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Usage file for the Spade v092200.1
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Author: Jim Hoagland (hoagland@SiliconDefense.com)
This file contains information about how to use and configure the Statistical
Packet Anomaly Detection Engine (Spade), spp_anomsensor.
-= The main configuration line =-
To enable spp_anomsensor, you must have a line of this form in your snort
configuration file:
preprocessor spade:
For example:
preprocessor spade: 10.5 spade.rcv log.txt 3 50000
The following subsections describe what these arguments mean and additional
available lines in the configuration do. Note that on this line and all Spade
configuration lines that if you leave some of the arguments at the end, they
will assume their default value.
-= Threshold =-
is the (initial) threshold at which packets are reported.
If a packet has an anomaly score at least as big as this threshold, it will
be sent as an alert. If this is a negative number, Spade will start up with
an with no reporting. -1 is the default.
-= Log file =-
is a the logging file for Spade. This is regenerated on every
SIGHUP, SIGQUIT, and SIGUSR1 and on Snort exit. At a minimum, the number of
packets accepted by Spade (not counting those that were not TCP SYNs or that
did not meet the homenet requirements) and the number of alerts sent is
reported here. Some optional parts of Spade write to this log file as well.
If this argument is '-', then standard output (stdout) is used. '-' is the
default.
-= Checkpointing and recovery =-
Since Spade maintains a history-based probability table, it is important to
have persistent storage for this table, especially since some sites restart
their snort processes regularly.
Towards this end, Spade has a checkpoint and recovery feature. (At present,
this just covers the probability tables.) The state file is given by the
argument (default "spade.rcv"). If this file is present when
starting up, the initial state of Spade is taken from this. (Otherwise it
starts up with a clean slate.) Periodically this state file is updated with
the current state. This is done with a frequency of every
accepted packets (default 50000), on SIGHUP, SIGQUIT, and SIGUSR1, and on
Snort exit.
To disable checkpointing and recovering (not generally recommended), give "0"
as the argument.
Note that the size of the of file is roughly the size of Spade in memory.
Also note that it may take a few seconds to checkpoint during which time snort
will not otherwise run.
-= Probability mode =-
There are four probability modes available in Spade. These modes configure
how Spade determines the likelihood of a particular packet. We do not know
which is best and it might be different depending on the characteristics of
your network, so we allow you to decide. You may just want to leave the
default unless you wish to play with it.
The probability mode is set by the argument on the main
configuration line. The possible values are:
+ 0: a Bayes network approximation of P(sip,sport,dip,dport)
+ 1: P(sip,sport,dip,dport)
+ 2: P(sip,dip,dport)
+ 3: P(dip,dport)
The default is 3.
Warning: If you change probability modes, you will need to discard your
state-file from checkpointing. The wrong set of information has been
recorded. Not doing this will not cause a crash, the probabilities may just
be off.
-= Home networks =-
You can restrict Spade to considering packets destined to particular networks
or hosts. That is, packets for addresses outside those networks are ignored
by Spade. The default is to consider all packets. To enable this, add a
line like this to your snort configuration file:
preprocessor spade-homenet: ...
where is either CIDR notation for a network (e.g., 123.123.128.0/17)
or an IP address (e.g. 123.123.123.123).
Note that this home network specification is independent of the -h option of
snort and the HOMENET variable in the rules file.
-= Finding a good threshold =-
There are 4 facilities for helping you find and maintain an appropriate
reporting threshold, so that you do not get flooded with alerts about normal
packets by having too low of a threshold and so that you do not miss packets
of interest by having too high a threshold. One is threshold learning and the
other three are different means of automatically adapting the threshold to
meet observed conditions.
The premise for these is that you want to aim for a certain rate of alerts, a
rate just high enough to catch interesting events. Each of these facilities
observes the network for a certain interval of time, keeping record of the
anomaly scores for the packets observed. Based on this, an "ideal" threshold
can be derived that would have produced exactly the number of alerts wanted.
At least, during that time interval. We have observed that this is a pretty
noisy process and this will vary from interval to interval.
Note that regardless of the way your threshold is set, your rate of alerts
will not be steady. This is since the rate of anomalous events is not steady.
For example, if someone runs a noisy Nmap on you, you will get more alerts
than normal (unless, of course, this is normal). So, for whatever target rate
you aim for, consider that to be your target for most of the time intervals.
You can either use one of the 4 facilities described in the next two
subsections or do it yourself by trying out different threshold values.
-= Threshold learning =-
To start up threshold learning mode when Snort starts up, provide a line of
this form in the Snort configuration file:
preprocessor spade-threshlearn:
This mode is enabled for hours (default 24), after which it reports
on the threshold that would have been needed to produce scores
(default 200) during that time. At the end of the time period, a report about
this is generated to the log file specified on the main sensor configuration
line. An intermediate report is produced on every SIGHUP, SIGQUIT, and
SIGUSR1 and on Snort exit.
-= Threshold adapting =-
There are three modes of adapting. None of these are on by default, but if
one were, then method #3 would be the default since we think it should work
the best. Your network may disagree though :).
Method #1 is the simplest approach. It periodically takes a weighted average
of the current threshold and the recently observed ideal. You activate this
by adding a line of this form to the Snort configuration file:
preprocessor spade-adapt:
The target packet count is given by the argument (default 20).
The length of time during which that count is aimed for and the refresh rate
for the threshold is given by (default 2). is the
weight given to the new component of the weighted average (default 0.5).
Higher values (up to 1.0) give more weight to recent observations.
An option with method #1 is to measure the adapt period by packet count rather
than by time. That is, the adapt time specification is converted into a count
of packets, based on the current best estimate of a rate of packets. The
advantage here is that observed ideal values between periods is more likely to
be similar since about the same number of packets were considered for each, so
the transitions will be steadier. This is on by default. To disable, set the
argument to 0 (rather than 1).
Method #2 is more involved. A new threshold is based the average of short,
medium and long term components. This is the line to add to the configuration
file:
preprocessor spade-adapt2:
is the specification of the number of alerts wanted. If it is
>= 1, it is an hourly alert rate. If it is < 1, then it is a fraction of
considered packets to report, based on the best estimate of your packet rate.
The later form of specification might be preferred if your network might
experience a shift in packet rates. The default is 0.01 (1%).
is the number of minutes in an observation window (default 15).
The is the frequency with which the reporting threshold is updated and is
actually converted to a packet count. times is how long the
short term is. The default for is 4, so the combined default is 1 hour.
is the number of short term periods in the medium term (default 24) and
is the number of medium term periods in the long term (default 7).
For a more complete description of how this mode works, see the comments in
the source code.
Method #3 is fairly simple. The reporting threshold is based on an average of
the ideal threshold values from the last N observation periods. (If there
haven't been N observation periods yet, it just takes the average of the ones
seen so far). This mode is invoked with a line of the form:
preprocessor spade-adapt3:
is the specification of the target alert rate and takes the same
form as that in method #2 (default 0.01). is the number of minutes
in a period of observation (default 60); this is converted to count of
packets. is the number of observations to average over (default
168, which is the number of hours in a week).
-= Survey mode =-
Survey mode periodically reports information about the anomaly scores produced
in the last time interval. It is activated with the following line:
preprocessor spade-survey:
where is the file to write the output to (default is standard
output) and is the frequency of the observation period,
in minutes (default 60). This mode is active for as long as Snort is running.
The file produced is in a table form suitable for importing into spreadsheets
and databases. A line of column headers is on the first line and the
following are tab-separated on the following lines:
+ interval #
+ number of accepted packets in the interval
+ median (50th percentile) anomaly score in the interval
+ 90th percentile anomaly score
+ 99th percentile anomaly score
Linear interpolation is used for the percentile results if there is no exact
score in the indicated position.
Note that at present a O(n*n) algorithm is used for storing the anomaly
scores, so that when number of accepted packets in the interval becomes large,
this mode runs slowly. If this mode becomes used seriously, we should use an
order statistics tree or some other O(n*log(n)) algorithm.
-= Statistics mode =-
When the statistics mode is activated certain information about the network
traffic is reported. This makes use of the already available probabilities
from the calculation of the anomaly scores, which will depend on the
probability mode selected. It is enabled with the following line in the
configuration file:
preprocessor spade-stats: ...
where is one of:
+ "entropy" (to display the known entropies and conditional entropies)
+ "uncondprob" (to display the known non-0 simple (joint) probabilities)
+ "condprob" (to display the known non-0 conditional (joint) probabilities)
These are written to the log file on SIGHUP, SIGQUIT, and SIGUSR1 and on Snort
exit. Be aware that it might take a while to write the "uncondprob" and
"condprob" results as there is in general alot of those.
The following results are available from probability mode 3:
+ H(dip), H(dport|dip)
+ P(dip=x), P(dip=x,dport=y)
+ P(dport=x|dip=y)
For finer grained control over what statistics are available, you will need to
modify the source code. See the "parts" variable. Warning: this process is
a bit ugly.
-= Source code parameters =-
There are a few tunable parameters that you will need to change some numbers
in the source code in order to adjust. Fortunately most people probably won't
want to change these anyway.
A set of parameters in anomsensor_plug.h configure how the adjustment of
probability is done to more strongly reflect recent network characteristics.
SCALE_FREQ is the frequency (in seconds) with which this is updated (4 hours
is the distributed value). Note that scaling is a fairly intensive operation.
SCALE_FACTOR is the relative weight to give to traffic observed before an
update as compared to the traffic after (0.96409 is the distributed value).
It is reasonable to adjust these without discarding the state file. So, the
probabilities you had before the scale is only SCALE_FACTOR as important as
those in the later period. 4 hours and 0.96409 together imply a half life of
a little over 3 days.
At some point, the occurrance of something a long time ago (relative to the
number of times it occurred) makes little difference in the anomaly scores
produces, so it might as well be discarded to save memory. MIN_NODE_SIZE is
the size of an occurrance count at which the record of something has occurred
is discarded (distributed value is 0.18). The combination of these parameters
as distributed means that a one-time occurrence is discarded after a little
over one week (and a double occurrance after two weeks, etc.).
A different set of parameters are used to control how much memory can be used
in maintaining the probability state. A description of exactly what these do
requires a discussion beyond the scope of this document. For now, if you get
a message of the form "exhausted all X blocks of Y , try increasing
the corresponding DEFAULT_MAX_*_SIZE parameter in params.h.