Recently Ed Michael showed me that Cellebrite now parses cell tower locations from several models of Android phones. He said that this information has been useful a few times but manually finding and mapping the cell tower locations by hand has been a pain in the butt. I figured that it should be easy enough to automate and Anaximander was born.
Anaximander consists of two python 2.7 scripts. One you only need to run once to dump the cell tower location information into a SQLite database and the second script you run each time to generate a Google Earth KML file with all of the cell tower locations on it. As an added bonus, the KML file also respects the timestamps in the file so modern versions of Google Earth will have a time slider bar across the top to let you create animated movies or only view results between a specific start and end time.
Step one is to acquire the cell tower location. For this we go to http://opencellid.org/ and sign up for a free API. Once we get the API key (instantly) we can download the latest repository of cell phone towers.
Currently the tower data is around 2.2 GB and contained in a CSV file. Once that file downloads you can unzip it to a directory and run the dbFill.py script from Anaximander. The short and simple script creates a SQLite database named “cellTowers.sqlite” and inserts all of the records into that database. The process should take 3-4 minutes and the resulting database will be around 2.6 GB.
Once the database is populated, the next time you dump an Android device with Cellebrite and it extracts the cell towers from the phone, you’ll be ready to generate a map.
From The “Cell Towers” section of your Cellebrite results, export the results in “XML”. Place that xml file and the Anaximander.py file in the same directory as your cellTowers.sqlite database and then run Anaximander.py –t <YourCellebriteExport.xml> . The script will start parsing through the XML file to extract cell towers and query the SQLite database for the location of the tower. Due to the size of the database the queries can take a second or two each so the script can take a while to run if the report contains a large number of towers.
Ed was kind enough to provide two reports from different Android devices and both parsed with no issues. Once the script is finished it will let you know how many records it parsed and that it generated a KML file.
This is what the end results look like.
The script can be downloaded from: https://github.com/azmatt/Anaximander
This is the first version and there are several improvements to make but I wanted to get a working script out to the community to alleviate the need for examiners to map the towers one at a time. Special thanks again to Ed Michael for the idea for this (and one other) script as well as for providing test data to validate the script.