Tshark Examples for Extracting IP Fields
In a previous blog entry, I referenced using tshark to extract IP header information so that it could be sorted and analyzed. I had a number of questions around how this works, so I wanted to post a more in-depth blog entry that discusses tshark’s ability to display specific header fields. I’ll also dive into how these fields can be extracted and manipulated. For reference, here’s the screen capture that started the conversation:
Let’s break down some of the components of this command.
Reading Capture files With Tshark
By default, tshark will listen on the local interface in order to grab packets off the wire. If you have a pcap file that you wish to process, you can use the “-r” command. If you will be printing the output to the screen, I like to pipe the output through “head” (show only a specified number of lines of output) or “less” (show one full page of output at a time) so that it’s easier to read. For example:
tshark -r interesting-packets.pcap | head
By default “head” will show the first 10 lines of output but you can modify this as needed, feeding it the number of lines you want to see as a command line switch. For example in the first screen capture, I used “head -20” to print the first 20 lines of output.
Filtering Traffic With Tshark Capture Filters
When we review a pcap file, there is usually a specific characteristic we are looking for. For example, we may wish to examine all traffic associated with a specific IP address or service. Capture filters permit us to start honing in on an interesting pattern.
If you are a Wireshark user, capture filters work a bit differently with tshark versus Wireshark. Tshark actually uses the Wireshark Display Filter syntax for both capture and display. This is pretty cool as it provides a lot more functionality. The syntax for tshark capture filters is:
Some examples would be:
ip.dst==192.168.1.10 ip.proto==17 tcp.flags.reset!=0
Note that in the second example I have to use the protocol number (17) instead of the protocol name (UDP). This is pretty common for most filters. Use the Wireshark Display Filter syntax page I referenced above to identify the proper format to use. In the first two examples, I use the operator “==” to identify that the value must be a match. Note that in the last example I use “!=” which means not equal to. You can also use greater than ( >> ), less than ( << ), equal to or greater than ( >= ) or less than or equal to ( <=).
Also, note that in the last example I’m matching on a single bit (reset bit in byte 13 of the TCP header). This means I need to identify if I’m interested in the bit being on (represented by a “1”) or off (represented by a “0”). So another possible way to write that last example would be:
If I’m interested in traffic associated with a specific IP address, I could build on the “-r” command above as followed:
tshark -r interesting-packets.pcap ip.dst==192.168.1.10 | head
Redirecting Tshark Output to a New File
Sometimes it is helpful to read an existing pcap file and redirect the output to a new file. For example, what if I wanted to take all traffic associated with a specific IP address and put that in a different file for further analysis? This would permit me to review this new file and possibly refine my filtering even further. We can use “-w” to create a new capture file. Here’s an example:
tshark -r interesting-packets.pcap -w interesting-host.pcap ip.dst==192.168.1.10 | head
Selecting Which Fields to Output With Tshark
By default, tshark will print a brief summary of each packet which includes various header fields. Here’s an example:
While this is handy when performing a quick decode, what if the information we wish to review is not in the default output? What if we only want to see one or two of the fields but not everything else? Luckily tshark lets us specify the exact fields we wish to see.
We can use the command line switch “-T fields” to identify that we wish to specify the exact fields to print rather than showing the default information. We can then use “-e” to identify which specific fields to print. The values I use with “-e” are the Wireshark Display Filters I mentioned earlier. Here’s an example that would print just the source and destination IP address:
tshark -r interesting-host.pcap -T fields -e ip.src -e ip.dst ip.dst==192.168.1.10 | head
This would produce output similar to the following:
If I want to organize this for viewing, I can add the “-E header=y” switch as shown in the first screen cap. This will print out the first line of column titles. While this can be helpful if you will be importing the data into a spreadsheet, I don’t recommend it if you will be manipulating data from the command line. This is because the column titles may get mixed in with the data.
Organizing Tshark Fields For Additional Processing
Let’s assume we want to extract certain fields out of our packets and move them to a file for further processing. The first thing we should do is print the interesting fields but use a consistent column separator so that the values will be easier to pass to other tools. For this, we will use the “separator” switch and set it to use a comma. Here’s an example command:
tshark -r interesting-host.pcap -T fields -E separator=, -e ip.src -e
ip.dst ip.dst==192.168.1.10 | head
This will give me output similar to the last example, but with commas instead of spaces between the printed values. Finally, rather than printing to the screen, we should redirect the output to a text file. This way we can feed that file into additional tools for processing. Here’s an example:
tshark -r interesting-host.pcap -T fields -E separator=, -e
ip.src -e ip.dst ip.dst==192.168.1.10 > analyze.txt
This will result in a text file where each line contains information extracted from a single packet. The line will include the source and destination IP address separated by a comma.
Manipulating Tshark Output
Which tools I should use to manipulate the data depends on the goal I’m trying to achieve. Linux has a wide range of text manipulation tools such as cut, sort, uniq and grep. With a bit of Google searching, you can find a ton of useful write-ups on using each of these tools. For this blog entry, I want to cover the “R” command as it permits us to do some statistical analysis.
Here’s the command I used to generate data output similar to the first screen capture, but in a format, I can use for beacon analysis:
tshark -r interesting.pcap -T fields -E separator=, -e ip.src -e ip.dst -e
ip.proto -e udp.dstport -e ip.len -e
frame.time_delta_displayed ip.dst==188.8.131.52 and udp.dstport==53 > analyze.txt
This produced a file called “analyze.txt” which contained data similar to the following:
192.168.88.2,184.108.40.206,17,53,89,1.073288580 192.168.88.2,220.127.116.11,17,53,89,1.067193833 192.168.88.2,18.104.22.168,17,53,89,1.057524219 192.168.88.2,22.214.171.124,17,53,89,1.085981806 192.168.88.2,126.96.36.199,17,53,89,1.072384382
It is the last two fields I’m interested in analyzing. With beacon analysis, I want to look for repeating patterns. Consistency in both session data size and timing can be indications of an internal system that has been compromised and is calling home. One way to check for repeating patterns is to analyze the standard deviation and the variance of the data. Luckily the R command can do this for us.
I’m going to use “cut” to extract the column of data that I’m interested in analyzing, and then use R to identify the minimum, maximum, mean, standard deviation and variance of the data set. Here’s an example:
cut -d ',' -f 5 analyze.txt | Rscript -e 'y <-scan("stdin", quiet=TRUE)' -e 'cat(min(y), max(y), mean(y), sd(y), var(y), sep="\n")' 89 290 95.74 33.82236 1143.952
In the above example, “cut” extracts column 5 which is the amount of data transferred in each session. It then passes these values to “R” which calculates the minimum, maximum, mean, standard deviation and variance for this data set. Note that my standard deviation is much larger than the difference between the mean and the minimum value. This tells me that most of my sessions are closer to the minimum 89 byte size. This is somewhat interesting because it indicates that the majority of traffic exchanged between these two systems involved sessions with a small amount of data. This could be indicative of a beaconing heartbeat but is certainly not conclusive.
I can perform a similar analysis on the session timing:
cut -d ',' -f 6 analyze.txt | Rscript -e 'y <-scan("stdin", quiet=TRUE)' -e 'cat(min(y), max(y), mean(y), sd(y), var(y), sep="\n")' 0 2.088164 0.9999386 0.2973222 0.08840052
This is where things get really interesting. Note that the maximum gap between sessions is just a bit over two seconds. This is extremely frequent. Also, note that the variance from the mean is just .08840052 seconds or about 88 ms. This tells us that an overwhelming majority of the communication sessions are taking place almost exactly .9999 seconds apart from each other. This is a clear indicator of a beacon heartbeat. Based on this data, if I did not expect to see beacon behavior between these two systems, I would want to subject the internal system to a forensic analysis.
One of the challenges of packet analysis is honing in on the interesting bits and ignoring everything else. This can be a challenge with the default view in most packet decoders, as you either get too much information or not enough. Further, while graphical analysis tools can be easy to use, they make it difficult to leverage other tools or automate an analysis. By leveraging tshark’s ability to print specific fields, you can manipulate data as needed to perform an in-depth analysis.
Interested in threat hunting tools? Check out AC-Hunter
Active Countermeasures is passionate about providing quality, educational content for the Infosec and Threat Hunting community. We appreciate your feedback so we can keep providing the type of content the community wants to see. Please feel free to Email Us with your ideas!
Chris has been a leader in the IT and security industry for over 20 years. He’s a published author of multiple security books and the primary author of the Cloud Security Alliance’s online training material. As a Fellow Instructor, Chris developed and delivered multiple courses for the SANS Institute. As an alumni of Y-Combinator, Chris has assisted multiple startups, helping them to improve their product security through continuous development and identifying their product market fit.