Knowing User Locations Out of Tweets
If you have been using Twitter, you may think that you are tweeting your updates from sheer
randomness; however, the truth is that you are following an informal formula for the tweets that
you compose. Generally, this formula includes another Twitter user’s name which tells to whom
your tweet is directed to, the text of your tweet, and your choice of hash tag. There are other data
included in your tweet, which may not be visible in the body of your tweet, such as an image that
you want to share or a location.
To a hacker, all the information in your tweet contains something
that will be important in writing an attack – when you think about it, you are giving away
information about the person that you are interested in, links that you and your friend are likely to
be interested in, and trends that you might want to learn about. The pictures, especially an image
of a location, become added details to a user’s profile, which for example may indicate where a
targeted person is likely to go to eat breakfast.
If you want to get details anonymously to retrieve all these information, you can use the following
code:
Now, you can test this script by creating a list of cities that host major league teams. After that you
can scrape Twitter accounts for Washington Nationals and the Boston Red Sox. Your script will
look like this:
When your script returns with the above results, you are likely to deduce that the these teams are
tweeting live from where they are. From this output, you may deduce that the Red Sox are playing
in Toronto, while the Nationals are in Denver.
Matching an IP Address to a Physical Location
Most of the time, people are willing to post what is on their mind on social media sites, or
perform attacks that they find using online tools that they can download, thinking that they will
never have to face the consequences of their actions. While most bullheaded yet inexperienced
hackers and online trolls think that they can hide behind a fake account to conceal their identity,
you can prove that these people are not as anonymous as they think they are. In fact, there are
several ways to use libraries and third-party modules in Python to unmask the location and
identity of a user based on his or her IP address.
For example, you suspect that your system is being targeted by another hacker and you notice that
your open ports are being sniffed by a particular IP address. What you will want to do once you
realize this potential attack is to identify that IP address’ location and report it to the authorities.
Python can help you do that using a script that is similar to what is going to be discussed in this
section.
In this example, you will be using the freely available database that can be found in
http://www.maxmind.com/app/geolitecity. Using this free database, you will aim to write a code
that will match the IP addresses found on their list to cities. To do that, download the free
database, decompress it, and send it to the location /opt/GeoIP/Geo.dat.
Once you are able to download the GeoCityLite database, you will be able to analyze the IP
addresses down to locating the country name, state, postal code, and a general longitude and
latitude. To make the job easier, you can use a Python library created to analyze this database.
When you run this script, you will be able to see data that looks like this:
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