Correlating Across Sources and Building a Timeline
What is it?
Real incidents cross sources: auth says who signed in, the proxy says where they went, EDR says what ran. Correlation lines these up by a shared key (user, host, IP) and time, producing one timeline that tells the whole story.
Why it matters
No single source proves an intrusion; the sequence across them does. A failed-then-successful login is not alarming until the proxy shows exfiltration two minutes later. The timeline is the evidence you hand up.
Where you see it
Combine sources and order by time: `(sourcetype=auth OR sourcetype=proxy OR sourcetype=edr) user=j.rai | sort _time | table _time, sourcetype, action, dest`. The rows interleave into one narrative.
What normal looks like
A benign timeline explains itself: a login, expected app traffic, no unusual process — each event has an innocent neighbour that accounts for it.
What suspicious looks like
A causal chain no benign story explains: foreign login → credential access on the host → large upload to a new domain, all within minutes and all tied to one user. Correlation, not any single line, is the tell.
How analysts investigate
Choose the shared key, pull the relevant sources, order by time into one table, and read the sequence for cause and effect. Then test the story: is there a benign explanation for the whole chain, not just each link?
Common beginner mistakes
- Correlating on time alone, mixing unrelated users' events into one false story.
- Reporting a scary single event without the timeline that gives it meaning — or missing the benign explanation for the whole chain.
One timeline, many sources
key = user:j.rai, ordered by _time
02:14 auth login success src=Kyiv ← foreign login
02:15 edr lsass access host=FIN-07 ← credential access
02:17 proxy upload 240MB dest=new-cdn.io ← exfiltration
no single line proves it — the CHAIN within 3 minutes doesQuick check
Which conclusion is defensible enough to escalate?
A quick self-check — it doesn't affect your XP or progress.
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