Plugin support, README updated

This commit is contained in:
BlackLight 2010-10-26 21:58:34 +02:00
parent 820ca2151c
commit 7772c9b089
17 changed files with 437 additions and 40 deletions

View file

@ -26,6 +26,7 @@ cluster.c \
correlation.c \
db.c \
fsom/fsom.c \
modules.c \
mysql.c \
neural.c \
outdb.c \
@ -57,6 +58,8 @@ fi
mkdir -p "${SHARE_PREFIX}/htdocs"
mkdir -p "${SHARE_PREFIX}/htdocs/js"
mkdir -p "${SHARE_PREFIX}/schemas"
mkdir -p "${SHARE_PREFIX}/corr_modules"
cp -rf "${PWD}/corr_modules/"* "${SHARE_PREFIX}/corr_modules"
install -m 0644 "${PWD}/htdocs/index.html" "${SHARE_PREFIX}/htdocs"
install -m 0644 "${PWD}/htdocs/manual_correlations.dtd" "${SHARE_PREFIX}/htdocs"
install -m 0644 "${PWD}/htdocs/manual_correlations.xml" "${SHARE_PREFIX}/htdocs"

View file

@ -84,11 +84,11 @@ am_libsf_ai_preproc_la_OBJECTS = libsf_ai_preproc_la-alert_history.lo \
libsf_ai_preproc_la-cencode.lo libsf_ai_preproc_la-bayesian.lo \
libsf_ai_preproc_la-cluster.lo \
libsf_ai_preproc_la-correlation.lo libsf_ai_preproc_la-db.lo \
libsf_ai_preproc_la-fsom.lo libsf_ai_preproc_la-mysql.lo \
libsf_ai_preproc_la-neural.lo libsf_ai_preproc_la-outdb.lo \
libsf_ai_preproc_la-postgresql.lo libsf_ai_preproc_la-regex.lo \
libsf_ai_preproc_la-spp_ai.lo libsf_ai_preproc_la-stream.lo \
libsf_ai_preproc_la-webserv.lo
libsf_ai_preproc_la-fsom.lo libsf_ai_preproc_la-modules.lo \
libsf_ai_preproc_la-mysql.lo libsf_ai_preproc_la-neural.lo \
libsf_ai_preproc_la-outdb.lo libsf_ai_preproc_la-postgresql.lo \
libsf_ai_preproc_la-regex.lo libsf_ai_preproc_la-spp_ai.lo \
libsf_ai_preproc_la-stream.lo libsf_ai_preproc_la-webserv.lo
nodist_libsf_ai_preproc_la_OBJECTS = \
libsf_ai_preproc_la-sf_dynamic_preproc_lib.lo \
libsf_ai_preproc_la-sfPolicyUserData.lo
@ -268,6 +268,7 @@ cluster.c \
correlation.c \
db.c \
fsom/fsom.c \
modules.c \
mysql.c \
neural.c \
outdb.c \
@ -418,6 +419,9 @@ libsf_ai_preproc_la-db.lo: db.c
libsf_ai_preproc_la-fsom.lo: fsom/fsom.c
$(LIBTOOL) --tag=CC $(AM_LIBTOOLFLAGS) $(LIBTOOLFLAGS) --mode=compile $(CC) $(DEFS) $(DEFAULT_INCLUDES) $(INCLUDES) $(AM_CPPFLAGS) $(CPPFLAGS) $(libsf_ai_preproc_la_CFLAGS) $(CFLAGS) -c -o libsf_ai_preproc_la-fsom.lo `test -f 'fsom/fsom.c' || echo '$(srcdir)/'`fsom/fsom.c
libsf_ai_preproc_la-modules.lo: modules.c
$(LIBTOOL) --tag=CC $(AM_LIBTOOLFLAGS) $(LIBTOOLFLAGS) --mode=compile $(CC) $(DEFS) $(DEFAULT_INCLUDES) $(INCLUDES) $(AM_CPPFLAGS) $(CPPFLAGS) $(libsf_ai_preproc_la_CFLAGS) $(CFLAGS) -c -o libsf_ai_preproc_la-modules.lo `test -f 'modules.c' || echo '$(srcdir)/'`modules.c
libsf_ai_preproc_la-mysql.lo: mysql.c
$(LIBTOOL) --tag=CC $(AM_LIBTOOLFLAGS) $(LIBTOOLFLAGS) --mode=compile $(CC) $(DEFS) $(DEFAULT_INCLUDES) $(INCLUDES) $(AM_CPPFLAGS) $(CPPFLAGS) $(libsf_ai_preproc_la_CFLAGS) $(CFLAGS) -c -o libsf_ai_preproc_la-mysql.lo `test -f 'mysql.c' || echo '$(srcdir)/'`mysql.c
@ -840,6 +844,8 @@ fi
mkdir -p "${SHARE_PREFIX}/htdocs"
mkdir -p "${SHARE_PREFIX}/htdocs/js"
mkdir -p "${SHARE_PREFIX}/schemas"
mkdir -p "${SHARE_PREFIX}/corr_modules"
cp -rf "${PWD}/corr_modules/"* "${SHARE_PREFIX}/corr_modules"
install -m 0644 "${PWD}/htdocs/index.html" "${SHARE_PREFIX}/htdocs"
install -m 0644 "${PWD}/htdocs/manual_correlations.dtd" "${SHARE_PREFIX}/htdocs"
install -m 0644 "${PWD}/htdocs/manual_correlations.xml" "${SHARE_PREFIX}/htdocs"

98
README
View file

@ -30,7 +30,8 @@ Table of contents:
5. Correlation rules
6. Output database
7. Web interface
8. Additional documentation
8. Additional correlation modules
9. Additional documentation
===============================
@ -161,18 +162,13 @@ following:
preprocessor ai: \
alertfile "/your/snort/dir/log/alert" \
alert_history_file "/your/snort/dir/log/alert_history" \
alert_serialization_interval 3600 \
alert_bufsize 30 \
alert_clustering_interval 300 \
alert_correlation_weight 5000 \
alert_history_file "/your/snort/dir/log/alert_history" \
alert_serialization_interval 3600 \
bayesian_correlation_interval 1200 \
bayesian_correlation_cache_validity 600 \
correlation_graph_interval 300 \
correlation_rules_dir "/your/snort/dir/etc/corr_rules" \
correlated_alerts_dir "/your/snort/dir/log/correlated_alerts" \
correlation_threshold_coefficient 0.5 \
cluster_max_alert_interval 14400 \
clusterfile "/your/snort/dir/log/clustered_alerts" \
cluster ( class="dst_port", name="privileged_ports", range="1-1023" ) \
cluster ( class="dst_port", name="unprivileged_ports", range="1024-65535" ) \
cluster ( class="src_addr", name="local_net", range="192.168.1.0/24" ) \
@ -181,10 +177,21 @@ preprocessor ai: \
cluster ( class="dst_addr", name="local_net", range="192.168.1.0/24" ) \
cluster ( class="dst_addr", name="dmz_net", range="155.185.0.0/16" ) \
cluster ( class="dst_addr", name="vpn_net", range="10.8.0.0/24" ) \
cluster_max_alert_interval 14400 \
clusterfile "/your/snort/dir/log/clustered_alerts" \
corr_modules_dir "/your/snort/dir/share/snort_ai_preproc/corr_modules" \
correlation_graph_interval 300 \
correlation_rules_dir "/your/snort/dir/etc/corr_rules" \
correlated_alerts_dir "/your/snort/dir/log/correlated_alerts" \
correlation_threshold_coefficient 0.5 \
database ( type="dbtype", name="snort", user="snortusr", password="snortpass", host="dbhost" ) \
database_parsing_interval 30 \
hashtable_cleanup_interval 300 \
manual_correlations_parsing_interval 120 \
neural_network_training_interval 43200 \
neural_train_steps 10 \
output_database ( type="dbtype", name="snort", user="snortusr", password="snortpass", host="dbhost" ) \
output_neurons_per_side 20 \
tcp_stream_expire_interval 300 \
webserv_banner "Snort AIPreprocessor module" \
webserv_dir "/prefix/share/htdocs" \
@ -197,6 +204,15 @@ The options are the following:
and not to a database (default if not specified: /var/log/snort/alert)
- alert_correlation_weight: When this number of alert is stored in the "memory"
of the software (i.e. in the alert history file or in the output database), the
weight for the heuristical correlation indexes (bayesian network and neural
network) will be more or less equal to 0.95, on a scale from 0 to 1.
This parameter expresses how much the heuristical indexes should be weighted and
it can be considered like a kind of "learning rate" for the alert correlation
algorithm (default value if not specified: 5000)
- alert_history_file: The file keeping track of the history, in binary format,
of all the alerts received by the IDS, so that the module can build some
statistical correlation inferences over the past
@ -234,6 +250,14 @@ in the bayesian correlation hash table (i.e. a pair of alerts with the
before being updated (default: 600 seconds)
- corr_modules_dir: This software supports a kind of plugins, or "modules over
the module", that allow the user to specify some extra correlation rules and
indexes. These modules are .so files placed in this directory (default if not
specified: PREFIX/share/snort_ai_preproc/corr_modules), dynamically loaded by
the module. For more information on how to write your own module, see the
dedicated section in this file.
- correlation_graph_interval: The interval that should occur from the building
of the correlation graph between the clustered alerts and the next one (default
if not specified: 300 seconds)
@ -301,6 +325,20 @@ the hashtable of TCP streams and the next one (default if not specified: 300
seconds)
- manual_correlations_parsing_interval: Interval in seconds between an execution
of the thread for parsing the alert correlations manually set and the next one
(default value if not specified: 120 seconds)
- neural_network_training_interval: Interval in seconds between an execution of
the thread for training the neural network using the set of recent alerts and
the next one (default if not specified: 43200 seconds)
- neural_train_steps: Number of steps to take in each training cycle for the
neural network (default: 10)
- output_database: Specify this option if you want to save the outputs from the
module (correlated alerts, clustered alerts, alerts information and their
associated packets streams, and so on) to a relational database as
@ -312,6 +350,13 @@ module, just give the right file to your database, e.g. for MySQL
$ mysql -uusername -ppassword dbname < schemas/mysql.sql
- output_neurons_per_side: Number of output neurons per side on the output layer
of the neural network (that is a rectangular matrix). A higher number allows a
higher granularity over similar alerts, but a linear increment of this value
produces a squared increment of the computational complexity for the training
and evaluation algorithms (default value if not specified: 20)
- tcp_stream_expire_interval: The interval that should occur for marking a TCP
stream as "expired", if no more packets are received inside of that and it's not
"marked" as suspicious (default if not specified: 300 seconds)
@ -467,8 +512,41 @@ that, all the alerts of those types will be marted as correlated, or
uncorrelated.
=================================
8. Additional correlation modules
=================================
It is possible to add extra parameters and indexes for evaluating the
correlation between two alerts in an extremely simple way. The directory
specified in the configuration option "corr_modules_dir" contains the extra
modules (as binary shared libraries -> .so). Each of these modules should
contain a function whose prototype is
double AI_corr_index ( AI_snort_alert*, AI_snort_alert* )
taking two alerts as parameters and returning a correlation value between them,
and one whose prototype is
double AI_corr_index_weight ()
returning a coefficient in [0,1] expressing the weight of that index. An
example module is contained in the corr_modules directory in the source
directory, or in PREFIX/share/snort_ai_preproc/corr_modules after installation.
When you write your own module, just add in the Makefile in the corr_modules
directory a line like the one already present there for compiling, then type
`make'. You may need to link your module source file(s) against
libsf_ai_preproc.la if you want to use some of the functions from the module,
for example, for reading the alerts stored in the history file, in the
database, the current correlations, and so on.
===========================
8. Additional documentation
9. Additional documentation
===========================
The additional documentation over the code, functions and data structures can

3
TODO
View file

@ -2,10 +2,8 @@
AVERAGE/HIGH PRIORITY:
======================
- Supporting extra modules for alert correlation
- Code profiling
- Comment all the code!!!
- Neural network for computing k
- Testing more scenarios, making more hyperalert models
=============
@ -36,4 +34,5 @@ DONE:
+ Saving packet flows as .pcap
+ Manual alert correlation from the web interface
+ Neural network for alert correlation
+ Supporting extra modules for alert correlation

View file

@ -497,7 +497,7 @@ __AI_copy_alerts ( AI_snort_alert *node )
AI_snort_alert*
AI_get_alerts ()
{
AI_snort_alert *alerts_copy;
AI_snort_alert *alerts_copy = NULL;
pthread_mutex_lock ( &alert_mutex );
alerts_copy = __AI_copy_alerts ( alerts );

View file

@ -751,7 +751,7 @@ __AI_copy_clustered_alerts ( AI_snort_alert *node )
AI_snort_alert*
AI_get_clustered_alerts ()
{
AI_snort_alert *alerts_copy;
AI_snort_alert *alerts_copy = NULL;
pthread_mutex_lock ( &mutex );
alerts_copy = __AI_copy_clustered_alerts ( alert_log );

View file

@ -42,6 +42,9 @@
/* Define to 1 if you have the `connect' function. */
#undef HAVE_CONNECT
/* Define to 1 if you have the <dirent.h> header file. */
#undef HAVE_DIRENT_H
/* Define to 1 if you have the <dlfcn.h> header file. */
#undef HAVE_DLFCN_H
@ -60,6 +63,9 @@
/* Define to 1 if you have the <inttypes.h> header file. */
#undef HAVE_INTTYPES_H
/* Define to 1 if you have the `dl' library (-ldl). */
#undef HAVE_LIBDL
/* Define to 1 if you have the `gvc' library (-lgvc). */
#undef HAVE_LIBGVC

52
configure vendored
View file

@ -11719,6 +11719,56 @@ as_fn_error $? "libm not found on the system
See \`config.log' for more details" "$LINENO" 5 ; }
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for dlopen in -ldl" >&5
$as_echo_n "checking for dlopen in -ldl... " >&6; }
if test "${ac_cv_lib_dl_dlopen+set}" = set; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-ldl $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char dlopen ();
int
main ()
{
return dlopen ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_dl_dlopen=yes
else
ac_cv_lib_dl_dlopen=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_dl_dlopen" >&5
$as_echo "$ac_cv_lib_dl_dlopen" >&6; }
if test "x$ac_cv_lib_dl_dlopen" = x""yes; then :
cat >>confdefs.h <<_ACEOF
#define HAVE_LIBDL 1
_ACEOF
LIBS="-ldl $LIBS"
else
{ { $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
$as_echo "$as_me: error: in \`$ac_pwd':" >&2;}
as_fn_error $? "libdl not found on the system
See \`config.log' for more details" "$LINENO" 5 ; }
fi
if test "x$prefix" == x/usr; then :
CORR_RULES_PREFIX="/etc/snort/corr_rules"
@ -11956,7 +12006,7 @@ _ACEOF
fi
for ac_header in inttypes.h limits.h stddef.h stdlib.h string.h unistd.h wchar.h math.h
for ac_header in dirent.h dlfcn.h inttypes.h limits.h math.h stddef.h stdlib.h string.h unistd.h wchar.h
do :
as_ac_Header=`$as_echo "ac_cv_header_$ac_header" | $as_tr_sh`
ac_fn_c_check_header_mongrel "$LINENO" "$ac_header" "$as_ac_Header" "$ac_includes_default"

View file

@ -136,6 +136,7 @@ AS_IF([test "x$with_graphviz" != xno],
AC_CHECK_LIB([xml2], [xmlReaderForFile],, AC_MSG_FAILURE(libxml2 not found on the system))
AC_CHECK_LIB([pthread], [pthread_create],, AC_MSG_FAILURE(libpthread not found on the system))
AC_CHECK_LIB([m], [sqrt],, AC_MSG_FAILURE(libm not found on the system))
AC_CHECK_LIB([dl], [dlopen],, AC_MSG_FAILURE(libdl not found on the system))
AS_IF([test "x$prefix" == x/usr],
[AC_SUBST([CORR_RULES_PREFIX], ["/etc/snort/corr_rules"])],
@ -161,7 +162,7 @@ AS_IF([test "x$with_graphviz" != xno],
[AC_DEFINE([HAVE_BOOLEAN], [1], [Check if the boolean type is defined])])
AC_FUNC_ALLOCA
AC_CHECK_HEADERS([inttypes.h limits.h stddef.h stdlib.h string.h unistd.h wchar.h math.h],,AC_MSG_ERROR(At least one of the required headers was not found))
AC_CHECK_HEADERS([dirent.h dlfcn.h inttypes.h limits.h math.h stddef.h stdlib.h string.h unistd.h wchar.h],,AC_MSG_ERROR(At least one of the required headers was not found))
# Check for int types
AC_CHECK_TYPES([u_int8_t,u_int16_t,u_int32_t,u_int64_t,uint8_t,uint16_t,uint32_t,uint64_t])

3
corr_modules/Makefile Normal file
View file

@ -0,0 +1,3 @@
all:
gcc -I. -I.. -I../uthash -I../base64 -I../fsom -I../include -D_GNU_SOURCE -Wall -pedantic -pedantic-errors -std=c99 -fPIC -shared -rdynamic -o libsf_ai_corr_example.so libsf_ai_corr_example.c

View file

@ -0,0 +1,37 @@
/*
* =====================================================================================
*
* Filename: libsf_ai_corr_example.c
*
* Description: Sample correlation module for two alerts
*
* Version: 0.1
* Created: 26/10/2010 14:23:24
* Revision: none
* Compiler: gcc
*
* Author: BlackLight (http://0x00.ath.cx), <blacklight@autistici.org>
* Licence: GNU GPL v.3
* Company: DO WHAT YOU WANT CAUSE A PIRATE IS FREE, YOU ARE A PIRATE!
*
* =====================================================================================
*/
#include "spp_ai.h"
/** Function that, given two alerts, returns a correlation index in [0,1] */
double
AI_corr_index ( const AI_snort_alert *a, const AI_snort_alert *b )
{
return 0.5;
}
/** Function that returns the weight of this index */
double
AI_corr_index_weight ()
{
return 0.0;
}

Binary file not shown.

View file

@ -102,9 +102,7 @@ __AI_correlated_alerts_to_dot ( AI_alert_correlation *corr, FILE *fp )
src_port1[10],
dst_port1[10],
src_port2[10],
dst_port2[10],
*timestamp1,
*timestamp2;
dst_port2[10];
if ( !corr )
return;
@ -115,37 +113,27 @@ __AI_correlated_alerts_to_dot ( AI_alert_correlation *corr, FILE *fp )
snprintf ( src_port1, sizeof ( src_port1 ), "%d", ntohs ( corr->key.a->tcp_src_port ));
snprintf ( dst_port1, sizeof ( dst_port1 ), "%d", ntohs ( corr->key.a->tcp_dst_port ));
timestamp1 = ctime ( &(corr->key.a->timestamp ) );
timestamp1 [ strlen ( timestamp1 ) - 1 ] = 0;
inet_ntop ( AF_INET, &(corr->key.b->ip_src_addr), src_addr2, INET_ADDRSTRLEN );
inet_ntop ( AF_INET, &(corr->key.b->ip_dst_addr), dst_addr2, INET_ADDRSTRLEN );
snprintf ( src_port2, sizeof ( src_port2 ), "%d", ntohs ( corr->key.b->tcp_src_port ));
snprintf ( dst_port2, sizeof ( dst_port2 ), "%d", ntohs ( corr->key.b->tcp_dst_port ));
timestamp2 = ctime ( &(corr->key.b->timestamp ) );
timestamp2 [ strlen ( timestamp2 ) - 1 ] = 0;
fprintf ( fp,
"\t\"[%d.%d.%d] %s\\n"
"%s:%s -> %s:%s\\n"
"%s\\n"
"(%d alerts grouped)\" -> "
"\"[%d.%d.%d] %s\\n"
"%s:%s -> %s:%s\\n"
"%s\\n"
"(%d alerts grouped)\";\n",
corr->key.a->gid, corr->key.a->sid, corr->key.a->rev, corr->key.a->desc,
src_addr1, src_port1, dst_addr1, dst_port1,
timestamp1,
corr->key.a->grouped_alerts_count,
corr->key.b->gid, corr->key.b->sid, corr->key.b->rev, corr->key.b->desc,
src_addr2, src_port2, dst_addr2, dst_port2,
timestamp2,
corr->key.b->grouped_alerts_count
);
} /* ----- end of function __AI_correlated_alerts_to_dot ----- */
@ -1230,7 +1218,10 @@ AI_alert_correlation_thread ( void *arg )
bayesian_correlation = 0.0,
neural_correlation = 0.0;
size_t n_correlations = 0;
size_t n_correlations = 0,
n_corr_functions = 0,
n_corr_weights = 0;
FILE *fp = NULL;
AI_alert_correlation_key corr_key;
@ -1255,6 +1246,12 @@ AI_alert_correlation_thread ( void *arg )
graph_t *g = NULL;
#endif
double (**corr_functions)( const AI_snort_alert*, const AI_snort_alert* ) = NULL;
double (**corr_weights)() = NULL;
corr_functions = AI_get_corr_functions( &n_corr_functions );
corr_weights = AI_get_corr_weights ( &n_corr_weights );
pthread_mutex_init ( &mutex, NULL );
/* Start the thread for parsing manual correlations from XML */
@ -1377,6 +1374,19 @@ AI_alert_correlation_thread ( void *arg )
n_correlations++;
}
/* Get the correlation indexes from extra correlation modules */
if (( corr_functions ))
{
for ( i=0; i < n_corr_functions; i++ )
{
if ( corr_weights[i]() != 0.0 )
{
corr->correlation += corr_weights[i]() * corr_functions[i] ( corr_key.a, corr_key.b );
n_correlations++;
}
}
}
if ( n_correlations != 0 )
{
corr->correlation /= (double) n_correlations;

151
modules.c Normal file
View file

@ -0,0 +1,151 @@
/*
* =====================================================================================
*
* Filename: modules.c
*
* Description: Support for extra correlation modules
*
* Version: 0.1
* Created: 26/10/2010 01:11:25
* Revision: none
* Compiler: gcc
*
* Author: BlackLight (http://0x00.ath.cx), <blacklight@autistici.org>
* Licence: GNU GPL v.3
* Company: DO WHAT YOU WANT CAUSE A PIRATE IS FREE, YOU ARE A PIRATE!
*
* =====================================================================================
*/
#include "spp_ai.h"
#include <dirent.h>
#include <dlfcn.h>
#include <stdlib.h>
#include <unistd.h>
/** \defgroup modules Software component for loading extra user-provided modules for correlating alerts
* @{ */
PRIVATE double (**corr_functions)(const AI_snort_alert*, const AI_snort_alert*) = NULL;
PRIVATE size_t n_corr_functions = 0;
PRIVATE double (**weight_functions)() = NULL;
PRIVATE size_t n_weight_functions = 0;
/**
* \brief Get the correlation functions from the extra correlation modules as array of function pointers
* \param n_functions Number of function pointers in the array
* \return The array of correlation functions
*/
double
(**AI_get_corr_functions ( size_t *n_functions )) (const AI_snort_alert*, const AI_snort_alert*)
{
*n_functions = n_corr_functions;
return corr_functions;
} /* ----- end of function AI_get_corr_functions ----- */
/**
* \brief Get the weights of the correlation extra modules as array of function pointers
* \param n_functions Number of function pointers in the array
* \return The array of correlation weights functions
*/
double
(**AI_get_corr_weights ( size_t *n_functions )) ()
{
*n_functions = n_weight_functions;
return weight_functions;
} /* ----- end of function AI_get_corr_weights ----- */
/**
* \brief Initialize the extra modules provided by the user
*/
void
AI_init_corr_modules ()
{
void **dl_handles = NULL;
DIR *dir = NULL;
char *err = NULL;
char *fname = NULL;
size_t n_dl_handles = 0;
struct dirent *dir_info = NULL;
if ( !( dir = opendir ( config->corr_modules_dir )))
{
return;
}
while (( dir_info = readdir ( dir )))
{
if ( preg_match ( "(\\.(l|s)o)|(\\.l?a)", dir_info->d_name, NULL, NULL ))
{
if ( !( dl_handles = (void**) realloc ( dl_handles, (++n_dl_handles) * sizeof ( void* ))))
{
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
}
if ( !( fname = (char*) malloc ( strlen ( config->corr_modules_dir ) + strlen ( dir_info->d_name ) + 4 )))
{
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
}
sprintf ( fname, "%s/%s", config->corr_modules_dir, dir_info->d_name );
if ( !( dl_handles[n_dl_handles-1] = dlopen ( fname, RTLD_LAZY )))
{
if (( err = dlerror() ))
{
_dpd.errMsg ( "dlopen: %s\n", err );
}
AI_fatal_err ( "dlopen error", __FILE__, __LINE__ );
}
free ( fname );
fname = NULL;
if ( !( corr_functions = (double(**)(const AI_snort_alert*, const AI_snort_alert*))
realloc ( corr_functions, (++n_corr_functions) * sizeof ( double(*)(const AI_snort_alert*, const AI_snort_alert*) ))))
{
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
}
*(void**) (&(corr_functions[ n_corr_functions - 1 ])) = dlsym ( dl_handles[n_dl_handles-1], "AI_corr_index" );
if ( !corr_functions[ n_corr_functions - 1 ] )
{
if (( err = dlerror() ))
{
_dpd.errMsg ( "dlsym: %s\n", err );
}
AI_fatal_err ( "dlsym error", __FILE__, __LINE__ );
}
if ( !( weight_functions = (double(**)()) realloc ( weight_functions, (++n_weight_functions) * sizeof ( double(*)() ))))
{
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
}
*(void**) (&(weight_functions[ n_weight_functions - 1 ])) = dlsym ( dl_handles[n_dl_handles-1], "AI_corr_index_weight" );
if ( !weight_functions[ n_weight_functions - 1 ] )
{
if (( err = dlerror() ))
{
_dpd.errMsg ( "dlsym: %s\n", err );
}
AI_fatal_err ( "dlsym error", __FILE__, __LINE__ );
}
}
}
closedir ( dir );
} /* ----- end of function AI_init_corr_modules ----- */
/** @} */

View file

@ -251,7 +251,7 @@ __AI_som_train ()
if ( !( res = (DB_result) DB_out_query ( query )))
{
AI_fatal_err ( "AIPreproc: Query error", __FILE__, __LINE__ );
return;
}
num_rows = DB_num_rows ( res );
@ -277,7 +277,7 @@ __AI_som_train ()
{
row = (DB_row) DB_fetch_row ( res );
tuples[i].gid = row[0] ? strtoul ( row[0], NULL, 10 ) : 0;
tuples[i].sid = row[1] ? strtoul ( row[1], NULL, 10 ) : 0;
tuples[i].rev = row[2] ? strtoul ( row[2], NULL, 10 ) : 0;
tuples[i].timestamp = row[3] ? (time_t) strtol ( row[3], NULL, 10 ) : (time_t) 0;

View file

@ -110,6 +110,9 @@ static void AI_init(char *args)
sfPolicyUserPolicySet(ex_config, policy_id);
sfPolicyUserDataSetCurrent(ex_config, config);
/* Initialize the extra correlation modules */
AI_init_corr_modules();
/* If the hash_cleanup_interval or stream_expire_interval options are set to zero,
* no cleanup will be made on the streams */
if ( config->hashCleanupInterval != 0 && config->streamExpireInterval != 0 )
@ -173,8 +176,9 @@ static AI_config * AI_parse(char *args)
char alertfile[1024] = { 0 },
alert_history_file[1024] = { 0 },
clusterfile[1024] = { 0 },
corr_rules_dir[1024] = { 0 },
corr_alerts_dir[1024] = { 0 },
corr_modules_dir[1024] = { 0 },
corr_rules_dir[1024] = { 0 },
webserv_dir[1024] = { 0 },
webserv_banner[1024] = { 0 };
@ -209,6 +213,7 @@ static AI_config * AI_parse(char *args)
clusterfile_len = 0,
cluster_max_alert_interval = 0,
corr_alerts_dir_len = 0,
corr_modules_dir_len = 0,
corr_rules_dir_len = 0,
correlation_graph_interval = 0,
database_parsing_interval = 0,
@ -224,6 +229,7 @@ static AI_config * AI_parse(char *args)
has_stream_expire_interval = false,
has_correlation_interval = false,
has_corr_alerts_dir = false,
has_corr_modules_dir = false,
has_database_interval = false,
has_webserv_dir = false,
has_webserv_banner = false,
@ -791,6 +797,46 @@ static AI_config * AI_parse(char *args)
_dpd.logMsg(" webserv_dir: %s\n", config->webserv_dir);
/* Parsing the corr_modules_dir option */
if (( arg = (char*) strcasestr( args, "corr_modules_dir" ) ))
{
for ( arg += strlen("corr_modules_dir");
*arg && *arg != '"';
arg++ );
if ( !(*(arg++)) )
{
AI_fatal_err ( "corr_modules_dir option used but no filename specified", __FILE__, __LINE__ );
}
for ( corr_modules_dir[ (++corr_modules_dir_len)-1 ] = *arg;
*arg && *arg != '"' && corr_modules_dir_len < sizeof ( corr_modules_dir );
arg++, corr_modules_dir[ (++corr_modules_dir_len)-1 ] = *arg );
if ( corr_modules_dir[0] == 0 || corr_modules_dir_len <= 1 ) {
has_corr_modules_dir = false;
} else {
if ( corr_modules_dir_len >= sizeof ( corr_modules_dir )) {
AI_fatal_err ( "corr_modules_dir path too long ( >= 1024 )", __FILE__, __LINE__ );
} else if ( strlen( corr_modules_dir ) == 0 ) {
has_corr_modules_dir = false;
} else {
has_corr_modules_dir = true;
corr_modules_dir[ corr_modules_dir_len-1 ] = 0;
strncpy ( config->corr_modules_dir, corr_modules_dir, corr_modules_dir_len );
}
}
}
if ( ! has_corr_modules_dir )
{
#ifndef HAVE_CONFIG_H
AI_fatal_err ( "Unable to read PREFIX from config.h", __FILE__, __LINE__ );
#endif
snprintf ( config->corr_modules_dir, sizeof ( config->corr_modules_dir ), "%s/share/snort_ai_preprocessor/corr_modules", PREFIX );
}
/* Neural network output file */
if ( config->neuralNetworkTrainingInterval != 0 )
{

View file

@ -94,7 +94,7 @@
/** Default number of alerts needed in the history file or database for letting a certain
* heuristic correlation index weight be =~ 0.95 (the weight monotonically increases
* with the number of alerts according to a hyperbolic tangent function) */
#define DEFAULT_ALERT_CORRELATION_WEIGHT 400
#define DEFAULT_ALERT_CORRELATION_WEIGHT 5000
/** Default web server port */
#define DEFAULT_WEBSERV_PORT 7654
@ -105,7 +105,7 @@
/** Cutoff y value in the exponential decay for considering two alerts not correlated */
#define CUTOFF_Y_VALUE 0.01
/** Approximated solution of the equation tanh(x) = 0.95 */
/** Approximated solution of the equation tanh(x) = 0.95 (used as parameter in the correlation indexes weight function) */
#define HYPERBOLIC_TANGENT_SOLUTION 1.83178
/****************************/
@ -233,6 +233,9 @@ typedef struct
* and in the footer of error pages */
char webserv_banner[1024];
/** Directory containing extra correlation modules */
char corr_modules_dir[1024];
/** Alert file */
char alertfile[1024];
@ -486,6 +489,7 @@ void AI_pkt_enqueue ( SFSnortPacket* );
void AI_set_stream_observed ( struct pkt_key key );
void AI_hierarchies_build ( hierarchy_node**, int );
void AI_free_alerts ( AI_snort_alert *node );
void AI_init_corr_modules ();
struct pkt_info* AI_get_stream_by_key ( struct pkt_key );
AI_snort_alert* AI_get_alerts ( void );
@ -508,6 +512,9 @@ void* AI_store_alert_to_db_thread ( void* );
void* AI_store_cluster_to_db_thread ( void* );
void* AI_store_correlation_to_db_thread ( void* );
double(**AI_get_corr_functions ( size_t* ))(const AI_snort_alert*, const AI_snort_alert*);
double(**AI_get_corr_weights ( size_t* ))();
/** Function pointer to the function used for getting the alert list (from log file, db, ...) */
extern AI_snort_alert* (*get_alerts)(void);