syslog-ng Open Source Edition 3.16 - Administration Guide

Element: tags

<tags><tag>UserLogin</tag></tags>

Correlating log messages

The syslog-ng OSE application can correlate log messages. Alternatively, you can also correlate log messages using pattern databases. For details, see Correlating log messages using pattern databases.

• To group or correlate log messages that match a set of filters, use the grouping-by parser. This works similarly to SQL GROUP BY statements. For details, see Correlating messages using the grouping-by() parser.

• You can correlate log messages identified using pattern databases. For details, see Correlating log messages using pattern databases.

Log messages are supposed to describe events, but applications often separate information about a single event into different log messages. For example, the Postfix e-mail server logs the sender and recipient addresses into separate log messages, or in case of an unsuccessful login attempt, the OpenSSH server sends a log message about the authentication failure, and the reason of the failure in the next message. Of course, messages that are not so directly related can be correlated as well, for example, login-logout messages, and so on.

To correlate log messages with syslog-ng OSE, you can add messages into message-groups called contexts. A context consists of a series of log messages that are related to each other in some way, for example, the log messages of an SSH session can belong to the same context. As new messages come in, they may be added to a context. Also, when an incoming message is identified it can trigger actions to be performed, for example, generate a new message that contains all the important information that was stored previously in the context.

Correlating messages using the grouping-by() parser

The syslog-ng OSE application can correlate log messages that match a set of filters. This works similarly to SQL GROUP BY statements. Alternatively, you can also correlate log messages using pattern databases. For details, see Correlating log messages using pattern databases.

Log messages are supposed to describe events, but applications often separate information about a single event into different log messages. For example, the Postfix e-mail server logs the sender and recipient addresses into separate log messages, or in case of an unsuccessful login attempt, the OpenSSH server sends a log message about the authentication failure, and the reason of the failure in the next message. Of course, messages that are not so directly related can be correlated as well, for example, login-logout messages, and so on.

To correlate log messages with syslog-ng OSE, you can add messages into message-groups called contexts. A context consists of a series of log messages that are related to each other in some way, for example, the log messages of an SSH session can belong to the same context. As new messages come in, they may be added to a context. Also, when an incoming message is identified it can trigger actions to be performed, for example, generate a new message that contains all the important information that was stored previously in the context.

    +--------------------+
    |Incoming log message|
    +--------------------+
              |
              |
              |
              |
              V
    +-------------------------------------------+    No
    |Does it match key(), scope(), and where()? +----------> Ignore message
    +-------------------------------------------+
              |
              |
              V
    Add message to context
              |
              |
              v                    No
    Is it a trigger() message or --------> Wait until timeout() or a new message
    has the timeout() expired?
             +
             |
             |
             v                              No
    Does the context match having()? +-------------> Close the context
            +                                         and do nothing
            |
            |
            v
    Inject the aggregate() log message and close the context
    

parser parser_name {
    grouping-by(
        key()
        having()
        aggregate()
        timeout()
    );
};

For the parser to work, you must set at least the following options: key(), aggregate(), and timeout().

Note the following points about timeout values:

• When a new message is added to a context, syslog-ng OSE will restart the timeout using the context-timeout set for the new message.

• When calculating if the timeout has already expired or not, syslog-ng OSE uses the timestamps of the incoming messages, not system time elapsed between receiving the two messages (unless the messages do not include a timestamp, or the keep-timestamp(no) option is set). That way syslog-ng OSE can be used to process and correlate already existing log messages offline. However, the timestamps of the messages must be in chronological order (that is, a new message cannot be older than the one already processed), and if a message is newer than the current system time (that is, it seems to be coming from the future), syslog-ng OSE will replace its timestamp with the current system time.

  Example: How syslog-ng OSE calculates context-timeout

  Consider the following two messages:

  <38>1990-01-01T14:45:25 customhostname program6[1234]: program6 testmessage
  <38>1990-01-01T14:46:25 customhostname program6[1234]: program6 testmessage

  If the context-timeout is 10 seconds and syslog-ng OSE receives the messages within 1 sec, the timeout event will occour immediately, because the difference of the two timestamp (60 sec) is larger than the timeout value (10 sec).

• Avoid using unnecessarily long timeout values on high-traffic systems, as storing the contexts for many messages can require considerable memory. For example, if two related messages usually arrive within seconds, it is not needed to set the timeout to several hours.

type=SYSCALL msg=audit(1440927434.124:40347): arch=c000003e syscall=59 success=yes exit=0 a0=7f121cef0b88 a1=7f121cef0c00 a2=7f121e690d98 a3=2 items=2 ppid=4312 pid=4347 auid=4294967295 uid=0 gid=0 euid=0 suid=0 fsuid=0 egid=0 sgid=0 fsgid=0 tty=(none) ses=4294967295 comm="ntpdate" exe="/usr/sbin/ntpdate" key=(null)
type=EXECVE msg=audit(1440927434.124:40347): argc=3 a0="/usr/sbin/ntpdate" a1="-s" a2="ntp.ubuntu.com"
type=CWD msg=audit(1440927434.124:40347):  cwd="/"
type=PATH msg=audit(1440927434.124:40347): item=0 name="/usr/sbin/ntpdate" inode=2006003 dev=08:01 mode=0100755 ouid=0 ogid=0 rdev=00:00 nametype=NORMAL
type=PATH msg=audit(1440927434.124:40347): item=1 name="/lib64/ld-linux-x86-64.so.2" inode=5243184 dev=08:01 mode=0100755 ouid=0 ogid=0 rdev=00:00 nametype=NORMAL
type=PROCTITLE msg=audit(1440927434.124:40347): proctitle=2F62696E2F7368002F7573722F7362696E2F6E7470646174652D64656269616E002D73

parser auditd_groupingby {
    grouping-by(
        key("${.auditd.msg}")
        aggregate(
            value("MESSAGE" "$(format-json .auditd.*)")
        )
        timeout(10)
    );
};

Referencing earlier messages of the context

When creating the aggregated message, or in the various parameters of the grouping-by() parser, you can also refer to fields and values of earlier messages of the context by adding the @<distance-of-referenced-message-from-the-current> suffix to the macro. For example, if there are three log messages in a context, the ${HOST}@1 expression refers to the host field of the current (third) message in the context, the ${HOST}@2 expression refers to the host field of the previous (second) message in the context, ${PID}@3 to the PID of the first message, and so on. For example, the following message can be created from SSH login/logout messages: An SSH session for ${SSH_USERNAME}@1 from ${SSH_CLIENT_ADDRESS}@2 closed. Session lasted from ${DATE}@2 to ${DATE}.

aggregate(
    value('value name="MESSAGE" An SSH session for ${SSH_USERNAME}@1 from ${SSH_CLIENT_ADDRESS}@2 closed. Session lasted from ${DATE}@2 to ${DATE}')
)

If you do not know in which message of the context contains the information you need, you can use the grep template function. For details, see grep.

$(grep ("${username}" == "root") ${auth_method})

To perform calculations on fields that have numerical values, see Numerical operations.