What a SIEM Does
One search box over every log your network produces, if you feed it right.
What you will learn
- -Explain the collection, normalization, and correlation pipeline a SIEM runs
- -Recognize why raw logs from a dozen sources are useless until they share a schema
- -Read a single correlated alert and trace it back to the events that built it
An attacker into a workstation with stolen creds, pivots to a file , and dumps a database. That is three machines, three log formats, and three timestamps in three time zones. Without a you are grepping each box by hand and hoping you notice they are the same story. With one, that whole chain lands in one search and lines up on one timeline.
A SIEM (Security Information and Event Management) platform does three jobs in order: collect, normalize, correlate. Splunk, Elastic Security, Microsoft Sentinel, and Wazuh all differ in price and query language, but every one of them runs that same pipeline. the pipeline wrong and the fanciest correlation rules in the world fire on garbage.
Collection: get the logs off the box
Logs are worthless sitting on the machine that made them, because that is the first thing an attacker wipes. So you ship them off. A Windows runs a forwarder (the Splunk Universal Forwarder, Elastic's Winlogbeat, or the Wazuh agent) that reads the and streams it to the indexer. Linux boxes and gear usually push syslog over 514 or 6514 to a collector.
The rule that matters: if it is not being forwarded, it does not exist as far as your detection goes. Half of real is discovering the one server whose logs were never onboarded.
Normalization: make them speak one language
Windows calls it TargetUserName. Your calls it src_user. Zeek calls it user. Same field, three names, and a correlation rule cannot join across them until they match. Normalization maps every source into one schema so user=jdoe means the same thing everywhere.
Splunk uses the Common Information Model (CIM). Elastic uses the Elastic Common Schema (ECS), where a source IP is always source.ip no matter which sensor produced it. This mapping happens at ingest or search time, and it is the least glamorous, most important work in the whole platform.
A field that parses wrong is worse than a missing field, because it looks fine in the search bar and silently breaks every rule that depends on it. When a detection stops firing, suspect the parser before you suspect the rule.
Correlation: turn events into a story
One failed login is noise. Two hundred failed logins from one IP, then one success, then a new admin account created ninety seconds later, is a spray that worked. Correlation is the SIEM watching multiple normalized events across sources and firing a single when they form a known pattern.
That is the payoff for all the collection and normalization grind. The analyst does not see two hundred rows. They see one alert that says " followed by account creation on HR-FS01," with every underlying event one click away.
Only pull, query, or export logs from systems you are authorized to monitor. Logs carry usernames, internal , session , and sometimes in from misconfigured apps. Handle them like the sensitive data they are, and never move them off approved infrastructure.
A correlation rule that joins events on the username field stops matching after a new firewall is onboarded. What is the most likely cause?