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Showing posts with label Fingerprint. Show all posts
Showing posts with label Fingerprint. Show all posts

Operative Framework v1.0b - Fingerprint Framework



This is a framework based on fingerprint action, this tool is used for get information on a website or a enterprise target with multiple modules (Viadeo search, Linkedin search, Reverse email whois, Reverse ip whois, SQL file forensics ...)

Dependency & launching
  • pip install -r requirements.txt
  • python operative.py

Youtube

Campaign
  • You can start a (gathering/fingerprinting) campaign with :campaign command.
  • Update a value of YOURWEBSITE.COM / ENTERPRISE_NAME in config.json file.
  • You can add a module process for a customized campaign.

Core Modules
  • core/modules/cms_gathering
  • core/modules/domain_search
  • core/modules/email_to_domain
  • core/modules/https_gathering
  • core/modules/linkedin_search
  • core/modules/reverse_ipdomain
  • core/modules/search_db
  • core/modules/waf_gathering
  • core/modules/whois_domain
  • core/modules/generate_email
  • core/modules/viadeo_search
  • core/modules/file_common
  • core/modules/get_websiteurl
  • core/modules/getform_data
  • core/modules/subdomain_search
  • core/modules/vhost_IPchecker
  • core/modules/tools_suggester
  • core/modules/metatag_look
  • core/modules/header_retrieval

SQL File forensics
  • import database in core/dbs/
  • read table
  • read columns
  • search information with pattern

Write module
For write module look core/modules/sample_module class


mwebfp - Massive Web Fingerprinter

The "LowNoiseHG (LNHG) Massive Web Fingerprinter" ("mwebfp" from now on) was conceived in July 2013 after realizing the usefulness of webserver screenshots to pentesters, during an engagement with large external or internal IP address ranges, as a quick means of identification of critical assets, easily-exploitable services, forgotten/outdated servers and basic network architecture knowledge of the target.

Description

The basic operation of mwebfp consists of the processing of an input (targets and TCP ports) that is then used to identify open web server ports with the help of a powerful portscanner (nmap). All ports found open are then analyzed (on HTTP and HTTPS) and all relevant webserver information is recorded, as well as a screenshot of the rendered webpage (as if it is seen from a broswer).

Special Features

  • Input
    • Target(s) can be IP address(es), IP address range(s), server name(s), etc.
    • Target(s) can be provided directly on the command-line or on a file
  • Port Definition
    • Default ports are 80 (HTTP) and 443 (HTTPS), but any port can be easily configured at runtime
  • Output
    • All output files and related support files for the scan are saved on a directory configured at runtime by the user
    • Currently, mwebfp exports results on a CSV file (Easily usable on MS Excel) only
  • Virtual Hosts
    • If requested at runtime, mwebfp will find all virutally hosted domains and webpages for the target server
  • Webserver Screenshots
    • If requested at runtime, mwebfp will grab screenshots of all found web pages (Graphical UI under Linux is required)

Parameters

# LowNoiseHG Massive Web Fingerprinter
# by F4Lc0N - LNHG - USA/Colombia
#
# Thanks to ET, c4an, Th3R3g3nt, ch0ks and ElJeffe311
# for inspiration, ideas and debugging/beta-testing help.

usage: mwebfp.py [-h]
[-i INPUT_RANGE | -n SERVER_NAME | -f INPUT_FILE | -r]
[-p HTTP_PORTS] [-s HTTPS_PORTS] [-o OUTPUT_DIR]
[-t {HTML,XLS,CSV,XML}] [-v {yes,no}] [-w {yes,no}]

optional arguments:
-h, --help show this help message and exit
-i INPUT_RANGE, --input-range INPUT_RANGE
input IP CIDR range
-n SERVER_NAME, --server-name SERVER_NAME
name of server (DNS name)
-f INPUT_FILE, --input-file INPUT_FILE
input file containing IP addresses and/or IP ranges
-r, --recover recover/continue previous process
-p HTTP_PORTS, --http-ports HTTP_PORTS
TCP HTTP ports (Default: 80/tcp)
-s HTTPS_PORTS, --https-ports HTTPS_PORTS
TCP HTTPS ports (Default: 443/tcp)
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
working directory
-t {HTML,XLS,CSV,XML}, --output-format {HTML,XLS,CSV,XML}
output report format (Default: HTML)
-v {yes,no}, --vhosts {yes,no}
choice of processing vhosts for each IP address
(Default: no)
-w {yes,no}, --web-screenshots {yes,no}
choice of taking web schreenshots (Default: no)


[BlindElephant] Web Application Fingerprinting


 During Black Hat USA 2010, Patrick Thomas presented a new web application fingerprinting tool called Blind Elephant.

BlindElephant %E2%80%93 Web Application Fingerprinting

The BlindElephant Web Application Finger-printer attempts to discover the version of a (known) web application by comparing static files at known locations against precomputed hashes for versions of those files in all all available releases. The technique is fast, low-bandwidth, non-invasive, generic, and highly automatically.

BlindElephant works via a new trendy technique of fetching static elements of the web app such as .js, .css, and other core files then running a check sum to compare sizes of those files from released versions.

BlindElephant is available via SVN here

[SQL Fingerprint] Christmas Release


Microsoft SQL Server fingerprinting can be a time consuming process, because it involves trial and error methods to determine the exact version. Intentionally inserting an invalid input to obtain a typical error message or using certain alphabets that are unique for certain server are two of the many ways to possibly determine the version, but most of them require authentication, permissions and/or privileges on Microsoft SQL Server to succeed. 

Instead, ESF.pl uses a combination of crafted packets for SQL Server Resolution Protocol (SSRP) and Tabular Data Stream Protocol (TDS) (protocols natively used by Microsoft SQL Server) to accurately perform version fingerprinting and determine the exact Microsoft SQL Server version. ESF.pl also applies a sophisticated Scoring Algorithm Mechanism (Powered by Exploit Next Generation++ Technology), which is a much more reliable technique to determine the Microsoft SQL Server version. It is a tool intended to be used by: 




This version is a completely rewritten version in Perl, making ESF.pl much more portable than the previous binary

version (Win32), and its original purpose is to be used as a tool to perform automated penetration test. This version also includes the followingMicrosoft SQL Server versions to its fingerprint database:  

        • Microsoft SQL Server 2012 SP1 (CU1)
• Microsoft SQL Server 2012 SP1
• Microsoft SQL Server 2012 SP1 CTP4
• Microsoft SQL Server 2012 SP1 CTP3
• Microsoft SQL Server 2012 SP0 (CU4)
• Microsoft SQL Server 2012 SP0 (MS12-070)
• Microsoft SQL Server 2012 SP0 (CU3)
• Microsoft SQL Server 2012 SP0 (CU2)
• Microsoft SQL Server 2012 SP0 (CU1)
• Microsoft SQL Server 2012 SP0 (MS12-070)
• Microsoft SQL Server 2012 SP0 (KB2685308)
• Microsoft SQL Server 2012 RTM

Download: http://code.google.com
Source: http://adf.ly/146C04

[NetSleuth] Open source Network Forensics And Analysis Tools

NetSleuth-Offline-Varied-2
NetSleuth identifies and fingerprints network devices by silent network monitoring or by processing data from PCAP files.

NetSleuth is an opensource network forensics and analysis tool, designed for triage in incident response situations. It can identify and fingerprint network hosts and devices from pcap files captured from Ethernet or WiFi data (from tools like Kismet).
It also includes a live mode, silently identifying hosts and devices without needing to send any packets or put the network adapters into promiscuous mode ("silent portscanning").
NetSleuth is a free network monitoring, cyber security and network forensics analysis (NFAT) tool that provides the following features:
  • An easy realtime overview of what devices and what people are connected to any WiFi or Ethernet network.
  • Free. The tool can be downloaded for free, and the source code is available under the GPL.
  • Simple and cost effective. No requirement for hardware or reconfiguration of networks.
  • “Silent portscanning” and undetectable network monitoring on WiFi and wired networks.
  • Automatic identification of a vast array of device types, including smartphones, tablets, gaming consoles, printers, routers, desktops and more.
  • Offline analysis of pcap files, from tools like Kismet or tcpdump, to aid in intrusion response and network forensics.