Thursday, April 22, 2010

Command Line Goodness Part II fortunately for me (and you), I am working a case right now that will help me to illustrate my point about using the command line perfectly. Now, let me preface these next few posts, and simply state that this is MY way of using the command line to parse data. There are SO many tools, and SO many different command switches, that you could literally skin the proverbial cat a dozen different ways. My way works for my purposes. If you have a command syntax that is more efficient, please let us know! I'm all about getting better!

Now, In this case, I have six images from a Point of sale (POS) network. My first goal is to find if I have track data in the clear on any of the images. Since this the fraud in this case is "card present", meaning that the bad guys jacked track data and used it to create new cards, I am anticipating finding some. For the purposes of data reduction, I JUST want to work with the systems with clear text track. So...I mount my images read only with ImDisk (This is pretty basic, so I am not going to cover how to do this in this post. Basically, you just need a single raw image, since ImDisk will not work with split images.) Once mounted, I use this command:

z:\>egrep -r "\;?[0-9]{12,19}[\=][0-9]{12,32}\.?" * > c:\cases\track2hits

This regex will provide me with all of the matches, along with their full paths. Now, I anticipate finding data in log files, or backup files. However, what I am looking for is a totally abnormal location. For example, in this case, I found a file we'll call "winprc.dll". Now, dll files should NOT contain track least none that I have ever seen, so this is automatically extremely suspect and likely a dump file for a credit card sniffing malware. How do I know this?

Well...think about it for a second. You have track a dll...which should absolutely not be there. Something put it had to to get there in the first place. So, in less than 30 minutes, I know can make the logical ju
mp to the fact that I have an intruder, I have malware (since I have a dump file), and I will logically have to have an exfiltration point....bad guy has to get his goodies off the network so he can make his counterfeit cards right? All this from a single regex...pretty kewl huh.

Now, I can start creating my "dirty word list"
or set of keywords to search on later. The name of this dll is now at the top of my list. next, I am interested in who connected to this box. So, I export my event logs in hopes of finding some IP addresses. Once I export them, I convert them into flat text files with Event Log Explorer and stick in them my working case directory.

Now, I JUST want the IPs from the log
s...nothing else. Now, since I am working with customer data, I am not going to show the actual event logs, but here is a screenshot of the event logs from my local machine.

OK...a quick check with word count and I see that I have 2394 lines in JUST this one log. (cat filename | wc -l). Now, I could export the logs to a csv and go through it in a spreadsheet, but that would require me to manually pick out IPs. WAY too time consuming. I want answers now. So...back to my regexes. I can use the regex for IP addresses and let's see how much smaller we can make this sample.

egrep -o "\b(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\b" | sort | uniq

SO...this regex pulls out anything that matches an IP address, the "-o" option shows me ONLY the hits for the regex (as opposed to the entire matching line), "sort" puts them in numerical order, and uniq removes the duplicates. Leaving me with this...

A whopping 10 IP addresses...or at least what appear to be IP addresses, but that' for me to figure out. Now again, this is not the data from the images, but from my local machine, but it clearly illustrates my point. I went from over 2000 lines of log files, to 10 in a few seconds by using the command line. Now, if you want to get a count say of the number of time each IP appears, simply add the -c (for count) option. In this example, my results looked like this...


The number off to the left shows the number of times each IP appears in the log. Pretty slick.

Now, you can use these commands to parse anything...not just IPs! In my current case, working with these two commands gave me an idea of what was going on, and which IPs may have interacted with this system, all in under 30 minutes. Not going to solve the case by any stretch, but as you can see I can perform significant data reduction using these methods.

In my next post I will cove how to use cut and awk to carve more complex log files to extract JUST the data you want.

Monday, April 19, 2010

Command Line Goodness Part 1 if you don't know how to use the command line effectively in your investigations, you are REALLY limiting yourself. Sure, there are plenty of tools that will do what I am going to cover in the next few posts, but I would argue that using the command line is MUCH faster, more efficient, and if done properly, can help you perform data reduction with more accuracy...not to mention that these methods and tools are FREE.

First of all, you will need to download UnxUtils. This is a suite of Windows port overs of the most popular Unix command line utilities. After you unzip the file, you can either drop them into the system32 directory, or add their path to your profile. You will also want to grab, grep v2.5.4, MD5deep and SSDeep, as well as perl and python v2.6.5. Once you have these command line utilities installed and part of your path, you should be able to use them from any location...which is WAY better than having to navigate to each respective directory just to issue a command.

So...not to rush, but I am getting on a plane shortly, so I am going to provide you with my list of regexes and a few commands. We will use these for the throughout the duration of this blog series, so if you are going to follow along, get your box set up, and we will begin analysis in part two!

All credit cards:
egrep -r "(4[0-9. -]{12}(?:[0-9]{3})?|5[1-5][0-9]{14}|6(?:011|5[0-9][0-9])[0-9]{12}|3[47][0-9]{13}|3(?:0[0-5]|[68][0-9])[0-9]{11}|(?:2131|1800|35\d{3})\d{11})" * > :\outfile.txt

Generic CC Numbers :

CC Numbers by brand:
Visa - ^4[0-9]{12}(?:[0-9]{3})?$
MC - ^5[1-5][0-9]{14}$
AMEX - ^3[47][0-9]{13}$
Discover - ^6(?:011|5[0-9]{2})[0-9]{12}$
JCB - ^(?:2131|1800|35\d{3})\d{11}$
Diners [^0-9](30[0-5]{1,1}[0-9]{11,11})|(3[68][0-9]{12,12})[^0-9]
JCB [^0-9]35[2-8]{1,1}[0-9]{1,1}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[^0-9]
MasterCard [^0-9](36[0-9]{12,12})|(5[1-5]{1,1}[0-9]{2,2}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[^0-9])
Visa-13 [^0-9]4[0-9]{12,12}[^0-9]
Visa-16 [^0-9]4[0-9]{3,3}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[^0-9]
AMEX [^0-9]3[47][0-9]{2,2}[\x20\-]{0,3}[0-9]{6,6}[\x20\-]{0,3}[0-9]{5,5}[^0-9]
Discover [^0-9](6011)|(6[245][0-9]{2,2})[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[\x20\-]{0,3}[0-9]{4,4}[^0-9]

Track 1:
\%?B[0-9 ]{12,19}\^[^\^]+\/[^\^]+\^[0-9]{7,7}[^\?]+\.?

Track 2:

IP address: '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}'
egrep -o "\b(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\b"



awk '{sub(/^/, "", $1); print }'

awk '{sub(/=(.)*/, "", $1) ; print }'

cut -d':' -f2 <-- This command cuts all before the ":" See you soon!

Thursday, April 8, 2010

The Next HOPE Conference

Sniper Forensics was just picked up by The Next HOPE (Hackers On Planet Earth) conference in New York City from July 16 - 18. Sweet!

Monday, April 5, 2010

ITB 0x1 Released

Issue 0x1 of ITB was posted this morning! There are some great articles by Don Weber, Harlan Carvey, Jamie Levy, Didier Stevens, and Me. Please give it a read, and give us some feedback! We really want this to be a success so like anything in the open source community, your input and assistance is needed.