Binary Akinator DESCRIPTION: This tool is run on an ELF or PE binary and tries to return k-Nearest-Neighbors files among those that have already been ingested into the pickled_files folder:

Machine Learning Model detailed in Binary Bouncer ReadMe. This model helps to strip unimportant sequences that mess with the validity of document matching due to its irrelevance.

INTENDED USE:
    * To be run on single binary file to compare against other files in existing library set
    * Returns k-Nearest-Neighbors (kNN) among library set, or those passing benchmark confidence levels

RUNNING:
    * Requirements: Existence of /buckets & /model folders within project directory,   (nothing needed in it)
    * '--help' for help
    * readelf (Unix tool) installation preferred (not required, affects Binary Bouncer results)

Library Set:
    * Stored in pickled_files/ sub-directory
    * populated by running akinator on them, to be ingested
    * comprised of previously ingested files

Data to be matched:
    * Pipes resulting buckets from Binary Bouncer, performs KNN Document Matching based on this data for each binary file in library set

Results:
    * shell output
    * results/ folder stores most recent results for each hash/filename pair
    * TODO: perhaps output the command options that were run resulting in the specified result

Pickle Validator:
    * helper_files/pickle_validator.py
    * directions on how to validate the generated pickle for recently ingested file are given as part of shell output.

IMPORTANT NOTES: (updated as necessary):
    * if file has changed after ingestion, results will not change until run again
    * all results are static/pinned to library state when originally run, updated library may need updated results -> have to run akinator on relevant files again

High Level Diagram:

USAGE:

python3 akinator.py [OPTIONS] INCOMING_BINARY
or
1) chmod +x akinator.py  (one time, turning into executable)
2) --> ./akinator.py [OPTIONS] INCOMING_BINARY


Options:
--bounce             set this flag if a previously bounced file needs to get
                    re-bounced
--n INTEGER          sets the number of nearest neighbors to return, kNN,
                    default 1
--benchmark INTEGER  return all kNN with a confidence over this benchmark,
                    default: 60
--help               Show this message and exit.