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Published on February 5th, 2019📅

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Fnord – Pattern Extractor For Obfuscated Code

Fnord is a pattern extractor for obfuscated code

Description
Fnord has two main functions:

  1. Extract byte sequences and create some statistics
  2. Use these statistics, combine length, number of occurrences, similarity and keywords to create a YARA rule

 

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1. Statistics
Fnord processes the file with a sliding window of varying size to extract all sequences of with a minimum length -m X (default: 4) up to a maximum length -x X (default: 40). For each length, Fnord will present the most frequently occurring sequences -t X(default: 3) in a table.
Each line in the table contains:

  • Length
  • Number of occurrences
  • Sequence (string)
  • Formatted (ascii/wide/hex)
  • Hex encoded form
  • Entropy

2. YARA Rule Creation
Fnord also generates an experimental YARA rule. During YARA rule creation it will calculate a score based in the length of the sequence and the number of occurrences (length * occurrences). It will then process each sequences by removing all non-letter characters and comparing them with a list of keywords (case-insensitive) to detect sequences that are more interesting than others. Before writing each string to the rule Fnord calculates a Levenshtein distance and skips sequences that are too similar to sequences that have already been integrated in the rule.

Status
[Experimental] Fnord was created a few days ago and I have tested it with a handful of samples. My guess is that I’ll adjust the defaults in the coming weeks and add some more keywords, filters, scoring options.

Improve the Results
If you’ve found obfuscated code in a sample, use a hex editor to extract the obfuscated section of the sample and save to a new file. Use that new file for the analysis.
Play with the flags -s-k, -r–yara-strings-mand-e`.
Please send me samples that produce weak YARA rules that could be better.

Usage

        ____                 __
       / __/__  ___  _______/ /
      / _// _ \/ _ \/ __/ _  /
     /_/ /_//_/\___/_/  \_,_/ Pattern Extractor for Obfuscated Code
     v0.6, Florian Roth

    usage: fnord.py [-h] [-f file] [-m min] [-x max] [-t top] [-n min-occ]
                    [-e min-entropy] [--strings] [--include-padding] [--debug]
                    [--noyara] [-s similarity] [-k keywords-multiplier]
                    [-r structure-multiplier] [-c count-limiter] [--yara-exact]
                    [--yara-strings max] [--show-score] [--show-count]
                    [--author author]

    Fnord - Pattern Extractor for Obfuscated Code

    optional arguments:
      -h, --help            show this help message and exit
      -f file               File to process
      -m min                Minimum sequence length
      -x max                Maximum sequence length
      -t top                Number of items in the Top x list
      -n min-occ            Minimum number of occurrences to show
      -e min-entropy        Minimum entropy
      --strings             Show strings only
      --include-padding     Include 0x00 and 0x20 in the extracted strings
      --debug               Debug output

    YARA Rule Creation:
      --noyara              Do not generate an experimental YARA rule
      -s similarity         Allowed similarity (use values between 0.1=low and
                            10=high, default=1.5)
      -k keywords-multiplier
                            Keywords multiplier (multiplies score of sequences if
                            keyword is found) (best use values between 1 and 5,
                            default=2.0)
      -r structure-multiplier
                            Structure multiplier (multiplies score of sequences if
                            it is identified as code structure and not payload)
                            (best use values between 1 and 5, default=2.0)
      -c count-limiter      Count limiter (limts the impact of the count by
                            capping it at a certain amount) (best use values
                            between 5 and 100, default=20)
      --yara-exact          Add magic header and magic footer limitations to the
                            rule
      --yara-strings max    Maximum sequence length
      --show-score          Show score in comments of YARA rules
      --show-count          Show count in sample in comments of YARA rules
      --author author       YARA rule author

Getting Started

  1. git clone https://github.com/Neo23x0/Fnord.git and cd Fnord
  2. pip3 install -r ./requirements.txt
  3. python3 ./fnord.py --help

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Examples

python3 fnord.py -f ./test/wraeop.sct --yara-strings 10
python3 fnord.py -f ./test/vbs.txt --show-score --show-count -t 1 -x 20
python3 fnord.py -f ./test/inv-obf.txt --show-score --show-count -t 1 --yara-strings 4 --yara-exact

Screenshots

 

 

FAQs

Why didn’t you integrate Fnord in yarGen?
yarGen uses a white-listing approach to filter the strings that are best for the creation of a YARA rule. yarGen applies some regular expressions to adjust scores of strings before creating the YARA rules. But its approach is very different to the method used by Fnord, which calculates the score of the byte sequences based on statistics.
While yarGen is best used for un-obfuscated code. Fnord is for obfuscated code only and should produce much better results than yarGen.

Contact
Follow on Twitter for updates @cyb3rops

Download Fnord



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