SCaLE 2016 - syslog-ng: From Raw Data to Big Data

syslog-ng: from raw data to Big Data
Scale 14x, Los Angles
Peter Czanik / Balabit

2
About me
■ Peter Czanik from Hungary
■ Community manager at BalaBit: syslog-ng upstream
■ Doing syslog-ng packaging, support, advocating
■ BalaBit is an IT security company with development HQ in Budapest,
Hungary
■ Over 200 employees: the majority are engineers

3
syslog-ng
■ Logging: recording events, like this one:
□ Jan 14 11:38:48 linux-0jbu sshd[7716]: Accepted publickey for root from
127.0.0.1 port 48806 ssh2
■ syslog-ng: enhanced logging daemon, with a focus on central log
collection.
□ Not only syslog
□ Processing and filtering messages
□ Storing to a central location or forwarding to a wide variety of destinations

5
syslog-ng and Big Data
syslog-ng can facilitate the data pipeline to Big Data in many ways:
■ Data collector
■ Data processor
■ Data filtering

6
syslog-ng: data collector
Collect system and application logs together: contextual data for either side
■ A wide variety of platform specific sources:
□ /dev/log & Co
□ Journal, Sun streams
■ Receive syslog messages over the network
□ Legacy or RFC5424, UDP/TCP/TLS
■ Logs or any kind of data from applications:
□ Through files, sockets, pipes, etc.
□ Application output

7
syslog-ng: processing
Process messages close to the source: easier filtering, lower load on the
consumer side
■ classify, normalize and structure logs with built-in parsers:
□ CSV-parser, DB-parser (PatternDB), JSON parser
■ rewrite messages:
□ for example anonymization
■ Reformatting messages using templates:
□ Destination might need a specific format (ISO date, JSON, etc.)
■ Enrich data:
□ GeoIP, additional fields based on message content

8
syslog-ng: data filtering
Main uses:
■ Message routing (login events to SIEM, smtp logs to separate file, etc.)
■ Throw away surplus logs (don't store debug level messages to SQL)
Many possibilities:
■ Based on message content, parameters or macros
■ Using comparisons, wildcards, regular expressions and functions
■ Combining all of these with boolean operators

9
syslog-ng “Big Data” destinations
■ Distributed file systems:
□ Hadoop
■ NoSQL databases:
□ MongoDB
□ Elasticsearch
■ Messaging systems:
□ Kafka

10
Free-form log messages
■ Most log messages are: date + hostname + text
Mar 11 13:37:56 linux-6965 sshd[4547]: Accepted keyboard-
interactive/pam for root from 127.0.0.1 port 46048 ssh2
■ Text = English sentence with some variable parts
■ Easy to read by a human
■ Difficult to process them with scripts

11
Solution: structured logging
■ Events represented as name-value pairs
■ Example: an ssh login:
□ source_ip=192.168.123.45
□ app=sshd
□ user=root
■ syslog-ng: name-value pairs inside
□ Date, facility, priority, program name, pid, etc.
■ Parsers in syslog-ng can turn unstructured and some structured data (csv,
JSON) into name value pairs

12
JSON parser
■ Turns JSON based log messages into name-value pairs
■ {"PROGRAM":"prg00000","PRIORITY":"info","PID":"1234","MESSAGE":"s
eq: 0000000000, thread: 0000, runid: 1374490607, stamp: 2013-07-
22T12:56:47 MESSAGE...
","HOST":"localhost","FACILITY":"auth","DATE":"Jul 22 12:56:47"}

13
csv parser
■ csv-parser: parses columnar data into fields
parser p_apache {
csv-parser(columns("APACHE.CLIENT_IP", "APACHE.IDENT_NAME", "APACHE.USER_NAME",
"APACHE.TIMESTAMP", "APACHE.REQUEST_URL", "APACHE.REQUEST_STATUS",
"APACHE.CONTENT_LENGTH", "APACHE.REFERER", "APACHE.USER_AGENT",
"APACHE.PROCESS_TIME", "APACHE.SERVER_NAME")
flags(escape-double-char,strip-whitespace) delimiters(" ") quote-pairs('""[]')
);
};
destination d_file { file("/var/log/messages-${APACHE.USER_NAME:-nouser}"); };
log { source(s_local); parser(p_apache); destination(d_file);};

14
PatternDB parser
■ PatternDB message parser:
□ Can extract useful information from unstructured messages into name-value
pairs
□ Add status fields based on message text
□ Message classification (like LogCheck)
■ Needs XML describing log messages
■ Example: an ssh login failure:
□ user=root, source_ip=192.168.123.45, action=login, status=failure
□ classified as “violation”

15
Anonymizing messages
■ Many regulations about what can be logged
□ PCI-DSS: credit card numbers
□ Europe: IP addresses, user names
■ Locating sensitive information:
□ Regular expressions: slow, works also in unknown logs
□ Patterndb: fast, only in known log messages
■ Anonymizing:
□ Overwrite it with constant
□ Overwrite it with a hash of the original

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Language bindings in syslog-ng
■ The primary language of syslog-ng is C:
□ High performance: processes a lot more EPS than interpreted languages
■ Not everything is implemented in C
■ Rapid prototyping is easier in interpreted languages
■ Python & Java destinations in syslog-ng, Lua & Perl in incubator
□ Embedded interpreter
□ Message or full range of name value pairs can be passed
□ Proper error handling

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Java based “Big Data” destinations
■ Most of “Big Data” is written in Java
■ C and Python clients exist, but Java is official and maintained together
with the server component
■ More effort to get started:
□ Due to missing JARs and build tools (gradle) not yet in distributions
□ libjvm.so needs to be added to LD_LIBRARY_PATH
■ https://czanik.blogs.balabit.com/2015/08/getting-started-with-syslog-ng-3-
7-1-and-elasticsearch-hadoop-kafka/

18
Configuration
■ “Don't Panic”
■ Simple and logical, even if looks difficult first
■ Pipeline model:
□ Many different building blocks (sources, destinations, filters, parsers, etc.)
□ Connected using “log” statements into a pipeline

19
syslog-ng.conf: global options
@version:3.7
@include "scl.conf"
# this is a comment :)
options {
flush_lines (0);
# [...]
keep_hostname (yes);
};

20
syslog-ng.conf: sources
source s_sys {
system();
internal();
};
source s_net {
udp(ip(0.0.0.0) port(514));
};

21
syslog-ng.conf: destinations
destination d_mesg { file("/var/log/messages"); };
destination d_es {
elasticsearch(
index("syslog-ng_${YEAR}.${MONTH}.${DAY}")
type("test")
cluster("syslog-ng")
template("$(format-json --scope rfc3164 --scope nv-pairs --exclude R_DATE --key ISODATE)n");
);
};

22
syslog-ng.conf: filters, parsers
filter f_nodebug { level(info..emerg); };
filter f_messages { level(info..emerg) and
not (facility(mail)
or facility(authpriv)
or facility(cron)); };
parser pattern_db {
db-parser(file("/opt/syslog-ng/etc/patterndb.xml") );
};

23
syslog-ng.conf: logpath
log { source(s_sys); filter(f_messages); destination(d_mesg); };
log {
source(s_net);
source(s_sys);
filter(f_nodebug);
parser(pattern_db);
destination(d_es);
flags(flow-control);
};

24
Patterndb & ElasticSearch & Kibana

25
Kafka
■ Publish – subscribe messaging
■ Data backbone for data driven organizations
□ LinkedIn
□ Spotify
■ Kafka destination is already in syslog-ng
□ Source is planned

26
syslog-ng benefits for Big Data
■ High performance reliable log collection
■ Simplified architecture
□ Single application for both syslog and application data
■ Easier to use data
□ Parsed and presented in a ready to use format
■ Lower load on destinations
□ Efficient message filtering and routing

27
Joining the community
■ syslog-ng: http://syslog-ng.org/
■ Source on GitHub: https://github.com/balabit/syslog-ng
■ Mailing list: https://lists.balabit.hu/pipermail/syslog-ng/
■ IRC: #syslog-ng on freenode
■ University students:
□ open trainee positions!
□ syslog-ng universe

28
Questions?
■ Questions?
□ My blog: http://czanik.blogs.balabit.com/
□ My e-mail: peter.czanik@balabit.com

30
Sample XML
■ <?xml version='1.0' encoding='UTF-8'?>
■ <patterndb version='3' pub_date='2010-07-13'>
■ <ruleset name='opensshd' id='2448293e-6d1c-412c-a418-a80025639511'>
■ <pattern>sshd</pattern>
■ <rules>
■ <rule provider="patterndb" id="4dd5a329-da83-4876-a431-ddcb59c2858c" class="system">
■ <patterns>
■ <pattern>Accepted @ESTRING:usracct.authmethod: @for @ESTRING:usracct.username: @from @ESTRING:usracct.device: @port @ESTRING::
@@ANYSTRING:usracct.service@</pattern>
■ </patterns>
■ <examples>
■ <example>
■ <test_message program="sshd">Accepted password for bazsi from 127.0.0.1 port 48650 ssh2</test_message>
■ <test_values>
■ <test_value name="usracct.username">bazsi</test_value>
■ <test_value name="usracct.authmethod">password</test_value>
■ <test_value name="usracct.device">127.0.0.1</test_value>
■ <test_value name="usracct.service">ssh2</test_value>
■ </test_values>
■ </example>
■ </examples>
■ <values>
■ <value name="usracct.type">login</value>
■ <value name="usracct.sessionid">$PID</value>
■ <value name="usracct.application">$PROGRAM</value>
■ <value name="secevt.verdict">ACCEPT</value>
■ </values>
■ </rule>

SCaLE 2016 - syslog-ng: From Raw Data to Big Data

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SCaLE 2016 - syslog-ng: From Raw Data to Big Data