Facebook - a storehouse of information for OSINT and ways to work with it
No doubt that every Internet user has ever heard of Facebook. It is currently world’s largest social network with over 1.7 billion daily users. Just imagine, for the US alone, almost 60% of its population has Facebook accounts. Considering the size of the audience, this certainly is a good source of information. Lampyre’s developers made a lot of effort to create a set of simple and convenient request types for Facebook — let’s look at them!
First, we will look at all of them — to do that, we open List of requests and type in Facebook in Tasks window:
We bet no other OSINT tool will give you this much. Okay, we’re not going to brag, let’s see what these requests can give you. We will start with a simple one, such as Facebook checker by email. This tool determines whether a Facebook account has been created for email address you input. You can check up to 50 emails at once, depending on your subscription type.
The output table is very simple and looks the following way:
Next we are going to see what basic information Lampyre can collect based on provided Facebook ID or username (not to be confused with first and last names, username is a nickname, you see it after a slash in page address). This query is called Facebook account info by account username or ID. It fetches all the available extended information on a Facebook account by its ID or nickname. The request obtains no info on social connections of the account/accounts. In our example we will use Mark Zuckerberg’s page https://www.facebook.com/zuck . We put “zuck” in Username field:
Lampyre generates several tables, depending on data available for a given page:
Facebook accounts table has all basic user information:
The next tables are Facebook schools and Facebook universities — they collect information about schools and universities that user has provided in his profile:
In a similar way, Facebook works shows user’s employment information. Even though we all know where Mark works, let’s still check out how the table looks like:
Last but not least is statistics table, that shows user’s followers and followings:
Lampyre can also collect information on user’s friends, if this part is made visible for all users. Same as above,you just have to input user ID or nickname. This time, let’s try another account. The result generates same tables as above, but it also adds a table called Facebook friends links. which looks like this:
Another query is called Facebook hidden friends. This request restores some part of the hidden friend list of a Facebook account by its ID. The user will get a list of links to hidden friend accounts with all available information on them, and output tables will be same as for friends.
The following three request types are very identical, but we will nevertheless show you each of them.
The first one one is authors of comments:
Each of these tables collects information on all users that left comment’s on target’s posts. We will not go through each of them in detail, except for Facebook comments statistics. This table shows the total number of comments made by each user:
The table can also contain columns showing author of original posts, fullname and profile picture. By default, they are hidden, because they show values for target profile, which will be same for each row.
The second one is called authors of likes, with same tables as above, except for one called Facebook likes statistics which shows the total number of likes made by each user.
Now guess the name of the third one:
That’s right! It is for authors of reposts. All tables follow same principle as for the request above, and Facebook reposts statistics similarly reveals the total number of reposts made by each user:
In conclusion, we wanted to highlight again, that Lampyre is a very powerful and flexible tool that gives you plenty of OSINT power: investigations in Facebook are now made easy! But we would not have reached such heights without your help: your activeness and feedback lets us develop and enhance Lampyre, making it one of the best solutions for open-source-based investigations and analytics.
