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
This is a collection of Articles, Tools, Conference talks, interviews, etc by Mark Baggett