Changelog spiderfoot v2.9.0 New Modules / Data Sources:
+ This release introduces five new modules and an update to sfp_sharedip to include an additional data source:
– sfp_cymon: Searches Cymon.io for potentially malicious IP addresses, subnets, domains and hostnames. Requires a freely available API key.
– sfp_censys: Searches Censys.io for information in their database about your target IPs/hosts. Censys contains information such as the Operating System, Geo-location information, open ports and more. For this you will need to register (free) for an API key.
– sfp_hunter: Searches Hunter.io for potential e-mail addresses on your target domain name. Also needs an API key, freely available (with limits).
– sfp_base64: Looks for base64-encoded strings inside URLs and fetched web content. This can be useful for sometimes identifying hidden information the author didn’t intend to make visible.
+ Enhancements / Bug fixes
– sfp_accounts will produce way less false positives as it now also checks for the queried username to be mentioned within the returned social media site content.
– sfp_names and others now use French, German and Spanish as well as English dictionaries for better word/name detection which ultimately means less false positives.
– Removed the problematic use of metapdf in favor of PyPDF2.
– Removed the inclusion of BeautifulSoup and now added it as a requirement to be installed. This should address the compatibility issues many experienced on Kali Linux.
– The Windows binary has been compiled to not include SSL libraries causing conflicts on older versions of Windows, addressing errors some were seeing when trying to run 2.8.0 on Windows 7.
– Miscellaneous tweaks and improvements to reduce crashes/errors and detect more data.
SpiderFoot is an open source intelligence automation tool. Its goal is to automate the process of gathering intelligence about a given target, which may be an IP address, domain name, hostname or network subnet.
SpiderFoot can be used offensively, i.e. as part of a black-box penetration test to gather information about the target or defensively to identify what information your organisation is freely providing for attackers to use against you.
+ Utilises a shedload of data sources; over 40 so far and counting, including SHODAN, RIPE, Whois, PasteBin, Google, SANS and more.
+ Designed for maximum data extraction; every piece of data is passed on to modules that may be interested, so that they can extract valuable information. No piece of discovered data is saved from analysis.
+ Runs on Linux and Windows. And fully open-source so you can fork it on GitHub and do whatever you want with it.
+ Web-based UI. No cumbersome CLI or Java to mess with. Easy to use, easy to navigate. Take a look through the gallery for screenshots.
+ Highly configurable. Almost every module is configurable so you can define the level of intrusiveness and functionality.
+ Modular. Each major piece of functionality is a module, written in Python. Feel free to write your own and submit them to be incorporated!
+ SQLite back-end. All scan results are stored in a local SQLite database, so you can play with your data to your heart’s content.
+ Simultaneous scans. Each footprint scan runs as its own thread, so you can perform footprinting of many different targets simultaneously.
+ So much more.. check out the documentation for more information.
tar xf tar xf spiderfoot-2.9.0-src.tar.gz
pip install netaddr PyPDF2 gexf phonenumbers stem mako cherrypy dns M2Crypto
then browse to http://127.0.0.1:5001