Added a document for the SumStats framework.

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Seth Hall 2013-11-06 13:52:29 -05:00
parent eff96bef37
commit fab47cc749
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logging logging
notice notice
signatures signatures
sumstats

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@load base/frameworks/sumstats
event connection_established(c: connection)
{
# Make an observation!
# This observation is global so the key is empty.
# Each established connection counts as one so the observation is always 1.
SumStats::observe("conn established",
SumStats::Key(),
SumStats::Observation($num=1));
}
event bro_init()
{
# Create the reducer.
# The reducer attaches to the "conn established" observation stream
# and uses the summing calculation on the observations.
local r1 = SumStats::Reducer($stream="conn established",
$apply=set(SumStats::SUM));
# Create the final sumstat.
# We give it an arbitrary name and make it collect data every minute.
# The reducer is then attached and a $epoch_result callback is given
# to finally do something with the data collected.
SumStats::create([$name = "counting connections",
$epoch = 1min,
$reducers = set(r1),
$epoch_result(ts: time, key: SumStats::Key, result: SumStats::Result) =
{
# This is the body of the callback that is called when a single
# result has been collected. We are just printing the total number
# of connections that were seen. The $sum field is provided as a
# double type value so we need to use %f as the format specifier.
print fmt("Number of connections established: %.0f", result["conn established"]$sum);
}]);
}

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@load base/frameworks/sumstats
# We use the connection_attempted event limit our observations to those
# which were attempted and not successful.
event connection_attempt(c: connection)
{
# Make an observation!
# This observation is about the host attempting the connection.
# Each established connection counts as one so the observation is always 1.
SumStats::observe("conn attempted",
SumStats::Key($host=c$id$orig_h),
SumStats::Observation($num=1));
}
event bro_init()
{
# Create the reducer.
# The reducer attaches to the "conn attempted" observation stream
# and uses the summing calculation on the observations. Keep
# in mind that there will be one result per key (connection originator).
local r1 = SumStats::Reducer($stream="conn attempted",
$apply=set(SumStats::SUM));
# Create the final sumstat.
# This is slightly different from the last example since we're providing
# a callback to calculate a value to check against the threshold with
# $threshold_val. The actual threshold itself is provided with $threshold.
# Another callback is
SumStats::create([$name = "finding scanners",
$epoch = 5min,
$reducers = set(r1),
# Provide a threshold.
$threshold = 5.0,
# Provide a callback to calculate a value from the result
# to check against the threshold field.
$threshold_val(key: SumStats::Key, result: SumStats::Result) =
{
return result["conn attempted"]$sum;
},
# Provide a callback for when a key crosses the threshold.
$threshold_crossed(key: SumStats::Key, result: SumStats::Result) =
{
print fmt("%s attempted %.0f or more connections", key$host, result["conn attempted"]$sum);
}]);
}

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doc/frameworks/sumstats.rst Normal file
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==================
Summary Statistics
==================
.. rst-class:: opening
Measuring aspects of network traffic is an extremely common task in Bro.
Bro provides data structures which make this very easy as wellin
simplistic cases such as size limited trace file processing. In real-
world deployments though, there are difficulties that arise from
clusterization (many processes sniffing traffic) and unbounded data sets
(traffic never stops). The Summary Statistics (otherwise referred to as
SumStats) framework aims to define a mechanism for consuming unbounded
data sets and making them measurable in practice on large clustered and
non-clustered Bro deployments.
.. contents::
Overview
========
The Sumstat processing flow is broken into three pieces. Observations, where
some aspect of an event is observed and fed into the Sumstats framework.
Reducers, where observations are collected and measured, typically by taking
some sort of summary statistic measurement like average or variance (among
others). Sumstats, where reducers have an epoch (time interval) that their
measurements are performed over along with callbacks for monitoring thresholds
or viewing the collected and measured data.
Terminology
===========
Observation
A single point of data. Observations have a few components of their
own. They are part of an arbitrarily named observation stream, they
have a key that is something the observation is about, and the actual
observation itself.
Reducer
Calculations are applied to an observation stream here to reduce the
full unbounded set of observations down to a smaller representation.
Results are collected within each reducer per-key so care must be
taken to keep the total number of keys tracked down to a reasonable
level.
Sumstat
The final definition of a Sumstat where one or more reducers is
collected over an interval, also known as an epoch. Thresholding can
be applied here along with a callback in the event that a threshold is
crossed. Additionally, a callback can be provided to access each
result (per-key) at the end of each epoch.
Examples
========
These examples may seem very simple to an experienced Bro script developer and
they're intended to look that way. Keep in mind that these scripts will work
on small single process Bro instances as well as large many-worker clusters.
The complications from dealing with flow based load balancing can be ignored
by developers writing scripts that use Sumstats due to it's built in cluster
transparency.
Printing the number of connections
----------------------------------
Sumstats provides a simple way of approaching the problem of trying to count
the number of connections over a given time interval. Here is a script with
inline documentation that does this with the Sumstats framework:
.. btest-include:: ${DOC_ROOT}/frameworks/sumstats-countconns.bro
When run on a sample PCAP file from the Bro test suite, the following output
is created:
.. btest:: sumstats-countconns
@TEST-EXEC: btest-rst-cmd bro -r ${TRACES}/workshop_2011_browse.trace ${DOC_ROOT}/frameworks/sumstats-countconns.bro
Toy Scan detection
------------------
Taking the previous example even further, we can implement a simple detection
to demonstrate the thresholding functionality. This example is a toy to
demonstate how thresholding works in Sumstats and is not meant to be a real-
world functional example, that is left to the scan.bro script that is included
with Bro.
.. btest-include:: ${DOC_ROOT}/frameworks/sumstats-toy-scan.bro
Let's see if there any hosts that crossed the threshold in a PCAP file
containing a host running nmap:
.. btest:: sumstats-toy-scan
@TEST-EXEC: btest-rst-cmd bro -r ${TRACES}/nmap-vsn.trace ${DOC_ROOT}/frameworks/sumstats-toy-scan.bro
It seems the host running nmap was detected!

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