'\" t .\" Title: traffic_learner .\" Author: [see the "AUTHOR" section] .\" Generator: DocBook XSL Stylesheets vsnapshot .\" Date: 05/09/2024 .\" Manual: User Commands .\" Source: Samba 4.20.1 .\" Language: English .\" .TH "TRAFFIC_LEARNER" "7" "05/09/2024" "Samba 4\&.20\&.1" "User Commands" .\" ----------------------------------------------------------------- .\" * Define some portability stuff .\" ----------------------------------------------------------------- .\" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .\" http://bugs.debian.org/507673 .\" http://lists.gnu.org/archive/html/groff/2009-02/msg00013.html .\" ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .ie \n(.g .ds Aq \(aq .el .ds Aq ' .\" ----------------------------------------------------------------- .\" * set default formatting .\" ----------------------------------------------------------------- .\" disable hyphenation .nh .\" disable justification (adjust text to left margin only) .ad l .\" ----------------------------------------------------------------- .\" * MAIN CONTENT STARTS HERE * .\" ----------------------------------------------------------------- .SH "NAME" traffic_learner \- Samba tool to assist with traffic generation\&. .SH "SYNOPSIS" .HP \w'\ 'u traffic_learner {\-o\ OUTPUT_FILE\ \&.\&.\&.} [\-h] [\-\-dns\-mode\ {inline|count}] [SUMMARY_FILE] [SUMMARY_FILE\ \&.\&.\&.] .SH "DESCRIPTION" .PP This tool is part of the \fBsamba\fR(7) suite\&. .PP This tool assists with generation of Samba traffic\&. It takes a traffic\-summary file (produced by traffic_summary\&.pl) as input and produces a traffic\-model file that can be used by traffic_replay for traffic generation\&. .PP The model file summarizes the types of traffic (\*(Aqconversations\*(Aq between a host and a Samba DC) that occur on a network\&. The model file describes the traffic in a way that allows it to be scaled so that either more (or fewer) packets get sent, and the packets can be sent at a faster (or slower) rate than that seen in the network\&. .SH "OPTIONS" .PP \-h|\-\-help .RS 4 Print a summary of command line options\&. .RE .PP SUMMARY_FILE .RS 4 File containing a network traffic\-summary\&. The traffic\-summary file should be generated by traffic_summary\&.pl from a packet capture of actual network traffic\&. More than one file can be specified, in which case the traffic will be combined into a single traffic\-model\&. If no SUMMARY_FILE is specified, this tool will read the traffic\-summary from STDIN, i\&.e\&. you can pipe the output from traffic_summary\&.pl directly to this tool\&. .RE .PP \-o|\-\-out OUTPUT_FILE .RS 4 The traffic\-model that is produced will be written to this file\&. The OUTPUT_FILE can then be passed to traffic_replay to generate (and manipulate) Samba network traffic\&. .RE .PP \-\-dns\-mode [inline|count] .RS 4 How DNS traffic should be handled by the model\&. .RE .SH "EXAMPLES" .PP To take a traffic\-summary file and produce a traffic\-model file, use: .PP traffic_learner traffic\-summary\&.txt \-o traffic\-model\&.txt .PP To generate a traffic\-model from a packet capture, you can pipe the traffic summary to STDIN using: .PP tshark \-r capture\&.pcapng \-T pdml | traffic_summary\&.pl | traffic_learner \-o traffic\-model\&.txt .SH "OUTPUT FILE FORMAT" .PP The output model file describes a Markov model estimating the probability of a packet occurring given the last two packets\&. .PP The count of each continuation after a pair of successive packets is stored, and the ratios of these counts is used to calculate probabilities for the next packet\&. .PP The model is stored in JSON format, and also contains information about the packet rate and DNS traffic rate\&. .SS "Example ngram listing" .PP The following listing shows a contrived example of a single ngram entry\&. .sp .if n \{\ .RS 4 .\} .nf "ngrams": { "ldap:0\etdcerpc:11": { "lsarpc:77": 1, "ldap:2": 370, "ldap:3": 62, "wait:3": 2, "\-": 1 }, [\&.\&.\&.] } .fi .if n \{\ .RE .\} .PP This counts the observed continuations after an ldap packet with opcode 0 (a bind) followed by a dcerpc packet with opcode 11 (also a bind)\&. The most common next packet is "ldap:2" which is an unbind, so this is the most likely packet type to be selected in replay\&. At the other extreme, lsarpc opcode 77 (lookup names) has been seen only once, and it is unlikely but possible that this will be selected in replay\&. .PP There are two special packet types here\&. "wait:3" refers to a temporary pause in the conversation, where the "3" pseudo\-opcode indicates the length of the wait on an exponential scale\&. That is, a "wait:4" pause would be about 2\&.7 times longer that a "wait:3", which in turn would be similarly longer than a "wait:2"\&. .PP The other special packet is "\-", which represents the limit of the conversation\&. In the example, this indicates that one observed conversation ended after this particular ngram\&. This special opcode is also used at the beginning of conversations, which are indicated by the ngram "\-\et\-"\&. .SH "VERSION" .PP This man page is complete for version 4\&.20\&.1 of the Samba suite\&. .SH "SEE ALSO" .PP \fBtraffic_replay\fR(7)\&. .SH "AUTHOR" .PP The original Samba software and related utilities were created by Andrew Tridgell\&. Samba is now developed by the Samba Team as an Open Source project similar to the way the Linux kernel is developed\&. .PP The traffic_learner tool was developed by the Samba team at Catalyst IT Ltd\&. .PP The traffic_learner manpage was written by Tim Beale\&.