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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.

Senior SANS Instructor
GSE #15
Internet Storm Center Handler
Penetration Testing and Incident Response Consultant
Technical Advisor to DoD for The SANS Institute
Founding President of the Greater Augusta ISSA
Cofounder of BSidesAugusta Security Conference


Tools:
FREQ SERVER - Tool and technique for detecting Malware Command and Control domains
DOMAIN_STATES - Tool for detecting "Baby Domains" used for phishing and Malware distribution
SRUM_DUMP - Forensics tool for extracting System Resource Utilization Monitoring artifacts
LIAM_NEESON - Proof of Concept Linux Hash Protection
HONEY_HASHES - Certainly Honey Tokens have been around since 2003 but I created a cool technique for creating fake SATs in memory that was turned into Dell Secure Works DCEPT framework.
VSSOWN - Tool & Technique for Using Microsoft Volume Shadow Copies for hiding malware and extracting artifacts
SDB Hacking - Using Application Compatibility in unexpected ways.
SET-KBLED - Utility for Managing Clevo and Sager Laptop LED Backlit Keyboards
Reassembler.py - Scapy based fragement reassembly engine
eapmd5crack.py - A password cracker for the EAP protocol


and more. Most of these tools are available on my github page. Follow me on twitter @markbaggett





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.
Recent posts

Three Free Python apps to improve your defenses and incident response

I did a SANS Webcast on a couple of tools I developed to use automation to enhance your network defenses and incident response capability.    If you missed it you can check it out here:


Kringlecon Escaping Python Shells

If you had told 8 year old me that one day I would get to travel to the North Pole, meet Santa Claus and speak at Kringlecon I would, in complete honestly, have thought you were crazy and ran screaming to my parents in fear of you.   But it happened!   I gave a short talk at Kringlecon.   The talk was an abbreviated version of the talk I gave at SANS Pen Test Hackfest in 2018.   I will also be giving the full talk a few time at SANS conferences in 2019 so come by and see it.
You can download the associated sample code and follow along at here.
Check out Kringlecon here.

You can watch the Kringlecon talk here:






Security Onion getting the most from Freq.py and Domain States

My talk at Security Onion conference has been posted and is available for viewing here.


Python Decorators Webcast

In October I did a SANS Webcast on Python Decorators.  It was recorded and is available on YouTube.   Check it out.



SRUM DUMP and SRUM DUMP CSV Updated

An issue was reported where is some conditions SRUM_DUMP would stop processing and print the following error to the screen.

UnboundLocalError: local variable 'sid_str' referenced before assignment
The issue was that sometimes the SRUM database had entries in it that were all zeros.

OrderedDict([('IdType', 3), ('IdIndex', 38127), ('IdBlob', '0000000000000000')])

I've released an update that handles the anomoly althought I do not understand the circomstances of why Windows would record all zero's for as the user SID.

The issue was fixed and new versions of both SRUM DUMP and SRUM DUMP CSV were released.






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.
Improvements: -Only one table is required for case sensitve or insensitive lookups. The tables are all case sensitive. You can turn off and on case sensitivity and the .probability l…