Developed since 2011 for the needs of the French Internet Resilience Observatory, TaBi is a framework that ease the detection of BGP IP prefixes conflicts, and their classification into BGP hijacking events. The term prefix hijacking refers to an event when an AS, called an hijacking AS, advertises illegitimately a prefix equal or more specific to a prefix delegated to another AS, called the hijacked AS.
Usually, TaBi processes BGP messages that are archived in MRT files. Then, in order to use it, you will then need to install a MRT parser. Its favorite companion is MaBo, but it is also compatible with CAIDA's bgpreader. Internally, TaBi translates BGP messages into its own representation. Therefore, its is possible to implement new inputs depending on your needs.
- Nicolas Vivet firstname.lastname@example.org
- Guillaume Valadon email@example.com
- Julie Rossi firstname.lastname@example.org
- François Contat email@example.com
TaBi depends on two external Python modules. The easiest method to install them is to use virtualenv and pip.
If you use a Debian-like system you can install these dependencies using:
Then install TaBi in a virtual environment:
apt-get install python-dev python-pip python-virtualenv
Removing TaBi and its dependencies is therefore as simple as removing the cloned repository.
pip install py-radix python-dateutil
python setup.py install
Historically TaBi was designed to process MRT dump files from the collectors of the RIPE RIS.
### Grabbing MRT dumps
You will then need to retrieve some MRT dumps. Copying and pasting the following commands in a terminal will grab a full BGP view and some updates.
wget -c http://data.ris.ripe.net/rrc01/2016.01/bview.20160101.0000.gz
wget -c http://data.ris.ripe.net/rrc01/2016.01/updates.20160101.0000.gz
tabi- the command line tool
tabicommand is the legacy tool that uses TaBi to build technical indicators for the Observatory reports. It uses mabo to parse MRT dumps.
Given the name of the BGP collector, an output directory and MRT dumps using the RIS naming convention,
tabiwill follow the evolution of routes seen in MRT dumps (or provided with the
--asesoption), and detect BGP IP prefixes conflicts.
Several options can be used to control tabi behavior:
Among this options, two are very interesting:
$ tabi --help
Usage: tabi [options] collector_id output_directory filenames*
-h, --help show this help message and exit
-f, --file files content comes from mabo
-p PIPE, --pipe=PIPE Read the MRT filenames used as input from this pipe
-d, --disable disable checks of the filenames RIS format
-j JOBS, --jobs=JOBS Number of jobs that will process the files
-a ASES, --ases=ASES File containing the ASes to monitor
-s, --stats Enable code profiling
-m OUTPUT_MODE, --mode=OUTPUT_MODE
Select the output mode: legacy, combined or live
-v, --verbose Turn on verbose output
-l, --log Messages are written to a log file.
-jthat forks several
tabiprocesses to process the MRT dumps faster
-athat can be used to limit the output to a limited list of ASes
Here is an example call to tabi:
After around 5 minutes of processing, you will find the following files in
tabi -j 8 rrc01 results/ bview.20160101.0000.gz updates.20160101.0000.gz
all.defaults.json.gzthat contains all default routes seen by TaBi
all.routes.json.gzthat contains all routes monitored
all.hijacks.json.gzthat contains all BGP prefix conflicts
TaBi could also be used as a regular Python module in order to use it in your own tool.
The example provided in this repository enhance BGP prefix conflicts detection, with possible hijacks classification. To do so, it relies on external data sources such as RPKI ROA, route objects and other IRR objects.