Multilevel MDA-Lite Paris Traceroute is a portable (Linux, MacOS, Windows) traceroute-like tool capable of both giving IP and router level view. It supports IPv4 for IP level and router level, and IPv6 only for IP level.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
MMLPT is written in Python, and uses different libraries to work.
To craft, send and parse packets, it uses scapy:
sudo pip install scapy
To provide a rich graph view, and to compute the IP and router level graphs, MMLPT uses graph-tool, which is a boost C++ library with a python wrapper.
Follow the instructions in the following link to install graph-tool. As the C++ Library makes an extensive use of metaprogramming and templates, it can take a while (up to 30 minutes on a recent laptop) to compile graph-tool:
To install then, just tap:
sudo python setup.py install
To run a simple MDA-Lite traceroute at IP level, tap
sudo python MDALite.py destination
To run MDA-Lite traceroute at both IP and router level, tap:
sudo python MDALite.py -a destination
You can tap the following command for the different options
sudo python MDALite.py --help
Recall that on very large topologies, the measurement can take few minutes, up to 10-15 on very complex topologies.
You should have this kind of output:
(0) : 127.0.0.1 -> ['192.168.0.254']
(1) : 192.168.0.254 -> ['137.194.164.254']
(2) : 137.194.164.254 -> ['137.194.4.240']
(3) : 137.194.4.240 -> ['212.73.200.45']
(4) : 212.73.200.45 -> ['4.69.161.114', '4.69.161.110']
(5) : 4.69.161.114 -> ['4.68.111.194']
4.69.161.110 -> ['4.68.111.194']
(6) : 4.68.111.194 -> ['62.115.122.10', '62.115.122.4']
(7) : 62.115.122.10 -> ['62.115.122.139']
62.115.122.4 -> ['62.115.123.12']
(8) : 62.115.123.12 -> ['62.115.138.236']
62.115.122.139 -> ['62.115.138.104']
(9) : 62.115.138.104 -> ['62.115.133.31', '62.115.136.37', '62.115.141.205', '62.115.119.115', '62.115.136.113', '62.115.139.107', '62.115.114.171', '62.115.136.35']
62.115.138.236 -> ['62.115.136.107', '62.115.133.29', '62.115.136.21', '62.115.136.23', '62.115.114.167', '62.115.141.201', '62.115.119.113', '62.115.136.25']
(10) : 62.115.136.107 -> ['213.248.79.106']
62.115.133.31 -> ['213.248.79.106']
62.115.133.29 -> ['213.248.79.106']
62.115.136.37 -> ['213.248.79.106']
62.115.141.205 -> ['213.248.79.106']
62.115.136.21 -> ['213.248.79.106']
62.115.119.115 -> ['213.248.79.106']
62.115.136.23 -> ['213.248.79.106']
62.115.136.113 -> ['213.248.79.106']
62.115.139.107 -> ['213.248.79.106']
62.115.114.171 -> ['213.248.79.106']
62.115.114.167 -> ['213.248.79.106']
62.115.141.201 -> ['213.248.79.106']
62.115.119.113 -> ['213.248.79.106']
62.115.136.25 -> ['213.248.79.106']
62.115.136.35 -> ['213.248.79.106']
(11) : 213.248.79.106 -> ['195.12.233.115']
(12) : 195.12.233.115
Routers found :
['62.115.136.113', '62.115.136.107']
['62.115.136.23', '62.115.133.31', '62.115.141.201', '62.115.136.21', '62.115.136.25']
['62.115.133.29', '62.115.119.113', '62.115.119.115']
['62.115.136.35', '62.115.136.37']
If the text output is not verbose enough, you can ask for a serialized version of the graph that basically keeps all the informations of the traceroute with the -o option
sudo python MDALite.py -o traceroute.xml -a destination
from graph_tool import *
g = load_graph("/path/to/serialized/graphs.xml")
# Manipulate the graph via its properties.
v_properties = g.vertex_properties
e_properties = g.edge_properties
g_properties = g.graph_properties
# Example: ip_ids, print ip_ids of an ip_address
ip_address = g.vertex_properties["ip_address"]
ip_ids = g.vertex_properties["ip_ids"]
for v in g.vertices():
if ip_address[v] == "an_ip_of_your_choice_in_the_traceroute":
print ip_ids[v]Dockerfile provides an example of a Docker script that allows you to deploy MMLPT in a Dockercontainer (in the example with an ubuntu image). To build the container, launch the command:
docker build --build-arg "CACHE_DATE=$(date)" -t "name/of/your/docker/image" .
Then push it to docker repository:
docker push name/of/your/docker/image
To run it:
docker run -d name/of/your/docker/image