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Welcome to Mark Baggett - In Depth Defense

I am the course Author of SANS SEC573 Automating Information Security with Python. Check back frequently for updated tools and articles related to course material.




Worst cognitive password?

Cognitive passwords are those questions your bank and other accounts have you setup so that you can reset your password or verify your identity if you have forgotten your password.   I personally am not a big fan of these.   If forced to implement a solution based on these I would go with several "In the Wallet" questions.   Questions that would require the individual pull something from there wallet to answer the question.   Things like:
"What are the last 6 digits of your library card number?" 
"What is the last name of the issuer of your fitness club card?" 
"What is the last 6 digits on your favorite Shopping club card?"
If you use these types of questions you have to give the user many choices.   Not everyone has a shopping club card  or a library card, so a broad set of questions works best.   The goal of coming up with the questions should be to have answers that can not be easily guessed or looked up on the internet.   Here are some examples of horrible questions.

Looked up with some simple information about the user:
"So Sarah Palin, where did you meet your spouse?"
"What is your voting precinct or district?"

Easily brute forced or guessed:
"What is your favorite baseball team?"   Guess what 80% of the people in Atlanta say.
"What is your favorite color?"   Come on, who isn't madly in love with one of the primary colors?

The last category of question that suck is those tha only a few possible answers that could be right.   Today I renewed by subscription to a prominent computer SECURITY magazine that asked me, "How many siblings do you have?"  With the exception of a few families we can pretty much rule out anything greater than 4.  And all of those families have their own discovery channel show, so we know their answers.   The best I can hope for is that my answer wont be brute-forced in the first 5 attempts!

Summary:  Avoid cognitive passwords if you can.  If you have to use them, be very careful with the questions you choose.



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SRUM-DUMP and SRUM_DUMP_CSV Ported to Python 3

SRUM_DUMP and SRUM_DUMP_CSV have been ported to Python3 and are available for download from the PYTHON3 branch of my github page.

https://github.com/MarkBaggett/srum-dump/tree/python3

In moving to Python3 I also updated the modules that I depend upon to parse and create XLSX files and access the ESE database that contains the SRUM data.  I hope that this will fix the issue that some users have experienced with SRUDB.dat files that create very large spreadsheets.  If it does not please let me know and continue to use SRUM_DUMP_CSV.EXE to avoid the XLSX problem.

In moving to Python3 you will find the process to be faster.

If you would like to run the tools from source instructions for doing so are in the README on the github page.

Awesome Keyboard Tricks - Clevo/Sager Backlight control from Powershell

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Use Python and Scapy to Easily Do Full Duplex Stream Reassembly!

Check out this blog on how to get scapy to do full packet reassembly in just a few lines of Python code.

https://pen-testing.sans.org/blog/2017/10/13/scapy-full-duplex-stream-reassembly


New tool Freq_sort.py

I read an article on Fireeye's website the other day where they used Machine Learning to eliminate a lot of the noise that comes out of tools like strings.  It's pretty interesting and looks like it would save me some time when looking through malware.

https://www.fireeye.com/blog/threat-research/2019/05/learning-to-rank-strings-output-for-speedier-malware-analysis.html

I wondered how effective freq.py scores would be in helping to eliminate the noise.  45 minutes and 29 lines of Python code later I have something that looks like it works.  Check out freq_sort.py.

Before freq_sort.py here is the output of strings on a piece of malware:

student@573:~/freq$ strings -n 6 malware.exe | head -n 20
!This program cannot be run in DOS mode.
e!Rich
`.rdata
@.data
.pdata
@.gfids
@.rsrc
@.reloc
\$0u"H
L$ SVWH
K SVWH
|$ H;_
<bt%<xt!<Zt
|$ AVH
l$ VWAV
L$ SUVWH
UVWATAUAVAWH
0A_A^A]A\_^]
UVWATAUAVAWH
@A_A^A]A\_^]

After freq_sort.py the useful stings quickly bubble to the top.  Its not perfect but th…

FREQ and FREQ-SERVER UPDATE

While sitting in SANS SEC511 I listened to @sethmisenar lament the difficulty in using existing tools to detect DGA (Dynamically Generation Algorithm) hostnames used by malware. There are lots of AI based tools out there that do this but some are rather complex. I thought I could quickly write a tool that would work. In about 30 minutes I threw together some old code I had lying around from a SQL Inction tool I worked on and I had a working proof of concept. freq.py was born and it worked pretty well. A year later @securitymapper had me wrap it in a web interface so he could query it from a SIM and then the tool took off. It turns out to be a pretty effective technique and gained some popularity and wide use! This is a rewrite of the tool that incorporates some lessons learned and performance enhancments.
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