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Command-line tool to scan Google search results for vulnerabilities
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dorkbot execute as python script for windows compatibility Feb 25, 2019
LICENSE restructure as a package Feb 14, 2019 update documentation Feb 14, 2019 bump version Feb 25, 2019


Scan Google (or other) search results for vulnerabilities.

dorkbot is a modular command-line tool for performing vulnerability scans against sets of webpages returned by Google search queries or other supported sources. It is broken up into two sets of modules:

  • Indexers - modules that return a list of targets
  • Scanners - modules that perform a vulnerability scan against each target

Targets are stored in a local database file until they are scanned, at which point a standard JSON report is produced containing any vulnerabilities found. Indexing and scanning processes can be run separately or combined in a single command (up to one of each).


usage: [-h] [-c CONFIG] [-r DIRECTORY] [-d DATABASE] [-f]
                  [-i INDEXER] [-l] [-o INDEXER_OPTIONS] [-p SCANNER_OPTIONS]
                  [-s SCANNER]

optional arguments:
  -h, --help            show this help message and exit
  -c CONFIG, --config CONFIG
                        Configuration file
  -r DIRECTORY, --directory DIRECTORY
                        Dorkbot directory (default location of config, db,
                        tools, reports)
  -d DATABASE, --database DATABASE
                        Database file/uri
  -f, --flush           Flush table of fingerprints of previously-scanned
  -i INDEXER, --indexer INDEXER
                        Indexer module to use
  -l, --list            List targets in database
                        Indexer-specific options (opt1=val1,opt2=val2,..)
                        Scanner-specific options (opt1=val1,opt2=val2,..)
  -s SCANNER, --scanner SCANNER
                        Scanner module to use


Python 2.7.x / 3.x (cross-platform) psycopg2 (if using PostgreSQL)


As needed, dorkbot will search for tools in the following order:

  • Directory specified via relevant module option
  • Located in dorkbot's tools directory, with the subdirectory named after the tool
  • Available in the user's PATH (e.g. installed system-wide)


Create a Google Custom Search Engine and note the search engine ID, e.g. 012345678901234567891:abc12defg3h. Download either Arachni or Wapiti, unpack it into the tools directory (e.g. ~/.config/dorkbot/tools/), and rename the subdirectory to arachni or wapiti as appropriate.

$ sudo apt install phantomjs
$ ./ -i google -o engine=012345678901234567891:abc12defg3h,query="filetype:php inurl:id"
$ ./ -s arachni
$ ./ -s wapiti


A dorkbot directory is used to manage all configuration files, SQLite3 databases, tools, and reports. By default it is located at ~/.config/dorkbot/ (Linux / MacOS) or in the Application Data folder (Windows). It will honor $XDG_CONFIG_HOME / %APPDATA%, or you can force a specific directory with the --directory flag. Default file paths within this directory are as follows:

  • Dorkbot configuration file: dorkbot.ini
  • Scanner url blacklist file: blacklist.txt
  • SQLite3 database file: dorkbot.db
  • External tools directory: tools/
  • Scan report output directory: reports/

Config File

The configuration file (dorkbot.ini) can be used to prepopulate certain command-line flags.

Example dorkbot.ini:


Blacklist File

The blacklist file (blacklist.txt) is a list of regular expressions of url patterns that should not be scanned. If a target url matches any line in this file it will be skipped and removed from the database. Note: do not leave any empty lines in the file.

Example blacklist.txt:


The first line will remove any target that doesn't contain a question mark, in other words any url that doesn't contain any GET parameters to test. The second attempts to avoid login functions, and the third blacklists all target urls on

Indexer Modules


Search for targets in a Google Custom Search Engine (CSE) via custom search element.

Requirements: PhantomJS


  • engine - CSE id
  • query - search query
  • phantomjs_dir - phantomjs base directory containing bin/phantomjs (default: tools/phantomjs/)
  • domain - limit searches to specified domain


Search for targets in a Google Custom Search Engine (CSE) via JSON API.

Requirements: none


  • key - API key
  • engine - CSE id
  • query - search query
  • domain - limit searches to specified domain


Search for targets within results via



  • domain - pull all results for given domain or subdomain
  • cc_py_dir - base directory containing the file (default: tools/
  • year - limit results to data sets from given year (17 or 18, defaults to all)


Search for targets via Bing Web Search API.

Requirements: none


  • key - API key
  • query - search query


Read targets from standard input, one per line.

Requirements: none

Options: none

Scanner Modules

(general options)

These options are applicable regardless of module chosen

  • blacklist - file containing (regex) patterns to blacklist from scans (default: blacklist.txt)
  • report_dir - directory to save vulnerability report (default: reports/)
  • log - log file to append scan activity (default: prints to stdout)
  • label - friendly name field to include in vulnerability report
  • count - number of urls to scan, or -1 to scan all urls (default: -1)
  • random - scan urls in random order


Scan targets with Arachni command-line scanner.

Requirements: Arachni


  • arachni_dir - arachni base directory containing bin/arachni and bin/arachni_reporter (default: tools/arachni/)
  • checks - space-delimited list of vulnerability checks to perform (default: "active/*")
  • timeout - maximum scan time in hours:minutes:seconds (default: disabled)
  • single-thread - set browser pool and max concurrency to one each
  • throttle - maximum requests per second (default: disabled)


Scan targets with Wapiti command-line scanner.

Requirements: Wapiti


  • wapiti_dir - wapiti base directory containing bin/wapiti (default: tools/wapiti/)
  • modules - space-delimited list of modules to perform (default: "blindsql exec file permanentxss sql xss")
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