Logs, Logs, Logs. I see, IPs. When reviewing log files for suspect activity it can be helpful to look up information related to IP addresses. There is a great utility for this by Nirsoft called IPNetinfo. You can import a whole list of IP addresses and it will give you "the owner of the IP address, the country/state name, IP addresses range, contact information (address, phone, fax, and email), and more."
When I am reviewing log files, an IP address associated with a foreign country may peak my interest. Another check I like to do is look for activity associated with Tor nodes. In a corporate environment, a user accessing a system from a Tor exit node may be a red flag.
When I am checking an IP address to see if it is associated with a Tor exit node I will use a website like ExoneraTor. It lets me put in an IP address and a date, and lets me know if the IP address is associate with a Tor relay. While this is a great tool, if I have a list of IP addresses to check, it's not very efficient. To that end, I wrote a little program to help automate the process of checking a list of IP addresses against Tor Relays and Bridges, Onion Peeler.
Onion Peeler is written in Python and uses OnionPy. OnionPy is a wrapper for the OnionOO Tor Api. Using OnionPy, Onion Peeler caches a local copy of the Tor exit nodes and performs a check for a list of supplied IP addresses. What's nice is that if you have a list of sensitive IPs, the information is not shared and is kept locally:
It will output a list of matches:
Since it's in Python, the program is cross-platform compatible. I've tested it on Windows, Linux and Mac. It just requires OnionPy, which can be installed using "pip install OnionPy". I also have a compiled Windows Executable if you don't have Python installed. It requires an Internet connection as the initial query grabs the latest Tor nodes from OnionOO. I am thinking about adding in a way to store an offline copy in the next version as well as add in additional details about the Tor nodes (first seen, last seen etc.)
It took about a minute to check 8,000 IP addresses. Of course, a bigger list will take longer, so be patient.
Code and program are available on my github.
Great stuff, Mari! Thanks for sharing and continuing to lead within the community with your example.ReplyDelete