About Adam

Maltego/Python Addict

Maltego: Enhance your….entity

So over the weekend I started off my series on how you can create your own Maltego transforms, quickly and without much effort. Today I wanted to expand on that and look at how we can expand on the original ‘GetRobots’ transform to make use of some of the additional properties within an entity.

If you remember our GetRobots transform made use of two builtin Maltego entities. The starting entity (the one you run the transform on) was the Website entity. The Website entity has two additional properties that can be set.

These are:

  • Ports
  • SSL Enabled

Screen Shot 2014-09-21 at 09.04.00

By default these are set to Port 80 and SSL isn’t enabled. The ‘Ports’ property allows you to enter an array of different ports that your target website might be running on, the ‘SSL Enabled’  is essentially a True or False option. In order to make use of these values (or allow for them to be changed) we need to change our original transform slightly.

NOTE: The python code is this transform might not be pretty but its more to show you how to call the additional properties rather than impress you with my Python skills.

OK, so in the GitHub repo (found HERE), you will see I’ve created a new file called GetRobots-mk2.py this is the same base code as the original transform but with some tweaks. So lets go through them;

from MaltegoTransform import *
import requests

m = MaltegoTransform()

So first off we removed the 'website = sys.argv[1]' line and replaced it with 'm.parseArguments(sys.argv)'. This is essentially telling the transform to make use of all the entity properties (regardless of how they are set). We now need to call these properties and store them in variables so we can use them.

website = m.getVar('fqdn')
port = m.getVar('ports')
port = port.split(',')
ssl = m.getVar('website.ssl-enabled')
robots = []

Now you may be wondering where I got the value names from, there are two places you can look. The first is this PDF from Paterva which explains the core entities and the values available which you can find HERE.

The second is from within Maltego (this is the way I tend to do it), click on Manage – Manage Entities scroll down to the Website entity, click on the three little blue dots on the right, then click on the ‘Additional Properties’ tab on the top.

On the left you will see a list of properties, if you select one the top right window will change to show you the details for that property. The ‘Name’  value is the important value and when you are pulling out these properties in your transforms it’s the one that will case you headaches (well it does me anyway).

Screen Shot 2014-09-22 at 20.59.29

So back to the code. We use the ‘getVar’  and the associated entity name (for that property) to store the values in a variable. The ‘ports’  properties is stored as a list so we can iterate over it later, the ‘ssl-enabled’  is a boolean so will return either True or False.

The rest of the code is tweaked slightly to make use of these new variables, which you can see below.

for c in port:
if ssl == 'true':
url = 'https://' + website + ':' + str(c) + '/robots.txt'
r = requests.get(url)
if r.status_code == 200:
robots = str(r.text).split('\n')
for i in robots:
ent = m.addEntity('maltego.Phrase', i)
ent.addAdditionalFields("url","Original URL",True,url)
m.addUIMessage("No Robots.txt found..")
url = 'http://' + website + ':' + str(c) + '/robots.txt'
r = requests.get(url)
if r.status_code == 200:
robots = str(r.text).split('\n')
for i in robots:
ent = m.addEntity('maltego.Phrase', i)
ent.addAdditionalFields("url","Original URL",True,url)
m.addUIMessage("No Robots.txt found..")
except Exception as e:

We’ve added two extra components, first we create a ‘for’ loop and iterate through each value stored in ‘ports’. This allows our transform to cater for multiple (or single) ports. We then throw in some ‘if’  logic to see if the ‘ssl-enabled’  property is set. If it is we change the url to be ‘https’ and chuck in the port number for good measure. Like I said, it’s not pretty but it works.. 🙂

The final addition piece to the puzzle is we have declared some additional properties in the ‘Phrase’  which if you check yourself will see don’t exist. The ‘Phrase’  entity has only one value, but Maltego allows you to create dynamic values which you can then use later on in other transforms. To do this, we changed the way we create the entity, in order to use some of the more ‘advanced’ features of ‘addEntity’ we created a variable called ‘ent’  which then allows use to add additional properties among other things.

ent = m.addEntity('maltego.Phrase', i)
ent.addAdditionalFields("url","Original URL",True,url)

The ‘addAdditionalFields’ function has these options (taken from Paterva’s documentation).

Set additional fields for the entity
fieldName: Name used on the code side, eg displayName may be “Age of Person”, but the app and your transform will see it as the fieldName variable
displayName: display name of the field shown within the entity properties
matchingRule: either “strict” for strict matching on this specific field or false
value: The additional fields value

If you install the new transform following the previous posts instructions and run it you will see that the new additional property is created as a ‘Dynamic Property’.

Screen Shot 2014-09-22 at 21.26.12

Screen Shot 2014-09-22 at 21.33.21

If you were to then write a new transform for our new ‘Phrase’ entity you would call the dynamic property using.

ent.addAdditionalFields("url","Original URL",True,url)
url = m.getVar('url')

Hope that all makes sense?? Next time we are going to look at Maltego Machines

Maltego: My First Transform

On Friday I posted a challenge on twitter called “Transform Friday”, you suggest a Maltego transform and I would have a go at writing it. There is no real reason behind the challenge other than I like writing Maltego transform and its a nice way to write something different to the normal packet related ones I do. My plan was to write them without using Canari (native Maltego transforms) and make them all available as TDS transforms (no installation required).

Screen Shot 2014-09-21 at 08.41.28

The first challenger soon steeped up and much to my surprise it was Paterva (yes thats right the people that make Maltego).

Screen Shot 2014-09-21 at 08.41.44

However it was then suggested to me that it would be quite cool if I wrote up how you (yes you) could create your own Maltego transforms. Now this is where I need to apologise, I’ve spent the last two years telling you all about the awesome (well I think they are awesome) Maltego transforms I’ve created but I’ve never told you how. Part of the reason behind this blog was to share information and try in some way to save you the pain I’ve suffered, that’s why I wrote the Scapy guide after all.

So this will be the first in a series of blog posts about creating Maltego transforms. Today we are going to cover some of the basics and write a nice and simple transform (that’s useful at the same time), and then over the coming weeks we will cover more advanced topics, like setting additional properties, changing link colour and finally creating TDS transforms.

There is a GitHub repo available with the code snippets in so you can follow along or just download the completed ones (link available towards the bottom).

The transforms will be written in Python (as that’s the only one I can do) but Paterva do cater for a range of languages to be used as well as having some documentation available. Links for all the resources will be available at the bottom of this post and in the GitHub repo. I should at this point say the documentation for developing with Maltego is actually pretty good and this is not supposed to be a replacement, but more a compliment to what the guys at Paterva already provide.

For the purpose of these blog posts, I’m going to assume that you know what Maltego is and how to use it (even the basics is fine). So before we start writing the transform we are going to talk a little about the two key Maltego things you need for a transform.

Entities & Transforms


These the building blocks of a Maltego graph, they are both the start and the finish of a transform. The type of entity (e.g. Website) defines what transforms can be run against, once a transform has run then you typically get a different entity type as a result (and the cycle repeats).

For your first transform we are going to use two entities.

  • Website
  • Phrase

The website entity by defaults contains ‘www.paterva.com’ as the default value. You can change this to the website of your choice and you have the option of marking whether the website is “SSL Enabled” or not and the ports it’s listening on.

Screen Shot 2014-09-21 at 09.04.00

The Phrase entity is really simple, it literally a piece of text. It has no additional properties available.

Screen Shot 2014-09-21 at 09.13.28


Transforms are where the magic on Maltego occurs, they take your starting entity (in our case website) run some magic (well code) and return the results as another entity.

There are two types of transforms,

  • Local
  • Remote

Local transforms are ones that you have to install locally on your machine. All the components required to run that transform have to be installed on your machine (Python libraries for example). One of the benefits of using local transforms is that it widens your scope for what you can do (I’ll explain that later), but it does limit the portability of those transforms (to a degree) as each person would need to install them (and the dependencies) before they can use them. There are a couple of ways to ease that pain but it’s still a manual process.

Remote transforms run on TDS servers, the code for TDS transforms are executed on the TDS server so you remove yourself from having to worry about dependencies and libraries. The main benefit of TDS transforms is that they are truely portable, however they are limited to what you can do with them (well to my knowledge). For example if you have a custom transform that wants to read a file on your machine (or a local server) there isn’t an easy way to execute that transform as TDS transform because the remote TDS server won’t have access to that file. You would have to somehow get that file to a location that the TDS server could access it.

Your First Transform

So enough about the boring stuff lets get started. Your first transform is nice and simple we are going to use a Website entity and then write a transform to check for the robots.txt file, open it and then return each entry as a Phrase entity.

So the first thing you need is the Maltego Python library which can be found HERE:

Extract the MaltegoTransform.py to your working directory (where you are going to write the transform), for example mine is:


Now create a new file in that directory called GetRobots.py

touch GetRobots.py

Using your editor of choice lets open the file and start coding (I use Sublime Text 3).

First off lets add the Python sheebang and a comment about what this code is for.

#!/usr/bin/env python

# Maltego transform for getting the robots.txt file from websites

Now we need to import the Maltego transform library and the other Python libraries we need.

from MaltegoTransform import *
import sys
import os
import requests

We will be using the ‘requests’  library to make the call to the website to retrieve the robots.txt file. We need the ‘sys’  library as the sys.argv command is used to pass the value of the starting Maltego entity to the transform. So in our case the value of website (e.g. http://www.paterva.com) will be sent to our transform as sys.argv[1].

Our next job is to create a variable to store that entity value in and something to store the output in.

website = sys.argv[1]
robots = []

Now we are going to initialise the Maltego library so we can use it later on.

m = MaltegoTransform()

Still with me??

Ok lets write the code for using ‘requests’ to go and retrieve the robots.txt file (if it exists).

r = requests.get('http://' + website + '/robots.txt')
if r.status_code == 200:
robots = str(r.text).split('\n')
for i in robots:
m.addEntity('maltego.Phrase', i)
m.addUIMessage("No Robots.txt found..")
except Exception as e:


Now this isn’t as bad as it looks (promise). Firstly we put everything in a ‘try/except’  bubble so that we have some error handling.

Next we make the initial GET request.

r = requests.get('http://' + website + '/robots.txt')

This adds the value we set on the Website entity and passes into the ‘request.get’  call with the ‘robots.txt’ added on the end.

We then add some logic in place to see if the robots.txt exists or not.

if r.status_code == 200:
robots = str(r.text).split('\n')
for i in robots:
m.addEntity('maltego.Phrase', i)
m.addUIMessage("No Robots.txt found..")

If the status code is 200 (that’s a HTTP OK response), we store the output in the list variable ‘robots’ as text (instead of unicode) and then split into separate list entries based on each new line.

We then iterate through the list and for each line we create a new Maltego entity.

m.addEntity('maltego.Phrase', i)

This is where the magic happens. We initialise the Maltego Transform library earlier as ‘m’, we then use the function ‘addEntity’  to create an entity and set is as ‘maltego.Phrase’. We can then pass ‘i’ (which is from our for loop) as the value to write to that entity.

There are two other statements that use part of the Maltego Transform library in our code.

m.addUIMessage("No Robots.txt found..")
except Exception as e:

The ‘addUIMessage’  function allows you to pass text back to the Maltego GUI when the transform is run (or running), it’s ideal for error handling messages which is how we used it here. The ‘else’  statement is if the status.code isn’t 200 (which is usually a bad thing) and would return the message to the Maltego GUI and the ‘except’  statement will return any other error message that occurs (such as the website not being available etc.).

We finish the whole thing off my then calling the Maltego Transform library and telling it to return the output from our transform back into the GUI.


Before we install this transform into Maltego we can actually check to make sure it works as expected. From your working directory simply run:

python GetRobots.py www[dot]paterva[dot]com

If it’s all worked you should see something like this.

Screen Shot 2014-09-21 at 11.14.50

What you might not have realised is that Maltego uses XML a lot of it’s transforms and entities, the Maltego Transform library will automatically wrap your output up in the correct format so that displays properly within Maltego (after all who likes messing with XML).

Now that we have working code, we can add it into Maltego as our own transform. This is acutally really easy. Within the Maltego GUI, click

Manage – Local Transforms

You should get a popup window like the one below.

Screen Shot 2014-09-21 at 10.33.54

On this first screen you need to enter some details about your transform.

Display name – This is how your transform appears in Maltego
Description – A brief description about what your transform does
Transform ID – A unique reference that Maltego uses (you can’t change it once you’ve created it)
Author – That’s you..
Input entity type – We need to choose ‘Website’, this means that our entity will only run on Website entities (which is good for us)
Transform set – Transform sets are a collection of transforms that relate to an entity type. I’ve chosen ‘none’ just for this example. You can create your own transform sets which we will cover in later posts

Screen Shot 2014-09-21 at 10.34.53

Click Next….

Screen Shot 2014-09-21 at 10.38.51

This is where we set the meat of the transform, as in actually point it to your code.

Command – This is the path to your interpretor so in my case ‘/usr/bin/python’ (I’m using a Mac though)
Parameters – This is where you point it to your actual GetRobots.py file
Working Directory – Set this to your working directory.

Screen Shot 2014-09-21 at 10.40.48

Click Finish….

So you’ve now added your transform into Maltego.. shall we run it??

Drag a website entity onto an empty graph in Maltego. Leave the default http://www.paterva.com address in there for now. Right click on the entity, then select

Run Transform – Other Transforms – GetRobots

Screen Shot 2014-09-21 at 10.45.44

All being well you should get a number of Phrase entities returned containing the same output as when you run your script manually??? (fingers crossed)

Screen Shot 2014-09-21 at 10.48.00

Add some other websites and see what you get back. If like me you are only using the Community Edition of Maltego then don’t be worried if you only get 12 entities returned.

Congratulations you’ve just created your first Maltego Transform.. it wasn’t that hard now was it, so what you waiting for?? 🙂

In the next post in this series we will explore some more of the features available when returning entites and look at how to use additional properties on an entity when running a transform and how to return additional properties once a transform is complete.

Link to GitHub repo:


Links to Maltego Developer documentation:

http://www.paterva.com/web6/documentation/developer.php – Main Developer Site

http://www.paterva.com/web6/documentation/developer-local.php? – Local Transforms
http://www.paterva.com/web6/documentation/localTransforms-SpecIII.pdf – Local Transform Specifications
http://www.paterva.com/web6/documentation/MaltegoTransform-Python.zip – Python Library

sniffmypackets v2 – Sneak Peak

So this week I started the long awaited (well on my part) rewrite of sniffmypackets. My initial release was more a voyage of discovery rather than a well thought out application but it did teach me a lot about how to write transforms for Maltego (using Canari Framework) so I felt it was best to start from scratch and just reuse chunks of code where it made sense.

I’ve also decided to add more functionality that will make using SmP (sniffmypackets) more than just a Maltego based exercise. There are 3 key features I will be adding.

  1. Database Support
  2. Web Interface
  3. Netflow support

The decision to use a database (MongoDB at the moment) was to allow for the database to exist after Maltego is closed. Every pcap will have a unique Session ID which means that not only can you load a pcap into SmP you can (on a different machine and without the original pcap) then rebuild the contents of the pcap based on the Session ID.

The web interface will mean that other people (who may or may not have Maltego) can then view key information about a pcap or you can just use it as another source of reference.

Both the database and web interface will be able to run outside of the machine running Maltego (so you can centralise it) and I might even include Vagrant machines if you don’t have the capacity to do that.

It does mean that SmP will need a MongoDB backend to run but trust me it will be worth it.

After a conversation I had a few weeks ago with some very clever people I decided to add Netflow capabilities into SmP to give you even more bang for your buck (so to speak).

Below are some screenshots of what it looks like at the minute.

SmP - Overview

SmP - Session Import


HoneyMalt – Maltego for Honeypots

So in my normal fashion, the other week I came up for another Maltego/Canari project while still not having completed most of the other projects I’ve started. That being said I like to keep things interesting so today I give you HoneyMalt.

The love child of the Canari Framework, Maltego and Kippo (SSH Honeypot), HoneyMalt allows you to pull data out of your Kippo honeypot (as long as you are using MySQL) and display it in a graph. A bit like this one below.


Currently HoneyMalt allows you to display the following information:

“Evil” IP address
Geo IP lookup for country code
Session ID
Username/Password combinations
Input (the stuff they type in)
File download info

I’ve also managed to get the hang of Maltego Machines (finally) and all of these transforms run from one machine (who knew that path & paths would give me so much grief). The sneaky use of a Maltego machines and a database means, that if like me you don’t have a full version of Maltego (donations accepted) you can still get the all the entities returned instead of hitting the 15 entity limit on a transform run, it just takes a few iterations of the machine running.

There is a quick Youtube video of what that looks like below.

I’m also in the process of adding some search functions so you can find specific sessions based on IP address, or keyword or url. After that I will be moving onto more honeypots (Dionaea next) to add into HoneyMalt with the sole intent of trying to breaking your machine while Maltego tries to graph it all (only kidding).

With HoneyMalt I’ve also resisted the urge to create loads of new entities so where possible I’ve used the Maltego builtin ones so that you can make use of the existing transform sets which is good for you and means I have less to code (I’m not lazy honest..). Likewise I’ve also resisted the urge to use lots of Python modules so you only need 3 (currently) and 1 of those is Canari.

The GitHub repo has the install instructions and if you get any problems raise an Issue Ticket on the repo. Repo is HERE

Have fun!!!

Scapy: Heartbleed

So I might be a bit late to the game but I post this code on Twitter a while back but then forgot to blog about so here you go…

I’ve written a little snippet of Python code that uses Scapy to search through a pcap file looking for Heartbleed requests and responses. Due to Scapy not having a layer for TLS connections this have been done by slicing and dicing the RAW layer and pulling out the information we need. A lot of the time that I’m writing Scapy code to analyse pcap files I use Wireshark to look at the packets and match that up in Scapy.

This is the output from Wireshark;

Screen Shot 2014-07-25 at 07.24.03

And this is what Scapy sees;

Raw load='\x18\x03\x02\x00\x03\x01@\x00'

Currently the script just looks for traffic on port 443, but I will tweak it over the next week or two to handle any port.

I’ve removed the port restrictions so it should be protocol agnostic.. (hopefully)..

You can find the code HERE:

To run it, just type

./pcap-heartbleed.py [pcapfile]

So for example:

./pcap-heartbleed.py heartbleed.pcap

If it finds anything it thinks is a Heartbleed packet you get an output similar to the one below (I’ve changed the IP addresses):

Heartbleed Request: src: dst:
Heartbleed Response: src: dst:
Heartbleed Request: src: dst:
Heartbleed Response: src: dst:
Heartbleed Request: src: dst:
Heartbleed Response: src: dst:


Packet Addict: IPv4 Packets

So I’ve decided to finally getting around to revising (and then taking) my SANS 503 exam (or GCIA). It’s been a while since I’ve spent anytime looking at packets up close and personal so rather than me suffering alone I thought I would blog as I go (plus it’s a good way to remember stuff).

This is the first in a new series called “Packet Addict” (that’s me by the way).

Today we are going to have a look at IPv4 packets, what makes up a IP packet and how you can read these things in their “naked” version (or Hex if you want to be precise). I’m going to be honest you can find all of this on Google, so go ahead or just carry on reading.

DISCLAIMER: If I get something wrong, please tell me as I’m revising for an exam and you wouldn’t want to feel guilty if I fail because you didn’t tell me something was wrong.. now would YOU.

So lets just cover some key terms before we start.

Bit – Smallest unit of a packet, has the value of 0 or 1 (so either on or off).
Nibble – Made up of 4 bits and has is one hexadecimal value.
Byte – This is 8 bits, or 2 nibbles and is 2 hexadecimal values.

So to put some context (we all love context), a TCP flag (covered later but used here for reference) is made up of 1 bit which means it’s either on or off (set or unset).

An example of a nibble (4 bits) would be the IP version number (currently you either get 4 or 6 but you know).

A byte is something like the IP Time to Live (amount of hops before the packet dies a slow and painful death in the darkness that is the internet), working on the basis that it’s 2 hexadecimal values then the maximum it can be (or should be) is 255 (0xFF).

To convert hex to decimal in python you can use this snippet of code:

>>> print int("5", 16)

Hexadecimal is a base 16 numbering system, so the python code takes your value (5 in this case) and prints the int value based on it being base 16.

All make sense?? Awesome lets carry on.

So an IPv4 packet is a minimum of 20 bytes with a maximum of 60 bytes, most IPv4 packets are 20 bytes and I’ve not come across one that is larger than that but I’ve led a settled life.

So in order to work out from hex (that’s hexadecimal in big word speak) what a IPv4 header is really saying (without using Wireshark) you need one of these things below (not mine, found it on the internet)..


This is a graphical representation of an IPv4 header and it’s associated bits (and bytes), so now with the magic of a calculator and Google for when I get stuck, lets make some packet magic.

OK so here is the hex dump of a IPv4 header (taken from a random pcap file).

4500 003c 2d70 4000 4006 d7f6 0a14 9096 0a14 9097

So lets work through the first few bits together. Every IPv4 packet starts (typically) with 4500 which makes it a bit easier to spot when looking at lots of raw packets. So remembering that each hex character is a nibble (2 bits) and using the IPv4 Header image from above we can begin to break out the individual parts of the packet.

Version -> 4 bits (1 hex) = 4
IHL -> 4 bits (1 hex) = 5

Now this is the bit that confuses me, how does a 5 in hex equal 20 bytes?? (the standard length of an IPv4 header)… Google to the rescue..

Brain Meltdown:
The IHL (Internet Header Length) field is 4 bits long and specifies the header length in 32-bit word (4 bytes).

So there are two ways to do this, my way and the right way but mine is quicker. 4 bits for IHL, multiple that by your IHL value (5) and you get 20 bytes.

The correct way is to do it like this:

5 * 32 / 8 = 20 (bytes)

5 is the IHL value, multiple by 32 (32 bit word), divide by 8 (number of bits in a byte).

So confused yet?? I know I am (trying writing a blog about this stuff), but lets continue. Next we will break down each chunk of the packet and then we can convert it back to decimal (i.e. readable format) later. Using the table above and the raw packet I will map each value into the diagram below with the hex values.


So I’ve tried to match the colouring coding across the original IPv4 Header picture a bit further up. Lets work through each value, convert it to decimal and then we should be able to see it make a bit more sense.

IP Version = 4 – Makes sense it’s an IPv4 packet after all
IHL = 5 – So we know that we need to multiple this by 4 to get the number of bytes = 20 bytes
Type of Service = 00 – So this is a result of zero, not uncommon to see in IP headers
Total Length = 003c – If we convert this to decimal we get 60, which is the size of the packet in bytes
IP Identification Number = 2d70 – This converts to 11632, this value is usually used for identifing the group of fragments of a single IP datagram
Flags = 4 – These flags are used for determining if a packet is fragmented or not and each of the 3 flags is a bit value (either 1 or a 0). The flags are:
bit 0: Reserved, must be zero
bit 1: Don’t Fragment (DF)
bit 2: More Fragments (MF)
So if we look at this from a binary point of view (as we are dealing with bits), we would get 0 1 0 0 which is hexadecimal for 4 (Don’t Fragment). If it was a fragmented packet it would be binary of 0 0 1 0 which is hexadecimal of 2.
Fragment Offset = 000 – A value of zero means it’s either the first fragment, but in this case because the Don’t Fragment bit isn’t set then there is no need for an offset.
Time to Live = 40 – This converts back to 64 decimal which is a “standard” TTL for a packet
Protocol = 06 – This converts to 6 decimal which is the protocol number for a TCP packet (the next layer)
Header Checksum = d7f6 – These are used for error checking, this value converts to 55286
Source IP = 0a149096 – So we know that the maximum value for an IPv4 Address is 255, so each octet of the IP address will be 2 hex values seperated by a “.”, so
if we break each down in 2 hex value pairs we get 0a 14 90 96, which converts to
Destination IP = 0a149097 – Same principal as before, we turn this value into 0a 14 90 97 which in turns converts to

So there you go, a fully decoded IPv4 packet.. trust me it was as painful to write as it was for you to read.. 🙂

More information about the protocol numbers can be found here:


and if you want to see more details about the IPv4 structure you can read this:


Gobbler: Eating its way through your pcap files…

So a while back I blogged about the future of sniffMyPackets and how I was looking at building components for it that would make better use of existing systems you may be using (not over tooling things). Gobbler is the first step of that journey and is now available for your amusement..

Gobbler can be found HERE:

Essentially you feed Gobbler a pcap file and tell it how you want the data outputted. The current supported outputs are:

  1. Splunk (via TCP)
  2. Splunk (via UDP)
  3. JSON (just prints to screen at the moment).

The tool is based on Scapy (as always) and once the initial file read is done it’s actually quite quick (well I think it is).

Moving forward I am going to add dumping into databases (mongodb to start with) and Elastic search. On top of this I’m going to start writing protocol parsers for Scapy that aren’t “available”. I’ve found an HTTP one written by @steevebarbeau that is included in Gobbler so you can now get better Scapy/HTTP dumps.

To use with Splunk is easy, first in your Splunk web console create a new TCP or UDP listener (see screenshots below).



NOTE: UDP Listeners are better for any pcap with over 10,000 packets. I’ve had issues with TCP listeners past that point.

Once your Splunk Listener is ready, just “tweak” the gobbler.conf file to meet your needs:

server = ‘localhost’
port = 10000
protocol = ‘udp’

If you created a TCP listener, change the protocol to ‘tcp’ and gobbler will work out the rest for you.

To run gobbler is easy (as it should be), from the gobbler directory run this command:

./gobbler.py -p [pcapfile] -u [upload type]

I’ve included a 1 packet pcap in the repo so you can straight away test using:

./gobbler.py -p pcaps/test.pcap -u splunk

or if you want to see the results straight away try the json option:

./gobbler.py - pcaps/test.pcap -u json

If you load the packets into Splunk, then they will look something like this:


This means if you were to search Splunk for any packet from a Source IP (of your choice) you can just use (test_index is where I am storing them):

index="test_index" "ip_src="

This means you can then use the built-in GeoIP lookup to find out the City etc using this Splunk Search:

index="test_index" | iplocation ip_src

Which would give you back the additional fields so you can do stuff like this:


The benefit of using Gobbler is that I’ve done all the hard work on the formatting, I was going to write a Splunk app but the people at Splunk have been ignoring me so…

I’ve successfully managed to import about 40,000 packets via a UDP listening in just a few minutes, it’s not lightning quick but it’s a start.


PS. A “rebranding” of my core projects will be underway soon so stay tuned for more updates.. 🙂

sniffmypackets – The Future..

So about a year ago I started work on “sniffMyPackets”, the Maltego transform set (using Canari Framework) for analysing pcap files. I started it for 3 reasons;

  1. I’m obsessed with pcap files (I admit it, I’m an addict)
  2. I wanted to start writing Python code
  3. It sounded like fun

At the end of last year I hit a wall, 68 transforms in with what I think is a pretty cool “flow” to it and I ran out of ideas, direction, steam, whatever you want to call it. So I haven’t really done much with it since.

Then over the last few months, with the Scapy workshop at BSides and a mental kick up the ass I decided that I should give it some love (virtual of cause). The next question was “OK so how do I make it better??”, I had an idea, I thought it was awesome that was going to be the next big release for SmP (sniffMyPackets), but as the weeks have gone on I’m starting to wonder if I”m looking at this wrong. What benefit would this give the people that use it??

Let me try and explain… (bear with me)

People write tools to help other people, to enable them to do the same task over and over again with little effort and to ensure the results are predictable (within a small margin of error). So I had written a tool (SmP), within another tool (Maltego), using another tool (Canari Framework) to enable me to do that. To be honest when you write it down like that it seems a little crazy. In order to use my tool you need another 2 in place already!!

One of the things that bugs me at work, is when people say “Sorry can’t do that, I need this tool and it costs $$$$”, honestly the amount of times I want to kick them in the nuts and say “Open your eyes, we have loads of tools already, just make the most of them”. The reality is that in IT (especially Operations), we like off the shelf tools, because we’re not developers, we don’t code, we just use the same tools as everyone else does.

So why do I tell you this?? Well so my “awesome” idea for SmP was to start integrating pcaps into a database, with a web front end and then rewrite the Maltego transforms to suck out data from the database. I honestly thought that would be cool. Then while researching I discovered there are lots of “tools” out there already. Things like Splunk, LogStash, ElasticSearch, MongoDB (for databases), so why I am retooling something just for the sake of it (other than learning how to do it)??

So from now on I’m going to write tools that let you integrate into existing toolsets, I want you to use my code to get more out of what you already have rather than forcing you to get another toolset to manage and support. You want pcap files in Splunk??? Right I’m going to write you a App for that, you want to use ElasticSearch?? Awesome I’ll do that as well. You want pcap files in json? Easy..

The existing Maltego set for SmP will stay (as I have at least 1 user) but I will rewrite them to plug into existing toolset and suck the same data out, that way you don’t need more tools, you can just get more of the ones you’ve already committed to.

Stay tuned…

PS sorry for any spelling/grammar issues, I’m not wearing my glasses..

Scapy – Iterating over DNS Responses

So while doing my Scapy Workshop at BSides London the other week, I stated that iterating over DNS response records with Scapy is a bit of a ball ache. Well I will be honest, I was kind of wrong. It’s not that difficult it’s just not that pretty.

This is an example of a DNS response (Answer) packet when running a dig against http://www.google.com

Screen Shot 2014-05-12 at 08.14.07

You will see that there are 5 DNSRR layers in the packet, now when you ask Scapy to return the rdata for those layers you will only get the first one (in the Scapy code below pkts[1] refers to the second packet in the pcap which is the response packet).


In order to get the rest, you need to iterate over the additional layers.


In the example above the [5] and [6] are the layer “numbers” so to make that a bit easier to understand.

pkts[1][0] = Ether
pkts[1][1] = IP
pkts[1][2] = UDP
pkts[1][3] = DNS
pkts[1][4] = DNSQR
pkts[1][5-9] = DNSRR

So the code below is a quick way to iterate over the DNS responses by using the ancount field to determine the number of responses and then working backwards through the layers to show all the values.

#!/usr/bin/env python

from scapy.all import *

pcap = ‘dns.pcap’
pkts = rdpcap(pcap)

for p in pkts:
if p.haslayer(DNSRR):
a_count = p[DNS].ancount
i = a_count + 4
while i > 4:
print p[0][i].rdata, p[0][i].rrname
i -= 1

So there you go, quick and dirty Scapy/Python code.


BSides London 2014 – Scapy Workshop

So this week (Tuesday) was the 4th annual BSides London event held at the Kensington and Chelsea Town Hall (same venue as last year). For the last 3 years I’ve attended the event as not only a participant but also as a crew member, helping make the event awesome (which it is every year) and making it a tradition not to see ANY of the talks.. For me BSides is more about taking part and just meeting loads of cool people rather than going to all the talks and snagging all the free stuff, well ok apart from the MWR t-shirts but they are awesome.

This year however was slightly different, a new twist on an already awesome day. Leading up to the event I was busy helping (I use the word loosely) keep the website up-to-date (oh how I hate HTML) and generally just counting down the days.

This year I had planned on attending one workshop on a subject very close to my heart.. Scapy, which was due to be run by Matt Erasmus (@undeadsecurity). However the Thursday before BSides Matt had to pull out which left a 2 hour slot in the BSides schedule free (Can you guess where this is going??).

Friday morning I get an email from Iggy (@GeekChickUK) asking if I fancied running the workshop instead. No my initial panic fuelled response was going to be “God no” but then I thought “Why not, what’s the worse that can happen).

The next 3 days were rammed with me writing a new workshop for a group (well I was hoping at least 1) of people that would most likely either professional infosec ninja’s (they are all ninja’s right??) or at least be able to point out my mistakes when I made them.

On the day I think about 18 people attended my workshop, most of them laughed at my jokes and most of them (hopefully) learnt something new about how awesome Scapy is. I’ve just found out the online feedback form for the whole BSides London event contains questions about my workshop so I will leave judging it’s success till I see those..

If nothing else it’s made me want to run more workshops, not just on Scapy but on other areas as I learn them, so I just want to say a BIG THANK YOU to Iggy for giving me that nudge and of course all the people that attended my workshop on the day.

The GitHub repo is HERE
The Slide Pack is HERE
The Scapy Cheat Card (pdf version) is HERE