Giter Club home page Giter Club logo

ws_dissector_helper's Introduction

ws_dissector_helper

Helper for creating a Wireshark Dissector in Lua. For text protocols only.

Basic features

  • Messages specifications in CSV format.
  • Fixed length fields.
  • Variable Length fields.
  • Composite fields.
  • Repeating Group fields.
  • Default preferences.
  • Message header/trailer.
  • All fields can be used in Wireshark's display filters.
  • Simple and flexible. Simple, because you could make small changes to the example protocol and create your own. Flexible, because you can override pretty much all functionality or add your own.

Field types

Type ProtoField mapping Description Remarks
STRING ftypes.STRING A fixed length string This is the default type. Fields with no specified type will become STRING.
NUMERIC ftypes.FLOAT A fixed length number Floating point number.
FIXED ftypes.STRING A string with fixed value This is useful for fields that have a fixed value and should be validated.
VARLEN ftypes.STRING A string of variable length The length of the field is specified by another field in the message.
COMPOSITE A field containing other fields Composite fields are visualized with a subtree in the Packet Details pane. This type cannot be specified in a CSV file. Use the Field.COMPOSITE function instead to create one dynamically. Useful for header/trailer fields. Note that only fixed length fields are allowed inside a composite.
REPEATING A repeating group These are composite fields that are repeated. The number of repeats is taken by another field. The end of the repeating group is either the last field or a field of type REPEATING-END.
REPEATING-END The end of a repeating group Marks the end of a repeating group.
OPTIONAL ftypes.STRING An optional fixed length string Only valid as the last field of a message or the last field before the message trailer. Not recommended for TCP segments with multiple messages.

Dissector preferences

Use the setDefaultPreference of the helper object with the values you want. The default preferences are:

Name Type Description Remarks
ports Pref.range The TCP ports to register For example "7001-70010,8005,8100"
trace Pref.bool Enables tracing Useful for debugging your dissector. You can also use the trace function of the helper object in your lua script instead of using print or debug.

These preferences can be changed from the Protocols section of Wireshark's Preferences dialog.

Getting started

Create a lua script for our new dissector. Let's name it sop.lua since the dissector we will create will be for the SOP protocol (an imaginary protocol used in this example).

Add the following lines at the end of Wireshark's init.lua script:

WSDH_SCRIPT_PATH='path to the directory src of the repo'
SOP_SPECS_PATH='path to the directory of the CSV specs'
dofile('path to sop.lua')

Then in the sop.lua file:

Create a Proto object for your dissector. The Proto class is part of Wireshark's Lua API.

sop = Proto('SOP', 'Simple Order Protocol')

Load the ws_dissector_helper script. We will use the wsdh object to access various helper functions.

local wsdh = dofile(WSDH_SCRIPT_PATH .. 'ws_dissector_helper.lua')

Create the proto helper. Note that we pass the Proto object to the createProtoHelper factory function.

local helper = wsdh.createProtoHelper(sop)

Create a table with the values for the default settings. The values can be changed from the Protocols section of Wireshark's Preferences dialog.

local defaultSettings = {
	ports = '9001-9010',
	trace = true
}
helper:setDefaultPreference(defaultSettings)

Define the protocol's message types. Each message type has a name and file property. The file property is the filename of the CSV file that contains the specification of the fields for the message type. Note that the CSV files should be located in SOP_SPECS_PATH.

local msg_types = { { name = 'NO', file = 'NO.csv' },
				    { name = 'OC', file = 'OC.csv' },
					{ name = 'TR', file = 'TR.csv' },
					{ name = 'RJ', file = 'RJ.csv' } }

Define fields for the header and trailer. If your CSV files contain all the message fields then there is no need to manually create fields for the header and trailer. In our example, the CSV files contain the specification of the payload of the message.

local SopFields = {
	SOH = wsdh.Field.FIXED(1,'sop.header.SOH', 'SOH', '\x01','Start of Header'),
	LEN = wsdh.Field.NUMERIC(3,'sop.header.LEN', 'LEN','Length of the payload (i.e. no header/trailer)'),
	ETX = wsdh.Field.FIXED(1, 'sop.trailer.ETX', 'ETX', '\x03','End of Message')
}

Then define the Header and Trailer objects. Note that these objects are actually composite fields.

local header = wsdh.Field.COMPOSITE{
	title = 'Header',
	SopFields.SOH,
	SopFields.LEN
}

local trailer = wsdh.Field.COMPOSITE{
	title = 'Trailer',
	SopFields.ETX
}

Now let's load the specs using the loadSpecs function of the helper object. The parameters of this function are:

  1. msgTypes this is a table of message types. Each type has two properties: name and file.
  2. dir the directory were the CSV files are located
  3. columns is a table with the mapping of columns:
    • name is the name of the field name column.
    • length is the name of the field legth column.
    • type is the name of the field type column. Optional. Defaults to STRING.
    • desc is the name of the field description column. Optional.
  4. offset the starting value for the offset column. Optional. Defaults to 0.
  5. sep the separator used in the csv file. Optional. Defaults to ','.
  6. header a composite or fixed length field to be added before the fields found in spec.
  7. trailer a composite or fixed length field to be added after the fields found in spec.

The function returns two tables. One containing the message specs and another containing parsers for the message specs. Each message spec has an id, a description and all the fields created from the CSV in a similar fashion to the one we used previously to create SopFields. Each message parser is specialized for a specific message type and they include the boilerplate code needed to handle the parsing of a message.

-- Column mapping. As described above.
local columns = { name = 'Field',
				  length = 'Length',
				  type = 'Type',
				  desc = 'Description' }

local msg_specs, msg_parsers = helper:loadSpecs(msg_types,
											    SOP_SPECS_PATH,
											    columns,
											    header:len(),
											    ',',
											    header,
											    trailer)

Now let's create a few helper functions that will simplify the main parse function.

-- Returns the length of the message from the end of header up to the start
-- of trailer.
local function getMsgDataLen(msgBuffer)
	return helper:getHeaderValue(msgBuffer, SopFields.LEN)
end

-- Returns the length of whole the message. Includes header and trailer.
local function getMsgLen(msgBuffer)
	return header:len() +
		   getMsgDataLen(msgBuffer) +
		   trailer:len()
end

One of the last steps and definatelly the most complicated is to create the function that validates a message, parses the message using one of the automatically generated message parsers and finally populates the tree in the Packet Details pane.

local function parseMessage(buffer, pinfo, tree)
	-- The minimum buffer length in that can be used to identify a message
	-- must include the header and the MessageType.
	local msgTypeLen = 2
	local minBufferLen = header:len() + msgTypeLen
	-- Messages start with SOH.

	if SopFields.SOH:value(buffer) ~= SopFields.SOH.fixedValue then
		helper:trace('Frame: ' .. pinfo.number .. ' No SOH.')
		return 0
	end

	-- Return missing message length in the case when the header is split
	-- between packets.
	if buffer:len() <= minBufferLen then
		return -DESEGMENT_ONE_MORE_SEGMENT
	end

	-- Look for valid message types.
	local msgType = buffer(header:len(), msgTypeLen):string()
	local msgSpec = msg_specs[msgType]
	if not msgSpec then
		helper:trace('Frame: ' .. pinfo.number ..
					 ' Unknown message type: ' .. msgType)
		return 0
	end

	-- Return missing message length in the case when the data is split
	-- between packets.
	local msgLen = getMsgLen(buffer)
	local msgDataLen = getMsgDataLen(buffer)
	if buffer:len() < msgLen then
		helper:trace('Frame: ' .. pinfo.number ..
					 ' buffer:len < msgLen')
		return -DESEGMENT_ONE_MORE_SEGMENT
	end

	local msgParse = msg_parsers[msgType]
	-- If no parser is found for this type of message, reject the whole
	-- packet.
	if not msgParse then
		helper:trace('Frame: ' .. pinfo.number ..
					 ' Not supported message type: ' .. msgType)
		return 0
	end

	local bytesConsumed, subtree = msgParse(buffer, pinfo, tree, 0)
	if bytesConsumed ~= 0 then
	    subtree:append_text(', Type: ' .. msgType)
	    subtree:append_text(', Len: ' .. msgLen)

	    pinfo.cols.protocol = sop.name
	else
		protoHelper:trace('Frame: ' .. pinfo.number .. ' Parsing did not complete.')
	end

	return bytesConsumed
end

Now that the parse function for the SOP protocol is ready, we need to create the dissector function using the getDissector helper function which returns a dissector function containing the basic while loop that pretty much all dissectors need to have.

sop.dissector = helper:getDissector(parseMessage)

Finally enable the dissector. enableDissector registers the ports to the TCP dissector table.

helper:enableDissector()

An example

A detailed example can be found here.

Installation

Add the following lines at the end of Wireshark's init.lua script:

WSDH_SCRIPT_PATH='path to the directory src of the repo'
SOP_SPECS_PATH='path to the directory of the CSV specs'
dofile('path to your dissector file')

Testing

At this point testing is manual. For an example have a look here.

Known bugs

On captures with many missing packages and many retransmissions the following errors can be found in the Expert Information dialog.

Lua Error: ws_dissector_helper.lua:98: Range is out of bounds Lua Error: ws_dissector_helper.lua:154: bad argument #3 to 'tvb' (number expected, got string)

Acknowledgments

Special thanks to the following people:

  • FlavioJS and the Athena Dev Teams, for the Athena dissector which was the starting point of this project.
  • Geoff Leyland, for his lua-csv.

ws_dissector_helper's People

Contributors

prontog avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.