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Awesome Keyboard Tricks - Clevo/Sager Backlight control from Powershell

I'm back on Windows. After 8 years on a Macintosh I just couldn't go another day with ONLY 16GB of RAM. I priced it out and for the cost of a top of the line MacBook I could get a tricked out PC with 32GB of ram and 2.5 TB or hard drive space (1.5 of it being SSD). So I made the switch. To get a top performing laptop I ended up buying a gaming machine from xoticpc.com. The model is Sager NP9752 ( Clevo P750ZM ). I have to say I like it quite a bit. One of the features I was curious about was the "Programmable backlit keyboard". With it you can set your keyboard backlight to various colors and light movement patterns. Now, when I hear "programmable" I think APIs. I was a little disappointed to find out there weren't any documented APIs that I could use to control the keyboard. Your only choice is to use their built in tool to configure the lights on the keyboard. That stinks. I want to be able to change key colors automatically

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.

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 t

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.

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:

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