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syslog-ng Premium Edition 7.0.32 - Administration Guide

Preface Introduction to syslog-ng The concepts of syslog-ng Installing syslog-ng PE The syslog-ng PE quick-start guide The syslog-ng PE configuration file Collecting log messages — sources and source drivers
How sources work default-network-drivers: Receive and parse common syslog messages internal: Collecting internal messages file: Collecting messages from text files google-pubsub: collecting messages from the Google Pub/Sub messaging service wildcard-file: Collecting messages from multiple text files linux-audit: Collecting messages from Linux audit logs mssql, oracle, sql: collecting messages from an SQL database network: Collecting messages using the RFC3164 protocol (network() driver) office365: Fetching logs from Office 365 osquery: Collect and parse osquery result logs pipe: Collecting messages from named pipes program: Receiving messages from external applications python: writing server-style Python sources python-fetcher: writing fetcher-style Python sources snmptrap: Read Net-SNMP traps syslog: Collecting messages using the IETF syslog protocol (syslog() driver) system: Collecting the system-specific log messages of a platform systemd-journal: Collecting messages from the systemd-journal system log storage systemd-syslog: Collecting systemd messages using a socket tcp, tcp6,udp, udp6: Collecting messages from remote hosts using the BSD syslog protocol udp-balancer: Receiving UDP messages at very high rate unix-stream, unix-dgram: Collecting messages from UNIX domain sockets windowsevent: Collecting Windows event logs
Sending and storing log messages — destinations and destination drivers
elasticsearch2>: Sending messages directly to Elasticsearch version 2.0 or higher (DEPRECATED) elasticsearch-http: Sending messages to Elasticsearch HTTP Event Collector file: Storing messages in plain-text files google_pubsub(): Sending logs to the Google Cloud Pub/Sub messaging service google_pubsub-managedaccount(): Sending logs to the Google Cloud Pub/Sub messaging service authenticated by Google Cloud managed service account hdfs: Storing messages on the Hadoop Distributed File System (HDFS) http: Posting messages over HTTP kafka(): Publishing messages to Apache Kafka (Java implementation) (DEPRECATED) kafka-c(): Publishing messages to Apache Kafka using the librdkafka client (C implementation) logstore: Storing messages in encrypted files mongodb: Storing messages in a MongoDB database network: Sending messages to a remote log server using the RFC3164 protocol (network() driver) pipe: Sending messages to named pipes program: Sending messages to external applications python: writing custom Python destinations sentinel(): Sending logs to the Microsoft Azure Sentinel cloud snmp: Sending SNMP traps smtp: Generating SMTP messages (email) from logs splunk-hec: Sending messages to Splunk HTTP Event Collector sql(): Storing messages in an SQL database stackdriver: Sending logs to the Google Stackdriver cloud syslog: Sending messages to a remote logserver using the IETF-syslog protocol syslog-ng(): Forward logs to another syslog-ng node tcp, tcp6, udp, udp6: Sending messages to a remote log server using the legacy BSD-syslog protocol (tcp(), udp() drivers) unix-stream, unix-dgram: Sending messages to UNIX domain sockets usertty: Sending messages to a user terminal — usertty() destination Client-side failover
Routing messages: log paths, flags, and filters Global options of syslog-ng PE TLS-encrypted message transfer Advanced Log Transport Protocol Reliability and minimizing the loss of log messages Manipulating messages parser: Parse and segment structured messages Processing message content with a pattern database Correlating log messages Enriching log messages with external data Monitoring statistics and metrics of syslog-ng Multithreading and scaling in syslog-ng PE Troubleshooting syslog-ng Best practices and examples The syslog-ng manual pages Glossary

iptables parser

The iptables parser can parse the log messages of the iptables command. Available in version 7.0.9 and later.

Declaration
@version: 7.0
@include "scl.conf"
log {
    source { system(); };
    parser { iptables-parser(); };
    destination { ... };
};

The iptables-parser() is actually a reusable configuration snippet configured to parse iptables messages. For details on using or writing such configuration snippets, see Reusing configuration blocks. You can find the source of this configuration snippet on GitHub.

prefix()
Synopsis: prefix()

Description: Insert a prefix before the name part of the parsed name-value pairs to help further processing. For example:

  • To insert the my-parsed-data. prefix, use the prefix(my-parsed-data.) option.

  • To refer to a particular data that has a prefix, use the prefix in the name of the macro, for example, ${my-parsed-data.name} .

  • If you forward the parsed messages using the IETF-syslog protocol, you can insert all the parsed data into the SDATA part of the message using the prefix(.SDATA.my-parsed-data.) option.

Names starting with a dot (for example, .example) are reserved for use by syslog-ng PE. If you use such a macro name as the name of a parsed value, it will attempt to replace the original value of the macro (note that only soft macros can be overwritten, see Hard versus soft macros for details). To avoid such problems, use a prefix when naming the parsed values, for example, prefix(my-parsed-data.)

By default, iptables-parser() uses the .iptables. prefix. To modify it, use the following format:

parser { 
    iptables-parser(prefix("myprefix.")); 
};

Processing message content with a pattern database

Classifying log messages

The syslog-ng application can compare the contents of the received log messages to predefined message patterns. By comparing the messages to the known patterns, syslog-ng is able to identify the exact type of the messages, and sort them into message classes. The message classes can be used to classify the type of the event described in the log message. The message classes can be customized, and for example, can label the messages as user login, application crash, file transfer, and so on events.

To find the pattern that matches a particular message, syslog-ng uses a method called longest prefix match radix tree. This means that syslog-ng creates a tree structure of the available patterns, where the different characters available in the patterns for a given position are the branches of the tree.

To classify a message, syslog-ng selects the first character of the message (the text of message, not the header), and selects the patterns starting with this character, other patterns are ignored for the rest of the process. After that, the second character of the message is compared to the second character of the selected patterns. Again, matching patterns are selected, and the others discarded. This process is repeated until a single pattern completely matches the message, or no match is found. In the latter case, the message is classified as unknown, otherwise the class of the matching pattern is assigned to the message.

To make the message classification more flexible and robust, the patterns can contain pattern parsers: elements that match on a set of characters. For example, the NUMBER parser matches on any integer or hexadecimal number (for example, 1, 123, 894054, 0xFFFF, and so on). Other pattern parsers match on various strings and IP addresses. For the details of available pattern parsers, see Using pattern parsers.

The functionality of the pattern database is similar to that of the logcheck project, but it is much easier to write and maintain the patterns used by syslog-ng, than the regular expressions used by logcheck. Also, it is much easier to understand syslog-ng pattens than regular expressions.

Pattern matching based on regular expressions is computationally very intensive, especially when the number of patterns increases. The solution used by syslog-ng can be performed real-time, and is independent from the number of patterns, so it scales much better. The following patterns describe the same message: Accepted password for bazsi from 10.50.0.247 port 42156 ssh2

A regular expression matching this message from the logcheck project: Accepted (gssapi(-with-mic|-keyex)?|rsa|dsa|password|publickey|keyboard-interactive/pam) for [^[:space:]]+ from [^[:space:]]+ port [0-9]+( (ssh|ssh2))?

A syslog-ng database pattern for this message: Accepted @QSTRING:auth_method: @ for@QSTRING:username: @from @QSTRING:client_addr: @port @NUMBER:port:@ ssh2

For details on using pattern databases to classify log messages, see Using pattern databases.

The structure of the pattern database

The pattern database is organized as follows:

Figure 42: The structure of the pattern database

  • The pattern database consists of rulesets. A ruleset consists of a Program Pattern and a set of rules: the rules of a ruleset are applied to log messages if the name of the application that sent the message matches the Program Pattern of the ruleset. The name of the application (the content of the ${PROGRAM} macro) is compared to the Program Patterns of the available rulesets, and then the rules of the matching rulesets are applied to the message.

  • The Program Pattern can be a string that specifies the name of the appliation or the beginning of its name (for example, to match for sendmail, the program pattern can be sendmail, or just send), and the Program Pattern can contain pattern parsers. Note that pattern parsers are completely independent from the syslog-ng parsers used to segment messages. Additionally, every rule has a unique identifier: if a message matches a rule, the identifier of the rule is stored together with the message.

  • Rules consist of a message pattern and a class. The Message Pattern is similar to the Program Pattern, but is applied to the message part of the log message (the content of the ${MESSAGE} macro). If a message pattern matches the message, the class of the rule is assigned to the message (for example, Security, Violation, and so on).

  • Rules can also contain additional information about the matching messages, such as the description of the rule, an URL, name-value pairs, or free-form tags. This information is displayed by the syslog-ng Premium Edition in the email alerts (if alerts are requested for the rule), and are also displayed on the search interface.

  • Patterns can consist of literals (keywords, or rather, keycharacters) and pattern parsers.

    NOTE: If the ${PROGRAM} part of a message is empty, rules with an empty Program Pattern are used to classify the message.

    If the same Program Pattern is used in multiple rulesets, the rules of these rulesets are merged, and every rule is used to classify the message. Note that message patterns must be unique within the merged rulesets, but the currently only one ruleset is checked for uniqueness.

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