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08/07/2026 6:59 pm
TL;DR: Security telemetry only becomes actionable when it is tied back to real users, devices, and entities, because static correlation and event-centric SIEM views miss attack chains, inflate noise, and weaken UEBA, according to Gurucul. Identity-first link analysis turns fragmented logs into contextual evidence, making investigations faster and more defensible.
NHIMG editorial — based on content published by Gurucul: Operationalizing Link Analysis: Why Context, Identity, and Correlation Matter
Questions worth separating out
Q: How should security teams improve correlation across identity, endpoint, and cloud telemetry?
A: Security teams should normalise logs into a shared identity model before they rely on correlation rules.
Q: Why do service accounts and API tokens complicate SIEM investigations?
A: They complicate investigations because they often lack the stable ownership and naming assumptions that work for human users.
Q: What do security teams get wrong about UEBA in dynamic environments?
A: They often treat UEBA as a scoring problem instead of a context problem.
Practitioner guidance
- Build an identity graph before you tune detections Normalize users, service accounts, tokens, devices, and cloud-native IDs into a single entity model so investigations can follow activity across systems without manual pivots.
- Enrich telemetry with business context Add role, department, title, and business unit data to security events so analysts can judge whether behaviour is unusual in operational terms, not only in technical terms.
- Stitch events into evidence chains Group related activity into before, during, and after sequences so SOC teams can reconstruct attack paths, support casework, and reduce alert fragmentation.
What's in the full article
Gurucul's full blog post covers the operational detail this post intentionally leaves for the source:
- The platform's step-by-step example of resolving one identifier into another across endpoint, cloud, and identity systems
- The specific behavioural baseline inputs Gurucul says it uses for UEBA and chain analysis
- The investigation workflow details behind the 'Investigate' search experience and contextual attributes
- The business-impact framing Gurucul uses to connect detection speed with SOC efficiency
👉 Read Gurucul's analysis of link analysis, identity context, and UEBA →
Link analysis and UEBA: where legacy correlation falls short?
Explore further
08/07/2026 7:22 pm
Identity correlation is now a governance problem, not just a SIEM feature. The article correctly frames link analysis as the difference between seeing logs and understanding behaviour. For IAM and NHI programmes, the real issue is whether every entity can be traced across systems with enough continuity to preserve accountability. That makes correlation architecture part of governance, not just analytics, and it should be treated as such in programme design.
A few things that frame the scale:
- From our research: Only 5.7% of organisations have full visibility into their service accounts, according to the Ultimate Guide to NHIs.
- Another finding from our research shows that 97% of NHIs carry excessive privileges, according to the Ultimate Guide to NHIs.
A question worth separating out:
Q: How can organisations tell whether their correlation model is working?
A: A correlation model is working when analysts can move from alert to evidence chain without manual field-matching across tools. The clearest signal is reduced investigation time with higher-confidence conclusions, especially when the same identity can be traced through identity systems, endpoints, cloud logs, and application events. If that continuity is missing, the model is only producing partial joins.
👉 Read our full editorial: Link analysis is exposing the limits of legacy SIEM correlation
