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title: Why data quality dictates security operations success
description: A controlled benchmark study compared how different network telemetry sources affect AI-driven SOC investigations, testing Corelight enriched logs, open-source...
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# Why data quality dictates security operations success

**[CSO Online](https://daily.dev/sources/csoonline)** · 6 min read · 0 upvotes · 0 comments

## Summary

A controlled benchmark study compared how different network telemetry sources affect AI-driven SOC investigations, testing Corelight enriched logs, open-source nDPI firewall logs, Snort 3 alerts, and NetFlow records against a Capture the Flag scenario and an incident response task. Corelight logs produced up to 4x better accuracy (95.2% vs 25.8% for NetFlow), 5x greater critical incident visibility, and nearly halved investigation time (14.7 vs 27 minutes) compared to lower-fidelity sources. The research, sponsored by Corelight, concludes that data quality outweighs LLM model selection in determining SOC investigation success, and recommends security leaders prioritize telemetry quality over model upgrades.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.csoonline.com/article/4206800/why-data-quality-dictates-security-operations-success.html>

## Questions this post answers

### Does the quality of network telemetry data or the choice of LLM matter more for AI-driven security investigations?

Data quality matters more than model selection, according to a controlled benchmark comparing Corelight enriched logs, nDPI firewall logs, Snort 3 alerts, and NetFlow across a 44-question capture-the-flag test and an incident response task. Corelight logs achieved 95.2% CTF accuracy versus 25.8% for NetFlow, a roughly fourfold difference, while using the same LLMs (Claude Opus 4.6, Gemini Pro 3.1 Preview) under identical prompts.

_Teams weighing telemetry upgrades against model upgrades can track this kind of security tooling research on daily.dev._

### How much faster is an AI security investigation when using enriched network logs instead of NetFlow data?

An LLM-driven investigation completed in 14.7 minutes using Corelight enriched logs, compared to 27.0 minutes with NetFlow records and 26.3 minutes with firewall logs, nearly doubling investigation time with lower-quality data. The slowdown occurred because models entered repeated retry loops when protocol-level context was missing from the telemetry.

_daily.dev is where security engineers follow findings like this when scoping SOC automation investments._

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---

Tags: [#security](https://daily.dev/tags/security), [#llm](https://daily.dev/tags/llm)

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