DBFP: [D]ata[B]ase [F]inger[P]rint. Fingerprint a SQLite database. Include indexing for faster queries.
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docs/README

      ==================
        DB Fingerprint
      ==================


-------------
  INTRO
-------------
[D]ata[B]ase [F]inger[P]rint

dbfp is a tool that will scan a sqlite database and generate a fingerprint.
The fingerprint will uniquely identify the database.
The fingerprint consists of the database schema, the sql table create statements, 
  md5 calculations, and file meta-data.
The fingerprint is stored to disk in JSON format.

The fingerprint can be used to identify unknown databases from random paths or recovered from deleted space.
The fingerprint can be used for historical comparisons to see what has changed in a new version of an application.


-------------
  FEATURES
-------------
1. Generate a fingerprint in JSON format.
2. Compare a sqlite database with a fingerprint.
3. Rip all apps from an Android phone and create fingerprints for all SQLite databases
4. Lightning fast fingerprint comparison
  a. creates an index of fingerprints
  b. query the index for quick fingerprint comparison


-------------
  USAGE
-------------

Create fingerprings from given path
find <db_files_path> -exec python dbfp.py -db {} \;

Attempt to fingerprint all files with *.db
find . -type f -name "*.db" -exec python dbfp.py -db {} \;

Attempt to fingerprint all files, recursively, from this path (no error if file not database)
find . -type f -exec python dbfp.py -db {} \;



***** ***** ***** *****
   DB Fingerprint
***** ***** ***** *****

Create fingerprint:
  dbfp.py  -db <database_file>

Create fingerprint index:
  dbfp.py  -fd <fingerprint_dir> -idx

Add fingerprint to index:
  dbfp.py  -fp <fingerprint_file> -idx (-db <database_file> | -fp <fingerprint_file>)

Compare fingerprint to a database file:
  dbfp.py  -fp <fingerprint_file> -db <database_file>

Lookup fingerprint from index:
  dbfp.py  -fd <fingerprint_dir> -fp <fingerprint_file>)

Lookup database from index:
  dbfp.py  -fd <fingerprint_dir> -db <database_file>

Lookup MD5 hash from index:
  dbfp.py  -fd <fingerprint_dir> -md5 <md5_hash_string>

Android App pull and fingerprint:
  dbfp.py -android_pull

***** ***** ***** *****

usage: dbfp.py [-h] [-db DATABASE] [-fd FPDIR] [-fp FINGERPRINT]
               [-ad ANDROID_DIR] [-dd DATA_DIR] [-an APP_NAME]
               [-av APP_VERSION] [-n NOTES] [-idx] [-md5 MD5] [-android_pull]
               [-v] [-vv] [-l]

Fingerprint a sqlite database based on its schema

optional arguments:
  -h, --help            show this help message and exit
  -db DATABASE, --database DATABASE
                        path to file to be fingerprinted
  -fd FPDIR, --fpdir FPDIR
                        path to directory of fingerprint files, compare each
                        file
  -fp FINGERPRINT, --fingerprint FINGERPRINT
                        fingerprint file to use in comparison
  -ad ANDROID_DIR, --android_dir ANDROID_DIR
                        path to a directory with android folder structure
                        sqlite files
  -dd DATA_DIR, --data_dir DATA_DIR
                        path to a directory to search for sqlite files
  -an APP_NAME, --app_name APP_NAME
  -av APP_VERSION, --app_version APP_VERSION
  -n NOTES, --notes NOTES
  -idx                  add a fingerprint to the index
  -md5 MD5              md5 hash to query the index`
  -android_pull         automated pull of applications from a physical android
                        phone
  -v, --verbose         will set logging level to INFO
  -vv, --vverbose       will set logging level to DEBUG
  -l, --logging         will supercede the -v option and send all logging to a
                        file, logging.DEBUG