

Data quality defines a ceiling for AI performance
Better AI models can't overcome missing evidence
Analytical power is lost when evidence is degraded

Read the research

What was tested

The impact of network data quality on AI SOC performance. Our testing included two goals: Investigation with a 44-question Capture the Flag exercise inspired by the Volt Typhoon threat actor, and incident response analysis for a realistic Salt Typhoon compromise.

How it was tested

The frontier LLM model and tasks were kept constant, with only the source of network-derived data changing. Four data sources were evaluated: Corelight data, nDPI firewall logs, Snort 3 IDS alerts, and NetFlow data. Performance was scored on CTF accuracy and IR "grounding" (claims supported by available evidence).

Why it's repeatable

We tested each data set independently, ingested all data via an OCSF-normalized schema, averaged results across multiple test runs, and took many measures to minimize model bias.

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