Writing Prelude LML rules

In this post, we will cover the basics of adding your own rules to Prelude-LML, which is Prelude's own log monitoring analysis engine. Highly optimized in C, Prelude-LML, comes with numerous rules built-in for everything from SSH authentication to Netscreen firewall rules.

To start we will navigate to the default LML ruleset directory, which is located in /usr/local/etc/prelude-lml/ruleset - unless you specified otherwise.

Our Example

For example purposes, we'll use the made up syslog entry below to follow along with. It shows the date, a host named some_hostame, with a service called mylogger_service, that printed some message.

Aug 22 05:22:05 some_hostname mylogger_service: We have an imortant message here.

Setting Up

The first thing you want to do is have a look at pcre.rules. The pcre.rules file, provides a way to match on certain criteria that all rules in a certain set will all match on, a lot of them are based on services, such as ssh, which allows LML to limit how many log messages are processed against which rules.

Since our service, mylogger_service, is new and no other specific rulesets apply to it, we'll add a line to pcre.rules to only apply our new rule (which we will add to its own file later, called local.rules). Adding the following to pcre.rules will do just this:

regex=mylogger_service; include = local.rules;

What this does, is only process rules in the local.rules file, if the log entry contains "mylogger_service" in it.


Adding a Rule to its own Ruleset

So now we see that we have prepped our new rule file (local.rules), to receive any log entries that contain the line mylogger_service in them. We next need to add rules to our local.rules file for further processing and alerting on any matches. Here is what we will add to local.rules for our example:

# Detect important messages from the mylogger_service.
# LOG:Aug 22 05:22:05 some_hostname mylogger_service: We have an imortant message here.
regex=important message; \
classification.text=Important Message Detected.; \
id=32001; \
revision=1; \
assessment.impact.type=other; \
assessment.impact.severity=low; \
assessment.impact.description=An important message was detected with the mylogger_service; \
last;

Stepping through this example, we see the following:

- A comment line that describes what this rule is about.
- A LOG line that shows an actual example syslog entry for what we are looking for.
- regex, that is what we are matching on, any potential regex can be used here. Such as character classes (\w,\d) or wildcards (.,*,+).
- classification.text, here is the main alert text for this rule
- id, which differentiates on this particular rule
- revision, bump this up by one as you make production edits
- impact type, which can be things such as admin, user, other, etc.
- impact severity, such as low, medium, high
- impact description, a longer description of what most likely is referenced in classification.text
- last, which basically tells LML to stop further processing if this rule matches

Many more IDMEF fields may be used, such as references or process names.

When mylogger_service is seen in a syslog entry that LML processes, it will process this entry against all the rules in the local.rules file (which is how we set this up in pcre.rules). Furthermore, if the entry matches our regex of "important message", we will get an alert with severity of low, a message text of "Important Message Detected", and the various other settings we have set.

Conclusion

This example showed a simple way of adding rules to your LML engines. You may have noticed when looking in pcre.rules, at the top is a "best practices" section on creating/adding LML rules. For much more extensive information, look here.