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https://github.com/BlackLight/Snort_AIPreproc.git
synced 2024-11-13 04:07:15 +01:00
Now supporting clustering with time constraints
This commit is contained in:
parent
c022edc637
commit
a454d15d29
7 changed files with 181 additions and 26 deletions
6
README
6
README
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@ -160,6 +160,7 @@ preprocessor ai: \
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correlation_threshold_coefficient 0.5 \
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database ( type="mysql", name="snort", user="snortusr", password="snortpass", host="dbhost" ) \
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database_parsing_interval 30 \
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cluster_max_alert_interval 14400 \
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clusterfile "/your/snort/dir/log/clustered_alerts" \
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cluster ( class="dst_port", name="privileged_ports", range="1-1023" ) \
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cluster ( class="dst_port", name="unprivileged_ports", range="1024-65535" ) \
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@ -253,6 +254,11 @@ the alerts from database and the next one (default if not specified: 30 seconds)
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- clusterfile: File where the clustered alerts will be saved by the module
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(default if not specified: /var/log/snort/clustered_alerts)
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- cluster_max_alert_interval: Maximum time interval, in seconds, occurred
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between two alerts for considering them as part of the same cluster (default:
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14400 seconds, i.e. 4 hours). Specify 0 for this option if you want to
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cluster alerts regardlessly of how much time occurred between them
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- cluster: Clustering hierarchy or list of hierarchies to be applied for
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grouping similar alerts. This option needs to specify:
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-- class: Class of the cluster node. It may be src_addr, dst_addr, src_port
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5
TODO
5
TODO
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@ -2,12 +2,12 @@
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AVERAGE/HIGH PRIORITY:
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======================
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- Clustering alerts with time constraints
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- Save clusters and correlations to db
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- Web interface
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- Code profiling
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- Comment all the code!!!
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- Saving packet flows as .pcap
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- Neural network for computing k
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- Isolating independant subgraphs from hyperalert correlation graphs
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- Testing more scenarios, making more hyperalert models
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=============
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@ -30,4 +30,5 @@ DONE:
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+ Add alerts' history serialization to db.c as well
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+ Bayesian learning among alerts in alert log
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+ Split bayesian correlation out of correlation.c
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+ Clustering alerts with time constraints
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@ -19,6 +19,7 @@
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#include "spp_ai.h"
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#include <stdio.h>
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#include <sys/stat.h>
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/** \defgroup alert_history Manage the serialization and deserialization of alert history to the history file
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@ -159,7 +159,6 @@ AI_alert_bayesian_correlation ( AI_snort_alert *a, AI_snort_alert *b )
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found->latest_computation_time = time ( NULL );
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}
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/* _dpd.logMsg ( "Correlation ('%s') -> ('%s'): %f\\n", a->desc, b->desc, corr ); */
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return corr;
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} /* ----- end of function AI_alert_bayesian_correlation ----- */
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34
cluster.c
34
cluster.c
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@ -213,7 +213,7 @@ _AI_get_min_hierarchy_node ( int val, hierarchy_node *root )
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*/
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PRIVATE BOOL
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_AI_equal_alarms ( AI_snort_alert *a1, AI_snort_alert *a2 )
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_AI_equal_alerts ( AI_snort_alert *a1, AI_snort_alert *a2 )
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{
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if ( a1->gid != a2->gid || a1->sid != a2->sid || a1->rev != a2->rev )
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{
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@ -249,7 +249,7 @@ _AI_equal_alarms ( AI_snort_alert *a1, AI_snort_alert *a2 )
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}
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return true;
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} /* ----- end of function _AI_equal_alarms ----- */
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} /* ----- end of function _AI_equal_alerts ----- */
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/**
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@ -270,26 +270,24 @@ _AI_merge_alerts ( AI_snort_alert **log )
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{
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if ( tmp2->next )
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{
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if ( !(
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tmp->gid == tmp2->next->gid &&
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tmp->sid == tmp2->next->sid &&
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tmp->rev == tmp2->next->rev &&
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tmp->timestamp == tmp2->next->timestamp &&
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tmp->ip_src_addr == tmp2->next->ip_src_addr &&
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tmp->ip_dst_addr == tmp2->next->ip_dst_addr &&
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tmp->tcp_src_port == tmp2->next->tcp_src_port &&
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tmp->tcp_dst_port == tmp2->next->tcp_dst_port ))
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/* If the two alerts are in the same clustering time window (if a time window was defined...) */
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if ( config->clusterMaxAlertInterval == 0 ||
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( config->clusterMaxAlertInterval > 0 && abs ( tmp->timestamp - tmp2->next->timestamp ) <= config->clusterMaxAlertInterval ))
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{
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if ( _AI_equal_alarms ( tmp, tmp2->next ))
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if ( tmp != tmp2->next )
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{
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if ( !( tmp->grouped_alerts = ( AI_snort_alert** ) realloc ( tmp->grouped_alerts, (++(tmp->grouped_alerts_count)) * sizeof ( AI_snort_alert* ))))
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_dpd.fatalMsg ( "AIPreproc: Fatal dynamic memory allocation error at %s:%d\n", __FILE__, __LINE__ );
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/* If the two alerts are equal... */
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if ( _AI_equal_alerts ( tmp, tmp2->next ))
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{
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if ( !( tmp->grouped_alerts = ( AI_snort_alert** ) realloc ( tmp->grouped_alerts, (++(tmp->grouped_alerts_count)) * sizeof ( AI_snort_alert* ))))
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_dpd.fatalMsg ( "AIPreproc: Fatal dynamic memory allocation error at %s:%d\n", __FILE__, __LINE__ );
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tmp->grouped_alerts[ tmp->grouped_alerts_count - 1 ] = tmp2->next;
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count++;
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tmp->grouped_alerts[ tmp->grouped_alerts_count - 1 ] = tmp2->next;
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count++;
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tmp3 = tmp2->next->next;
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tmp2->next = tmp3;
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tmp3 = tmp2->next->next;
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tmp2->next = tmp3;
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}
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}
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}
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134
spp_ai.c
134
spp_ai.c
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@ -166,6 +166,7 @@ static AI_config * AI_parse(char *args)
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bayesian_correlation_interval = 0,
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bayesian_correlation_cache_validity = 0,
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clusterfile_len = 0,
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cluster_max_alert_interval = 0,
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corr_rules_dir_len = 0,
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corr_alerts_dir_len = 0,
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alert_clustering_interval = 0,
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@ -182,6 +183,7 @@ static AI_config * AI_parse(char *args)
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has_corr_rules_dir = false,
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has_clustering = false,
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has_database_log = false,
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has_database_output = false,
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has_alert_history_file = false;
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if ( !( config = ( AI_config* ) malloc ( sizeof( AI_config )) ))
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@ -388,6 +390,27 @@ static AI_config * AI_parse(char *args)
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_dpd.logMsg( " Bayesian cache validity interval: %u\n", config->bayesianCorrelationCacheValidity );
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/* Parsing the cluster_max_alert_interval option */
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if (( arg = (char*) strcasestr( args, "cluster_max_alert_interval" ) ))
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{
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for ( arg += strlen("cluster_max_alert_interval");
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*arg && (*arg < '0' || *arg > '9');
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arg++ );
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if ( !(*arg) )
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{
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_dpd.fatalMsg("AIPreproc: cluster_max_alert_interval option used but "
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"no value specified\n");
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}
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cluster_max_alert_interval = strtoul ( arg, NULL, 10 );
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} else {
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cluster_max_alert_interval = DEFAULT_CLUSTER_MAX_ALERT_INTERVAL;
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}
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config->clusterMaxAlertInterval = cluster_max_alert_interval;
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_dpd.logMsg( " Cluster alert max interval: %u\n", config->clusterMaxAlertInterval );
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/* Parsing the alertfile option */
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if (( arg = (char*) strcasestr( args, "alertfile" ) ))
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{
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@ -550,7 +573,7 @@ static AI_config * AI_parse(char *args)
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}
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/* Parsing database option */
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if ( preg_match ( "\\s*database\\s*\\(\\s*([^\\)]+)\\)", args, &matches, &nmatches ) > 0 )
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if ( preg_match ( "\\s+database\\s*\\(\\s*([^\\)]+)\\)", args, &matches, &nmatches ) > 0 )
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{
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if ( ! has_database_log )
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has_database_log = true;
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@ -627,8 +650,109 @@ static AI_config * AI_parse(char *args)
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{
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_dpd.fatalMsg ( "AIPreproc: Database option used in config, but missing configuration option (all 'host', 'type', 'name', 'user', and 'password' option must be used)\n" );
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}
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_dpd.logMsg(" Reading alerts from the database %s\n", config->dbname );
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}
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/* Parsing output_database option */
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if ( preg_match ( "\\s*output_database\\s*\\(\\s*([^\\)]+)\\)", args, &matches, &nmatches ) > 0 )
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{
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if ( ! has_database_output )
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has_database_output = true;
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match = strdup ( matches[0] );
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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if ( preg_match ( "type\\s*=\\s*\"([^\"]+)\"", match, &matches, &nmatches ) > 0 )
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{
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if ( strcasecmp ( matches[0], "mysql" ) && strcasecmp ( matches[0], "postgresql" ))
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{
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_dpd.fatalMsg ( "AIPreproc: Not supported database '%s' (supported types: mysql, postgresql)\n", matches[0] );
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}
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if ( !strcasecmp ( matches[0], "mysql" ))
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{
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#ifndef HAVE_LIBMYSQLCLIENT
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_dpd.fatalMsg ( "AIPreproc: mysql output set in 'output_database' option but the module was not compiled through --with-mysql option\n" );
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#else
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config->outdbtype = mysql;
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#endif
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} else if ( !strcasecmp ( matches[0], "postgresql" )) {
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#ifndef HAVE_LIBPQ
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_dpd.fatalMsg ( "AIPreproc: postgresql output set in 'output_database' option but the module was not compiled through --with-postgresql option\n" );
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#else
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config->outdbtype = postgresql;
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#endif
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}
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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}
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if ( preg_match ( "name\\s*=\\s*\"([^\"]+)\"", match, &matches, &nmatches ) > 0 )
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{
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strncpy ( config->outdbname, matches[0], sizeof ( config->outdbname ));
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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}
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if ( preg_match ( "user\\s*=\\s*\"([^\"]+)\"", match, &matches, &nmatches ) > 0 )
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{
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strncpy ( config->outdbuser, matches[0], sizeof ( config->outdbuser ));
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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}
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if ( preg_match ( "password\\s*=\\s*\"([^\"]+)\"", match, &matches, &nmatches ) > 0 )
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{
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strncpy ( config->outdbpass, matches[0], sizeof ( config->outdbpass ));
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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}
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if ( preg_match ( "host\\s*=\\s*\"([^\"]+)\"", match, &matches, &nmatches ) > 0 )
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{
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strncpy ( config->outdbhost, matches[0], sizeof ( config->outdbhost ));
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for ( i=0; i < nmatches; i++ )
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free ( matches[i] );
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free ( matches );
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matches = NULL;
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}
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free ( match );
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if ( !strlen ( config->outdbhost ) || !strlen ( config->outdbname ) || !strlen ( config->outdbpass ) || !strlen ( config->outdbuser ))
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{
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_dpd.fatalMsg ( "AIPreproc: Output database option used in config, but missing configuration option (all 'host', 'type', 'name', 'user', and 'password' options must be used)\n" );
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}
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_dpd.logMsg(" Saving output alerts to the database %s\n", config->outdbname );
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}
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/* Parsing cluster options */
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while ( preg_match ( "\\s*(cluster\\s*\\(\\s*)([^\\)]+)\\)", args, &matches, &nmatches ) > 0 )
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{
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@ -877,8 +1001,8 @@ static AI_config * AI_parse(char *args)
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#ifdef HAVE_DB
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alertparser_thread = AI_db_alertparser_thread;
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#else
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_dpd.fatalMsg ( "AIPreproc: database logging enabled in config file, but the module was not compiled "
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"with database support (recompile, i.e., with ./configure --with-mysql or --with-postgresql)\n" );
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_dpd.fatalMsg ( "AIPreproc: database logging enabled in config file, but the module was not compiled "
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"with database support (recompile, i.e., with ./configure --with-mysql or --with-postgresql)\n" );
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#endif
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} else if ( has_alertfile ) {
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alertparser_thread = AI_file_alertparser_thread;
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@ -924,7 +1048,7 @@ static AI_config * AI_parse(char *args)
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}
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}
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_dpd.logMsg ( "Using correlation rules from directory %s\n", config->corr_rules_dir );
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_dpd.logMsg ( " Using correlation rules from directory %s\n", config->corr_rules_dir );
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if ( ! has_corr_alerts_dir )
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{
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@ -941,7 +1065,7 @@ static AI_config * AI_parse(char *args)
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config->alert_bufsize = DEFAULT_ALERT_BUFSIZE;
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}
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_dpd.logMsg ( "Saving correlated alerts information in %s\n", config->corr_alerts_dir );
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_dpd.logMsg ( " Saving correlated alerts information in %s\n", config->corr_alerts_dir );
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if ( has_database_log )
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{
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26
spp_ai.h
26
spp_ai.h
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@ -75,6 +75,9 @@
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/** Default interval of validity in seconds for an entry in the cache of correlated alerts */
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#define DEFAULT_BAYESIAN_CORRELATION_CACHE_VALIDITY 600
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/** Default maximum interval, in seconds, between two alerts for being considered in the same cluster */
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#define DEFAULT_CLUSTER_MAX_ALERT_INTERVAL 14400
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/** Cutoff y value in the exponential decay for considering two alerts not correlated */
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#define CUTOFF_Y_VALUE 0.01
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/** Interval in seconds between two alerts (a,b) for considering them correlated */
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unsigned long bayesianCorrelationInterval;
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/** Default maximum interval, in seconds, between two alerts for being considered in the same cluster */
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unsigned long clusterMaxAlertInterval;
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/** Interval in seconds for which an entry in the cache of correlated alerts is valid */
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unsigned long bayesianCorrelationCacheValidity;
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/** Database host, if database logging is used */
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char dbhost[256];
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/** Output database type, if clustered alerts and
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* correlations are saved to a database as well */
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enum { mysql, postgresql } outdbtype;
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/** Output database name, if clustered alerts and
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* correlations are saved to a database as well */
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char outdbname[256];
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/** Output database user, if clustered alerts and
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* correlations are saved to a database as well */
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char outdbuser[256];
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/** Output database password, if clustered alerts and
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* correlations are saved to a database as well */
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char outdbpass[256];
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/** Output database host, if clustered alerts and
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* correlations are saved to a database as well */
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char outdbhost[256];
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} AI_config;
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/*****************************************************************/
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/** Data type for hierarchies used for clustering */
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