Aggregating many different types sensors into a single data source (e.g. syslog) and ingesting that aggregate sensor into Metron is a common pattern. It is not obvious precisely how to manage these types of aggregate sensors as they require two-pass parsing. This document will walk through an example of supporting this kind of multi-pass ingest.
Multi-pass parser involves the following requirements:
- The enveloping parser (e.g. the aggregation format such as syslog or plain CSV) may contain metadata which should be ingested along with the data.
- The enveloping sensor contains many different sensor types
At a high level, we continue to maintain the architectural invariant of a 1-1 relationship between logical sensors and storm topologies. Eventually this relationship may become more complex, but at the moment the approach is to construct a routing parser which will have two responsibilities:
- Parse the envelope (e.g. syslog data) and extract any metadata fields from the envelope to pass along
- Route the unfolded data to the appropriate kafka topic associated with the enveloped sensor data
Because the data emitted from the routing parser is just like any data emitted from any other parser, in that it is a JSON blob like any data emitted from any parser, we will need to adjust the downstream parsers to extract the enveloped data from the JSON blob and treat it as the data to parse.
We assume that the following environment variables are set:
METRON_HOME
- the home directory for metronZOOKEEPER
- The zookeeper quorum (comma separated with port specified: e.g.node1:2181
for full-dev)BROKERLIST
- The Kafka broker list (comma separated with port specified: e.g.node1:6667
for full-dev)ES_HOST
- The elasticsearch master (and port) e.g.node1:9200
for full-dev.
Before editing configurations, be sure to pull the configs from zookeeper locally via
$METRON_HOME/bin/zk_load_configs.sh --mode PULL -z $ZOOKEEPER -o $METRON_HOME/config/zookeeper/ -f
Consider the following situation, we have some logs from a Cisco PIX device that we would like to ingest. The format is syslog, but multiple scenarios exist in the same log file. Specificaly, let's consider the sample logs here.
The log lines in general have the following components:
- A timestamp
- A message type tag
- The message payload that is dependent upon the tag
Let's consider two types of messages that we'd like to parse:
- Tag
6-302*
which are connection creation and teardown messages e.g.Built UDP connection for faddr 198.207.223.240/53337 gaddr 10.0.0.187/53 laddr 192.168.0.2/53
- Tag
5-304*
which are URL access events e.g.192.168.0.2 Accessed URL 66.102.9.99:/
A couple things are apparent from this:
- The formats we care about are easy to represent in grok, but are very different and logically represent very different sensors.
- The syslog loglines output by this device has many types of events that I do not care about (yet).
We will proceed to create 3 separate parsers:
- A
pix_syslog_router
parser which will:- Parse the timestamp field
- Parse the payload into a field called
data
- Parse the tag into a field called
pix_type
- Route the enveloped messages to the appropriate kafka topic based on the tag
- A
cisco-6-302
andcisco-5-304
parser which will append to the existing fields from thepix_syslog_router
the sensor specific fields based on the tag type.
In order to assist in these parsers, we're going to accumulate some grok expressions which will help us deal with these various parsers.
- Open a file
~/cisco_patterns
and place the following in there
CISCO_ACTION Built|Teardown|Deny|Denied|denied|requested|permitted|denied by ACL|discarded|est-allowed|Dropping|created|deleted
CISCO_REASON Duplicate TCP SYN|Failed to locate egress interface|Invalid transport field|No matching connection|DNS Response|DNS Query|(?:%{WORD}\s*)*
CISCO_DIRECTION Inbound|inbound|Outbound|outbound
CISCOFW302020_302021 %{CISCO_ACTION:action}(?:%{CISCO_DIRECTION:direction})? %{WORD:protocol} connection %{GREEDYDATA:ignore} faddr %{IP:ip_dst_addr}/%{INT:icmp_seq_num}(?:\(%{DATA:fwuser}\))? gaddr %{IP:ip_src_xlated}/%{INT:icmp_code_xlated} laddr %{IP:ip_src_addr}/%{INT:icmp_code}( \(%{DATA:user}\))?
ACCESSED %{URIHOST:ip_src_addr} Accessed URL %{IP:ip_dst_addr}:%{URIPATHPARAM:uri_path}
CISCO_PIX %{GREEDYDATA:timestamp}: %PIX-%{NOTSPACE:pix_type}: %{GREEDYDATA:data}
- Place this pattern in HDFS at
/tmp/cisco_patterns
viahadoop fs -put ~/cisco_patterns /tmp
- NOTE: In production, we'd have more battle hardened patterns as well as place them in a more sensible location.
- Create the
pix_syslog_router
kafka topic via:
/usr/hdp/current/kafka-broker/bin/kafka-topics.sh --zookeeper $ZOOKEEPER --create --topic pix_syslog_router --partitions 1 --replication-factor 1
- Create the
pix_syslog_router
parser by opening$METRON_HOME/config/zookeeper/parsers/pix_syslog_router.json
and placing the following:
{
"parserClassName" : "org.apache.metron.parsers.GrokParser"
,"sensorTopic" : "pix_syslog_router"
, "parserConfig": {
"grokPath": "/tmp/cisco_patterns",
"batchSize" : 1,
"patternLabel": "CISCO_PIX",
"timestampField": "timestamp",
"timeFields" : [ "timestamp" ],
"dateFormat" : "MMM dd yyyy HH:mm:ss",
"kafka.topicField" : "logical_source_type"
}
,"fieldTransformations" : [
{
"transformation" : "REGEX_SELECT"
,"input" : "pix_type"
,"output" : "logical_source_type"
,"config" : {
"cisco-6-302" : "^6-302.*",
"cisco-5-304" : "^5-304.*"
}
}
]
}
A couple of things to note about this config:
- In the
parserConfig
section, note that we are specifyingkafka.topicField
islogical_source_field
. This specifies that the parser will send messages to the topic specified in thelogical_source_type
field. If the field does not exist, then the message is not sent. - The
REGEX_SELECT
field transformation sets thelogical_source_type
field based on the value in thepix_type
field, which recall is our tag. This will enable us to route the broad category of cisco firewall messages along to the specific parser.
- Create the
cisco-6-302
kafka topic via:
/usr/hdp/current/kafka-broker/bin/kafka-topics.sh --zookeeper $ZOOKEEPER --create --topic cisco-6-302 --partitions 1 --replication-factor 1
- Create the
cisco-6-302
parser by opening$METRON_HOME/config/zookeeper/parsers/cisco-6-302.json
and placing the following:
{
"parserClassName" : "org.apache.metron.parsers.GrokParser"
,"sensorTopic" : "cisco-6-302"
,"rawMessageStrategy" : "ENVELOPE"
,"rawMessageStrategyConfig" : {
"messageField" : "data",
"metadataPrefix" : ""
}
, "parserConfig": {
"grokPath": "/tmp/cisco_patterns",
"batchSize" : 1,
"patternLabel": "CISCOFW302020_302021"
}
}
Note a couple of things:
- We are specifying the
rawMessageStrategy
to beENVELOPE
to indicate that it is not a straight data feed, but rather it's enveloped in a JSON map (i.e. the output of the `pix_syslog_router) - Because this is enveloped, we must specify the field which contains the actual raw data by setting
messageField
inrawMessageStrategyConfig
- You may be wondering why we specify
metadataPrefix
to be empty string. We want some of the fields in the enveloped message to be merged in without prefix. Most specifically, we want thetimestamp
field. By default, the prefix ismetron.metadata
.
- Create the
cisco-5-304
kafka topic via:
/usr/hdp/current/kafka-broker/bin/kafka-topics.sh --zookeeper $ZOOKEEPER --create --topic cisco-5-304 --partitions 1 --replication-factor 1
- Create the
cisco-5-304
parser by opening$METRON_HOME/config/zookeeper/parsers/cisco-5-304.json
and placing the following:
{
"parserClassName" : "org.apache.metron.parsers.GrokParser"
,"sensorTopic" : "cisco-5-304"
,"rawMessageStrategy" : "ENVELOPE"
,"rawMessageStrategyConfig" : {
"messageField" : "data",
"metadataPrefix" : ""
}
, "parserConfig": {
"grokPath": "/tmp/cisco_patterns",
"batchSize" : 1,
"patternLabel": "ACCESSED"
}
}
Mostly the same comments from the previous parser apply here; we are just using a different pattern label.
Now we should start the parsers
- Push the configs that we've created for the 3 parsers:
$METRON_HOME/bin/zk_load_configs.sh --mode PUSH -z $ZOOKEEPER -i $METRON_HOME/config/zookeeper/
- Start the
cisco-6-302
parser via
$METRON_HOME/bin/start_parser_topology.sh -k $BROKERLIST -z $ZOOKEEPER -s cisco-6-302
- Start the
cisco-5-304
parser via
$METRON_HOME/bin/start_parser_topology.sh -k $BROKERLIST -z $ZOOKEEPER -s cisco-5-304
- Start the
pix_syslog_router
parser via
$METRON_HOME/bin/start_parser_topology.sh -k $BROKERLIST -z $ZOOKEEPER -s pix_syslog_router
- Create a file called
~/data.log
with the sample syslog loglines here. - Send the data in via kafka console producer
cat ~/data.log | /usr/hdp/current/kafka-broker/bin/kafka-console-producer.sh --broker-list $BROKERLIST --topic pix_syslog_router
You should see indices created for the cisco-5-304
and cisco-6-302
data with appropriate fields created for each type.
Chained parsers can be run as aggregated parsers. These parsers continue to use the sensor specific Kafka topics, and do not do internal routing to the appropriate sensor.
Instead of creating a topology per sensor, all 3 (pix-syslog-parser
, cisco-5-304
, and cisco-6-302
) can be run in a single aggregated parser. It's also possible to aggregate a subset of these parsers (e.g. run cisco-6-302
as it's own topology, and aggregate the other 2).
The step to start parsers then becomes
$METRON_HOME/bin/start_parser_topology.sh -k $BROKERLIST -z $ZOOKEEPER -s cisco-6-302,cisco-5-304,pix_syslog_router
The flow through the Storm topology and Kafka topics: