blacklight/Snort_AIPreproc
1
0
Fork 0
mirror of https://github.com/BlackLight/Snort_AIPreproc.git synced 2024-11-14 12:47:16 +01:00
Code Issues Projects Releases Packages Wiki Activity
Snort_AIPreproc/correlation.c
BlackLight e406b637f0 Python module rewritten in pure Python
2011-02-04 00:43:59 +01:00

711 lines
21 KiB
C
Raw Blame History

/*
* =====================================================================================
*
* Filename: correlation.c
*
* Description: Runs the correlation algorithm of the alerts
*
* Version: 0.1
* Created: 07/09/2010 22:04:27
* 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 <alloca.h>
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>
#include <sys/stat.h>
#include <time.h>
#ifdef HAVE_LIBGVC
#include <gvc.h>
#endif
#ifdef HAVE_LIBPYTHON2_6
/*******************************************/
/* Avoid conflicts with Snort header files */
#ifdef _POSIX_C_SOURCE
#undef _POSIX_C_SOURCE
#endif
#ifdef _XOPEN_C_SOURCE
#undef _XOPEN_C_SOURCE
#endif
#ifdef _XOPEN_SOURCE
#undef _XOPEN_SOURCE
#endif
/*******************************************/
#include <Python.h>
#endif
/** \defgroup correlation Module for the correlation of security alerts
* @{ */
PRIVATE AI_snort_alert *alerts = NULL;
PRIVATE AI_alert_correlation *correlation_table = NULL;
PRIVATE pthread_mutex_t mutex;
/**
* \brief Clean up the correlation hash table
*/
PRIVATE void
__AI_correlation_table_cleanup ()
{
AI_alert_correlation *current;
while ( correlation_table )
{
current = correlation_table;
HASH_DEL ( correlation_table, current );
free ( current );
}
} /* ----- end of function __AI_correlation_table_cleanup ----- */
/**
* \brief Recursively write a flow of correlated alerts to a .dot file, ready for being rendered as graph
* \param corr Correlated alerts
* \param fp File pointer
*/
PRIVATE void
__AI_correlated_alerts_to_dot ( AI_alert_correlation *corr, FILE *fp )
{
char src_addr1[INET_ADDRSTRLEN],
dst_addr1[INET_ADDRSTRLEN],
src_addr2[INET_ADDRSTRLEN],
dst_addr2[INET_ADDRSTRLEN],
src_port1[10],
dst_port1[10],
src_port2[10],
dst_port2[10];
if ( !corr )
return;
inet_ntop ( AF_INET, &(corr->key.a->ip_src_addr), src_addr1, INET_ADDRSTRLEN );
inet_ntop ( AF_INET, &(corr->key.a->ip_dst_addr), dst_addr1, INET_ADDRSTRLEN );
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 ));
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 ));
fprintf ( fp,
"\t\"[%d.%d.%d] %s\\n"
"%s:%s -> %s:%s\\n"
"(%d alerts grouped)\" -> "
"\"[%d.%d.%d] %s\\n"
"%s:%s -> %s:%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,
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,
corr->key.b->grouped_alerts_count
);
} /* ----- end of function __AI_correlated_alerts_to_dot ----- */
/**
* \brief Recursively write the flow of correlated alerts to a .json file, ready for being rendered in the web interface
*/
PRIVATE void
__AI_correlated_alerts_to_json ()
{
AI_snort_alert *alert_iterator = NULL;
struct pkt_info *pkt_iterator = NULL;
FILE *fp;
unsigned int i = 0,
pkt_len = 0;
char *strtime = NULL,
*encoded_pkt = NULL,
json_file[1040] = { 0 },
srcip[INET_ADDRSTRLEN] = { 0 },
dstip[INET_ADDRSTRLEN] = { 0 },
srcport[10] = { 0 },
dstport[10] = { 0 };
/* If there is no directory configured for the web interface, just exit */
if ( strlen ( config->webserv_dir ) == 0 )
return;
snprintf ( json_file, sizeof ( json_file ), "%s/correlation_graph.json", config->webserv_dir );
if ( !( fp = fopen ( json_file, "w" )))
{
AI_fatal_err ( "Unable to write on correlated_graph.json in htdocs directory", __FILE__, __LINE__ );
}
fprintf ( fp, "[\n" );
for ( alert_iterator = alerts; alert_iterator; alert_iterator = alert_iterator->next )
{
strtime = ctime ( &(alert_iterator->timestamp ));
strtime[ strlen(strtime) - 1 ] = 0;
inet_ntop ( AF_INET, &(alert_iterator->ip_src_addr), srcip, INET_ADDRSTRLEN );
inet_ntop ( AF_INET, &(alert_iterator->ip_dst_addr), dstip, INET_ADDRSTRLEN );
snprintf ( srcport, sizeof ( srcport ), "%d", htons ( alert_iterator->tcp_src_port ));
snprintf ( dstport, sizeof ( dstport ), "%d", htons ( alert_iterator->tcp_dst_port ));
fprintf ( fp, "{\n"
"\t\"id\": %lu,\n"
"\t\"snortSID\": \"%u\",\n"
"\t\"snortGID\": \"%u\",\n"
"\t\"snortREV\": \"%u\",\n"
"\t\"label\": \"%s\",\n"
"\t\"date\": \"%s\",\n"
"\t\"clusteredAlertsCount\": %u,\n"
"\t\"from\": \"%s:%s\",\n"
"\t\"to\": \"%s:%s\",\n"
"\t\"latitude\": \"%f\",\n"
"\t\"longitude\": \"%f\"",
alert_iterator->alert_id,
alert_iterator->sid,
alert_iterator->gid,
alert_iterator->rev,
alert_iterator->desc,
strtime,
alert_iterator->grouped_alerts_count,
srcip, srcport, dstip, dstport,
alert_iterator->geocoord[0],
alert_iterator->geocoord[1]
);
if ( alert_iterator->stream )
{
fprintf ( fp, ",\n"
"\t\"packets\": [\n" );
for ( pkt_iterator = alert_iterator->stream; pkt_iterator; pkt_iterator = pkt_iterator->next )
{
encoded_pkt = NULL;
pkt_len = pkt_iterator->pkt->pcap_header->len + pkt_iterator->pkt->payload_size;
if ( !( encoded_pkt = (char*) calloc ( 4*pkt_len + 1, sizeof ( char ))))
{
AI_fatal_err ( "Fatal dynamic memory allocation", __FILE__, __LINE__ );
}
base64_encode (
(const char*) pkt_iterator->pkt->pkt_data,
pkt_len,
&encoded_pkt
);
fprintf ( fp, "\t\t\"%s\"%s\n",
encoded_pkt, ((pkt_iterator->next) ? "," : ""));
free ( encoded_pkt );
encoded_pkt = NULL;
}
fprintf ( fp, "\t]" );
}
for ( i=1; i < alert_iterator->grouped_alerts_count; i++ )
{
if ( i == 1 )
{
fprintf ( fp, ",\n\t\"clusteredAlerts\": [\n" );
}
if ( alert_iterator->grouped_alerts )
{
if ( alert_iterator->grouped_alerts[i] )
{
strtime = ctime ( &(alert_iterator->grouped_alerts[i]->timestamp ));
strtime[ strlen ( strtime ) - 1 ] = 0;
inet_ntop ( AF_INET, &(alert_iterator->grouped_alerts[i]->ip_src_addr), srcip, INET_ADDRSTRLEN );
inet_ntop ( AF_INET, &(alert_iterator->grouped_alerts[i]->ip_dst_addr), dstip, INET_ADDRSTRLEN );
snprintf ( srcport, sizeof ( srcport ), "%d", htons ( alert_iterator->grouped_alerts[i]->tcp_src_port ));
snprintf ( dstport, sizeof ( dstport ), "%d", htons ( alert_iterator->grouped_alerts[i]->tcp_dst_port ));
fprintf ( fp, "\t\t{\n"
"\t\t\t\"id\": %lu,\n"
"\t\t\t\"label\": \"%s\",\n"
"\t\t\t\"date\": \"%s\",\n"
"\t\t\t\"from\": \"%s:%s\",\n"
"\t\t\t\"to\": \"%s:%s\",\n"
"\t\t\t\"latitude\": \"%f\",\n"
"\t\t\t\"longitude\": \"%f\"%s",
alert_iterator->grouped_alerts[i]->alert_id,
alert_iterator->grouped_alerts[i]->desc,
strtime,
srcip, srcport, dstip, dstport,
alert_iterator->grouped_alerts[i]->geocoord[0],
alert_iterator->grouped_alerts[i]->geocoord[1],
(( alert_iterator->grouped_alerts[i]->stream ) ? ",\n" : "\n" )
);
if ( alert_iterator->grouped_alerts[i]->stream )
{
fprintf ( fp, "\t\t\t\"packets\": [\n" );
for ( pkt_iterator = alert_iterator->grouped_alerts[i]->stream; pkt_iterator; pkt_iterator = pkt_iterator->next )
{
if ( !pkt_iterator->pkt->ip4_header )
{
pkt_len = pkt_iterator->pkt->pcap_header->len +
pkt_iterator->pkt->tcp_options_length +
pkt_iterator->pkt->payload_size;
} else {
pkt_len = pkt_iterator->pkt->ip4_header->data_length;
}
if ( !( encoded_pkt = (char*) malloc ( 4*pkt_len + 1 )))
{
AI_fatal_err ( "Fatal dynamic memory allocation", __FILE__, __LINE__ );
}
memset ( encoded_pkt, 0, 4*pkt_len + 1 );
base64_encode (
(const char*) pkt_iterator->pkt->pkt_data,
pkt_len,
&encoded_pkt
);
fprintf ( fp, "\t\t\t\t\"%s\"%s\n",
encoded_pkt, ((pkt_iterator->next) ? "," : ""));
}
fprintf ( fp, "\t\t\t]\n" );
}
fprintf ( fp,
"\t\t}%s\n",
(( i < alert_iterator->grouped_alerts_count - 1 ) ? "," : "" ));
}
}
if ( i == alert_iterator->grouped_alerts_count - 1 )
{
fprintf ( fp, "\t]" );
}
}
for ( i=0; i < alert_iterator->n_derived_alerts; i++ )
{
if ( i == 0 )
{
fprintf ( fp, ",\n\t\"connectedTo\": [\n" );
}
fprintf ( fp, "\t\t{ \"id\": %lu }%s\n",
alert_iterator->derived_alerts[i]->alert_id,
((i < alert_iterator->n_derived_alerts - 1) ? "," : ""));
if ( i == alert_iterator->n_derived_alerts - 1 )
{
fprintf ( fp, "\t]" );
}
}
fprintf ( fp, "\n}%s\n",
(alert_iterator->next ? "," : ""));
}
fprintf ( fp, "]\n" );
fclose ( fp );
chmod ( json_file, 0644 );
} /* ----- end of function __AI_correlated_alerts_to_json ----- */
/**
* \brief Thread for correlating clustered alerts
*/
void*
AI_alert_correlation_thread ( void *arg )
{
int i;
struct stat st;
char corr_dot_file[4096] = { 0 };
#ifdef HAVE_LIBGVC
char corr_ps_file [4096] = { 0 };
#endif
double avg_correlation = 0.0,
std_deviation = 0.0,
corr_threshold = 0.0,
kb_correlation = 0.0,
bayesian_correlation = 0.0,
neural_correlation = 0.0;
size_t n_correlations = 0,
n_corr_functions = 0,
n_corr_weights = 0;
FILE *fp = NULL;
AI_alert_correlation_key corr_key;
AI_alert_correlation *corr = NULL;
AI_alert_type_pair_key pair_key;
AI_alert_type_pair *pair = NULL,
*unpair = NULL;
AI_snort_alert *alert_iterator = NULL,
*alert_iterator2 = NULL;
pthread_t manual_corr_thread;
#ifdef HAVE_LIBGVC
char corr_png_file[4096] = { 0 };
GVC_t *gvc = NULL;
graph_t *g = NULL;
#endif
double (**corr_functions)( const AI_snort_alert*, const AI_snort_alert* ) = NULL;
double (**corr_weights)() = NULL;
#ifdef HAVE_LIBPYTHON2_6
PyObject *pyA = NULL,
*pyB = NULL;
PyObject *pArgs = NULL,
*pRet = NULL;
PyObject **py_corr_functions = NULL;
PyObject **py_weight_functions = NULL;
size_t n_py_corr_functions = 0;
size_t n_py_weight_functions = 0;
double py_value = 0.0,
py_weight = 0.0;
#endif
corr_functions = AI_get_corr_functions ( &n_corr_functions );
corr_weights = AI_get_corr_weights ( &n_corr_weights );
py_corr_functions = AI_get_py_functions ( &n_py_corr_functions );
py_weight_functions = AI_get_py_weights ( &n_py_weight_functions );
pthread_mutex_init ( &mutex, NULL );
/* Start the thread for parsing manual correlations from XML */
if ( pthread_create ( &manual_corr_thread, NULL, AI_manual_correlations_parsing_thread, NULL ) != 0 )
{
AI_fatal_err ( "Failed to create the manual correlations parsing thread", __FILE__, __LINE__ );
}
while ( 1 )
{
sleep ( config->correlationGraphInterval );
if ( stat ( config->corr_rules_dir, &st ) < 0 )
{
_dpd.errMsg ( "AIPreproc: Correlation rules directory '%s' not found, the correlation thread won't be active\n",
config->corr_rules_dir );
pthread_exit (( void* ) 0 );
return ( void* ) 0;
}
/* Set the lock flag to true, and keep it this way until I've done with correlating alerts */
pthread_mutex_lock ( &mutex );
if ( alerts )
{
AI_free_alerts ( alerts );
alerts = NULL;
}
if ( !( alerts = AI_get_clustered_alerts() ))
{
pthread_mutex_unlock ( &mutex );
continue;
}
if ( config->use_knowledge_base_correlation_index != 0 )
{
AI_kb_index_init ( alerts );
}
__AI_correlation_table_cleanup();
correlation_table = NULL;
/* Fill the table of correlated alerts */
for ( alert_iterator = alerts; alert_iterator; alert_iterator = alert_iterator->next )
{
for ( alert_iterator2 = alerts; alert_iterator2; alert_iterator2 = alert_iterator2->next )
{
if ( alert_iterator != alert_iterator2 && ! (
alert_iterator->gid == alert_iterator2->gid &&
alert_iterator->sid == alert_iterator2->sid &&
alert_iterator->rev == alert_iterator2->rev ))
{
if ( !( corr = ( AI_alert_correlation* ) malloc ( sizeof ( AI_alert_correlation ))))
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
corr_key.a = alert_iterator;
corr_key.b = alert_iterator2;
corr->key = corr_key;
corr->correlation = 0.0;
n_correlations = 0;
kb_correlation = AI_kb_correlation_coefficient ( corr_key.a, corr_key.b );
bayesian_correlation = AI_alert_bayesian_correlation ( corr_key.a, corr_key.b );
neural_correlation = AI_alert_neural_som_correlation ( corr_key.a, corr_key.b );
/* Use the correlation indexes for which we have a value */
if ( bayesian_correlation != 0.0 && config->bayesianCorrelationInterval != 0 )
{
corr->correlation += AI_bayesian_correlation_weight() * bayesian_correlation;
n_correlations++;
}
if ( kb_correlation != 0.0 && config->use_knowledge_base_correlation_index )
{
corr->correlation += kb_correlation;
n_correlations++;
}
if ( neural_correlation != 0.0 && config->neuralNetworkTrainingInterval != 0 )
{
corr->correlation += AI_neural_correlation_weight() * neural_correlation;
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++;
}
}
}
#ifdef HAVE_LIBPYTHON2_6
if (( py_corr_functions ))
{
pyA = AI_alert_to_pyalert ( corr_key.a );
pyB = AI_alert_to_pyalert ( corr_key.b );
if ( pyA && pyB )
{
for ( i=0; i < n_py_corr_functions; i++ )
{
if ( !( pArgs = Py_BuildValue ( "(OO)", pyA, pyB )))
{
PyErr_Print();
AI_fatal_err ( "Could not initialize the Python arguments for the call", __FILE__, __LINE__ );
}
if ( !( pRet = PyEval_CallObject ( py_corr_functions[i], pArgs )))
{
PyErr_Print();
AI_fatal_err ( "Could not call the correlation function from the Python module", __FILE__, __LINE__ );
}
if ( !( PyArg_Parse ( pRet, "d", &py_value )))
{
PyErr_Print();
AI_fatal_err ( "Could not parse the correlation value out of the Python correlation function", __FILE__, __LINE__ );
}
Py_DECREF ( pRet );
Py_DECREF ( pArgs );
if ( !( pRet = PyEval_CallObject ( py_weight_functions[i], (PyObject*) NULL )))
{
PyErr_Print();
AI_fatal_err ( "Could not call the correlation function from the Python module", __FILE__, __LINE__ );
}
if ( !( PyArg_Parse ( pRet, "d", &py_weight )))
{
PyErr_Print();
AI_fatal_err ( "Could not parse the correlation weight out of the Python correlation function", __FILE__, __LINE__ );
}
Py_DECREF ( pRet );
if ( py_weight != 0.0 )
{
corr->correlation += py_weight * py_value;
n_correlations++;
}
}
Py_DECREF ( pyA ); Py_DECREF ( pyB );
/* free ( pyA ); free ( pyB ); */
pyA = NULL; pyB = NULL;
}
}
#endif
if ( n_correlations != 0 )
{
corr->correlation /= (double) n_correlations;
}
HASH_ADD ( hh, correlation_table, key, sizeof ( AI_alert_correlation_key ), corr );
}
}
}
if ( HASH_COUNT ( correlation_table ) > 0 )
{
avg_correlation = 0.0;
std_deviation = 0.0;
/* Compute the average correlation coefficient */
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
{
avg_correlation += corr->correlation;
}
avg_correlation /= (double) HASH_COUNT ( correlation_table );
/* Compute the standard deviation */
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
{
std_deviation += ( corr->correlation - avg_correlation ) * ( corr->correlation - avg_correlation );
}
std_deviation = sqrt ( std_deviation / (double) HASH_COUNT ( correlation_table ));
corr_threshold = avg_correlation + ( config->correlationThresholdCoefficient * std_deviation );
snprintf ( corr_dot_file, sizeof ( corr_dot_file ), "%s/correlated_alerts.dot", config->corr_alerts_dir );
if ( stat ( config->corr_alerts_dir, &st ) < 0 )
{
if ( mkdir ( config->corr_alerts_dir, 0755 ) < 0 )
{
AI_fatal_err ( "Unable to create directory the correlated alerts directory", __FILE__, __LINE__ );
}
} else if ( !S_ISDIR ( st.st_mode )) {
AI_fatal_err ( "The specified directory for correlated alerts is not a directory", __FILE__, __LINE__ );
}
if ( !( fp = fopen ( corr_dot_file, "w" )))
AI_fatal_err ( "Could not write on the correlated alerts .dot file", __FILE__, __LINE__ );
fprintf ( fp, "digraph G {\n" );
/* Find correlated alerts */
for ( corr = correlation_table; corr; corr = ( AI_alert_correlation* ) corr->hh.next )
{
pair_key.from_sid = corr->key.a->sid;
pair_key.from_gid = corr->key.a->gid;
pair_key.from_rev = corr->key.a->rev;
pair_key.to_sid = corr->key.b->sid;
pair_key.to_gid = corr->key.b->gid;
pair_key.to_rev = corr->key.b->rev;
HASH_FIND ( hh, manual_correlations, &pair_key, sizeof ( pair_key ), pair );
HASH_FIND ( hh, manual_uncorrelations, &pair_key, sizeof ( pair_key ), unpair );
/* Yes, BlackLight wrote this line of code in a pair of minutes and immediately
* compiled it without a single error */
if ( !unpair && ( pair || (
corr->correlation >= corr_threshold &&
corr_threshold != 0.0 &&
corr->key.a->timestamp <= corr->key.b->timestamp && ! (
corr->key.a->gid == corr->key.b->gid &&
corr->key.a->sid == corr->key.b->sid &&
corr->key.a->rev == corr->key.b->rev ) && (
corr->key.a->ip_src_addr == corr->key.b->ip_src_addr || (
(corr->key.a->h_node[src_addr] && corr->key.b->h_node[src_addr]) ?
( corr->key.a->h_node[src_addr]->max_val == corr->key.b->h_node[src_addr]->max_val &&
corr->key.a->h_node[src_addr]->min_val == corr->key.b->h_node[src_addr]->min_val ) : 0
)) && (
corr->key.a->ip_dst_addr == corr->key.b->ip_dst_addr || (
(corr->key.a->h_node[dst_addr] && corr->key.b->h_node[dst_addr]) ?
( corr->key.a->h_node[dst_addr]->max_val == corr->key.b->h_node[dst_addr]->max_val &&
corr->key.a->h_node[dst_addr]->min_val == corr->key.b->h_node[dst_addr]->min_val ) : 0
))
)
)
) {
if ( !( corr->key.a->derived_alerts = ( AI_snort_alert** ) realloc ( corr->key.a->derived_alerts,
(++corr->key.a->n_derived_alerts) * sizeof ( AI_snort_alert* ))))
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
if ( !( corr->key.b->parent_alerts = ( AI_snort_alert** ) realloc ( corr->key.b->parent_alerts,
(++corr->key.b->n_parent_alerts) * sizeof ( AI_snort_alert* ))))
AI_fatal_err ( "Fatal dynamic memory allocation error", __FILE__, __LINE__ );
corr->key.a->derived_alerts[ corr->key.a->n_derived_alerts - 1 ] = corr->key.b;
corr->key.b->parent_alerts [ corr->key.b->n_parent_alerts - 1 ] = corr->key.a;
__AI_correlated_alerts_to_dot ( corr, fp );
if ( config->outdbtype != outdb_none )
{
AI_store_correlation_to_db ( corr );
}
}
}
fprintf ( fp, "}\n" );
fclose ( fp );
#ifdef HAVE_LIBGVC
snprintf ( corr_png_file, sizeof ( corr_png_file ), "%s/correlated_alerts.png", config->corr_alerts_dir );
snprintf ( corr_ps_file , sizeof ( corr_ps_file ), "%s/correlated_alerts.ps" , config->corr_alerts_dir );
if ( !( gvc = gvContext() ))
continue;
if ( !( fp = fopen ( corr_dot_file, "r" )))
continue;
if ( !( g = agread ( fp )))
continue;
gvLayout ( gvc, g, "dot" );
gvRenderFilename ( gvc, g, "png", corr_png_file );
gvRenderFilename ( gvc, g, "ps" , corr_ps_file );
gvFreeLayout ( gvc, g );
agclose ( g );
fclose ( fp );
#endif
/* If no database output is defined, then the alerts have no alert_id, so we cannot use the
* web interface for correlating them, as they have no unique identifier */
if ( config->outdbtype != outdb_none )
{
if ( strlen ( config->webserv_dir ) != 0 )
{
__AI_correlated_alerts_to_json ();
}
}
}
pthread_mutex_unlock ( &mutex );
}
pthread_exit (( void* ) 0 );
return (void*) 0;
} /* ----- end of function AI_alert_correlation_thread ----- */
/** @} */
Reference in a new issue View git blame Copy permalink