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Mentalist - Graphical Tool For Custom Wordlist Generation

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Mentalist is a graphical tool for custom wordlist generation. It utilizes common human paradigms for constructing passwords and can output the full wordlist as well as rules compatible with Hashcat and John the Ripper.

Install from Source

Prerequisites

Linux (APT package manager)
Check if Python 3 is installed by running
python3 --version
If it is not, run:
sudo apt-get update && apt-get install python3.6
Additionally, you will need setuptools and Tk:
sudo apt-get install python3-setuptools python3-tk

OS X
There are varying ways of installing Python 3 on OS X, but the easiest is to install through Homebrew.
brew update && brew install python3

Windows
If using Windows, please refer to Installing Python 3 on Windows from the Hitchhiker's Guide. It is also extremely helpful to click the Python 3 installer checkbox to add Python to your PATH.

Install Mentalist
Clone the Mentalist repository:
git clone https://github.com/sc0tfree/mentalist.git

Go into the directory:
cd mentalist

Run setup.py:
python3 setup.py install

Running Mentalist

You can now run mentalist from the shell with the command
mentalist

Future Work
  • Ability to scrape sites as an attribute in the Base Words node.
  • Add dictionaries and lists for more languages
  • Add UK post codes to Append/Prepend Nodes
  • Option to perform de-duplication of Base Words
  • Mentalist Chain file differencing



cmsPoc - A CMS Exploit Framework

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A CMS Exploit Framework.

Requirements
  • python2.7
  • Works on Linux, Windows

Usage
usage: cmspoc.py [-h]
-t TYPE -s SCRIPT -u URL

optional arguments:
-h, --help show this help message and exit
-t TYPE, --type TYPE e.g.,phpcms
-s SCRIPT, --script SCRIPT
Select script
-u URL, --url URL Input a target url

Examples
python cmspoc.py -t phpcms -s v960_sqlinject_getpasswd -u http://10.10.10.1:2500/phpcms960


Scripts
TYPESCRIPTDESCRIPTION
phpcmsv960_sqlinject_getpasswdphpcmsv9.6.0 wap模块 sql注入 获取passwd
icmsv701_sqlinject_getadminicmsv7.0.1 admincp.php sql注入 后台任意登陆
discuzv34_delete_arbitary_filesdiscuz ≤ v3.4 任意文件删除
beecmsv40_fileupload_getshellbeecms ≤ V4.0_R_20160525 文件上传漏洞


Fake Sandbox Processes (FSP) - Tool to simulate fake processes of analysis sandbox/VM software

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This small script will simulate fake processes of analysis, sandbox and/or VM software that some malware will try to avoid. You can download the original script (made by @x0rz ) in the orig directory.

You can also download my slightly optimized script in the main directory. The file is named fsp.ps1.

Script-Features
  • Some (good) spyware will stop spying on you as long as the processes run, which are created by this script.
  • Requirements: Powershell (preinstalled on Win 7 and newer)
  • Runs on every Windows since Vista
  • Tiny size
  • No CPU load
  • Easy to use
  • No network connection required

Installer-Features
  • Automatically install the script to your autostart directory
  • Extremely easy to install
  • Uninstaller to purge all files
  • NO requirements
  • Tiny size
  • Offline package
  • Automatic updater included - only if you want!

Usage:
Open the command line and paste this command (don't forget to adjust the path!):
Powershell -executionpolicy remotesigned -File "Your\Path\fsp.ps1"
After pressing ENTER you will be asked to either start or stop all processes.

Autostart
If you execute the powershell script with the above command, you will have to rerun it after every login or startup. In order to autostart the script I made an easy-to-use installer.
  • Download the fsp-installer.bat file from the release section.
  • Double-click it.
  • Now you will see this cmd window:

  • Choose "i" to start the installer.
  • Now enter "y" to start installing or "n" to abort.
  • If you entered "y" this image will now pop up:

  • Enter "y" to install the auto-updater or "n" to not install it (it'll work anyways, but it is recommended to install the updater).
You can now close the window or press any key to close it. The (un)installation is complete.

Uninstall
If you no longer want this program on your computer, you'll need the fsp-installer.bat file again. Run it and chose "u" to start the uninstallation process. Then enter "y" if you are ready to uninstall it.


If the process was successful, you'll see a confirmation screen.

Successfully tested on the following Windows versions:
  • Win 10 Professional
  • Win 8.1 Home
  • Win 7 Professional


DumpsterFire - Security Incidents In A Box!

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DumpsterFire Toolset - "Security Incidents In A Box!"

The DumpsterFire Toolset is a modular, menu-driven, cross-platform tool for building repeatable, time-delayed, distributed security events. Easily create custom event chains for Blue Team drills and sensor / alert mapping. Red Teams can create decoy incidents, distractions, and lures to support and scale their operations. Turn paper tabletop exercises into controlled "live fire" range events. Build event sequences ("narratives") to simulate realistic scenarios and generate corresponding network and filesystem artifacts.

The toolset is designed to be dynamically extensible, allowing you to create your own Fires (event modules) to add to the included collection of toolset Fires. Just write your own Fire module and drop it into the FireModules directory. The DumpsterFire toolset will auto-detect your custom Fires at startup and make them available for use.


Author
Joe Gervais (TryCatchHCF)

Why
Red Teams and Blue Teams are typically overextended. What's missing is a way to scale each team's capabilites, providing more effective Red Team activity, and more realistic (and helpful) Blue Team / Purple Team exercises. Automation to the rescue! The DumpsterFire Toolset is a cross-platform menu-driven solution that allows you to easily create custom security incidents by combining modular, chained events into a consistent narrative. Those collection of events (DumpsterFires) can then be executed as time-delayed, automated processes. (They can also be triggered immediately, of course.)
The result? While you're in a meeting or out enjoying life, your DumpsterFire is waiting for its date-time trigger to activate. On a Red Team engagement, while you're busy exploiting that exposed service on a forgotten B2B server, your cloned & time-sychronized DumpsterFires are busy lighting up the target organization's SIEM on a far-away subnet, distracting their response team. Blue Teamers can turn table-top paper exercises into "live fire" range events, with controlled, pre-approved DumpsterFire event chains to trigger sensors and alerts, and train your analysts using their actual operational environment. Purple Team operations can now execute methodical, repeatable event chains to consistently map out their sensor and alerting posture. You can generate novel scenarios to test and train your teams, getting ahead of the threat space to be prepared for security contingencies.
Ever wondered how your Blue Team would respond to Mirai bot activity on your internal network? Now you can find out! (Don't worry, the Mirai bot Fire module doesn't pivot, but it does use the same usernames & passwords to brute-force telnet sessions across the target network.)
Don’t have a Red Team but wish you had an easy way to run controlled, repeatable, customized drills against all of your SOC shift teams? Done!
Wish you could support a Red Team engagement against a remote team that’s 7 timezones away, without waking up at 3:00am? Hit that snooze button!
Ever wanted to simultaneously rickroll all of your opponents’ systems during your annual cyberwarfare exercise? "Never gonna let you down!"
See sample DumpsterFires below. And of course the Shenanigans section.

Tutorial
See my CactusCon 2017 slides (included in project). The slides are written to stand on their own, providing background, approaches, specific use cases, and more. They'll put everything in context, and also won't put you to sleep. Unless they do put you to sleep, in which case you probably needed some rest anyway, so really we all come out ahead here.

Accountability
DumpsterFire creates a date-time stamped event log so that Red- and Blue teams can coordinate and track events, correlating them to what was detected (or not detected) by your sensors, which alerts did or did not trigger, etc. It also allows teams to confirm which events were part of your operation / exercise, keeping everyone out of trouble. All date-time tracking is performed in UTC, so your global operations can be easily correlated without worrying about conversions between timezones and international date lines.
The auto-generated date-time stamped event logs also provide an effortless value add to your engagements. Generate a collection of DumpsterFires for your client engagements, tailored to their attack surfaces. At the end of your operations you can hand over the logs as a bonus Purple Team deliverable to your client for post-engagement analysis.

Overview
The DumpsterFire toolset workflow is designed to be user-friendly and robust. Everything can be done from within the menu-driven dumpsterFireFactory.py script. Launch the script and the tool will guide you as you go. You can start by browsing the existing Fire modules and saved DumpsterFires. When you're ready to create your own DumpsterFires, the tool will lead through the workflow to get the job done. Finally it will be time to ignite your DumpsterFire. After selecting the DumpsterFire of your choice, you'll review the DumpsterFire's Fire modules and settings. If everything looks good, light it up!
When you're building a DumpsterFire, after you've chosen all of the Fire modules you wish to include, the tool will loop through the list of Fires. If a Fire has options for custom settings, the tool will call that Fire's Configure() method to present you with prompts for its settings (e.g. a target network's IP address).
Once all of the Fires have been configured, you'll then be given the option to assign individual time delays to your Fires. This allows the DumpsterFire to better mimic real operations when executing its chain of events. For example, the first Fire may visit various hacking Websites, the next Fire then downloads a few common hacking tools before launching the third Fire which starts scanning the local network. If this all happened within seconds of each other, no SOC analyst is going to believe it was a human. By adding several minutes or even hours between those events, you create a more realistic chain of events.
After all of the Fires have been configured and optional individual Fire delays assigned, you'll be asked to name your DumpsterFire. Do not use spaces or odd special characterse, just stick to letters, numbers, underscores, and hyphens.
Voila! You have now created your first DumpsterFire. Time to light one up!
When you're ready to ignite a DumpsterFire, the tool will first show you the DumpsterFire's settings. If everything looks good, you'll be asked if you want to assign a date-time delay before igniting. All date-time processing is done in UTC to ensure consistent execution regardless of your DumpsterFire's location of execution. Otherwise you can decline the date-time delay and execution will begin immediately after you give final confirmation.
As the DumpsterFire executes, you'll be given regular date-time stamped feedback on each Fire's status and critical events. This not only helps you track progress, but also provides a chronological record of your DumpsterFire's activities - critical in coordinating and deconflicting your events from the general background noise that floods every SOC. You can also hand over the chronological record to your external clients after your operations are complete, as a value-added record of your activites that they can use to review their sensor and alert settings. All with no extra effort on your part.

Shenanigans
April 1st happens! So do cyber wargames or your best friend's birthday. Some circumstances call for a little extra something. Finally infiltrate your opponent's perimeter in that net wars competition? Celebrate with Shenanigans while locking in your victory! Best friend leave their screen unlocked on game night? Sharing is caring! DumpsterFire's Shenanigans let you add some flavor to your operation.
Want to open the system's default browser and stream all of that Rick Astley awesomeness? After setting their system volume to maximum? How about opening any URL you choose? Or setting the system's shell aliases to pretend the filesystem is corrupted?


Files & Directories
dumpsterFireFactory.py - Menu-driven tool for creating, configuring, scheduling, and executing DumpsterFires
FireModules/ - Directory that contains subdirectories of Fires, each subdirectory is a specific Category of Fires to keep your Fire modules organized. Fires are added to a DumpsterFire to create a chain of events and actions.
DumpsterFires/ - Directory containing your collection of DumpsterFires
igniteDumpsterFire.py - Headless script, invoked at command line with the filename of the DumpsterFire you wish to execute. Useful for igniting distributed DumpsterFires.
testFireModule.py - Utility script for unit testing the Class methods of your custom Fire modules, without the hassle of running through the entire DumpsterFire Factory process to debug. Also useful for running a single Fire to check your settings. testFireModule.py will prompt you for configuration settings were applicable.
__init__.py files - Required to make Python treat directories as containing Python packages, allows DumpsterFire toolset to find and load Fire modules.

Requirements
Python 2.7.x

Run DumpsterFire Factory
$ ./dumpsterFireFactory.py

Creating a DumpsterFire:
The menu-driven DumpsterFire Factory script guides you through each step, with context-appropriate help along the way.



Sample DumpsterFires
In our first example, we have a DumpsterFire that could be either a SOC drill or a Red Team distraction. The DumpsterFire first does a Google search for hacking tools. The next Fire opens Web sessions to various hacking Websites. Next, a following Fire downloads some common hacking tools. Then a port scan targets the subnetwork, followed by bruteforce login attempts against a single host via Telnet. The final Fire runs a series of Linux commands. Note that between each Fire, the creator of this DumpsterFire has inserted some time delays. This makes the flow of events appear more realistic.



In the next example, Purple Teamers have created a DumpsterFire to help analyze and validate their sensor and alerting configurations. This DumpsterFire runs a choreographed series of port scans, each targeting different collections of ports & services, with varying probe rates as well. They've inserted a 5 minute delay between each scanning Fire to simplify isolating the traffic associated with each scanning Fire. When they run this DumpsterFire, they'll also see date-timestamps at the beginning of each Fire to help them deconflict the Fire's network activity vs. other network events.


Customizing Your Dumpster Fires
DumpsterFire's modular design gives you flexibility to create any number of event-chain narratives. Fire modules that have configurable settings allow you to set target networks or system, etc. There are a few Fire modules, however, that give you immediate flexibility to greatly expand your DumpsterFire event sequences.
Without creating any new FireModule classes, you can use these existing "custom" Fire modules to leverage and extend your DumpsterFires:
  • FireModules/Websurfing/custom_url.py
  • FireModules/FileDownloads/download_custom_url.py
  • FireModules/OSCommand/os_linux_unix_command.py
  • FireModules/OSCommand/os_win_cmd_command.py
  • FireModules/OSCommand/os_win_powershell_script.py
  • FireModules/OSCommand/os_osx_applescript_command.py
You can add any number of these to your DumpsterFire, each with its own custom actions. For example, you could chain together a dozen 'custom_url.py' Fire modules to build a complete, tailored browsing narrative. You could then have various 'OSCommand/' Fire instances that execute system commands to further reinforce your desired narrative of events. The 'OSCommand/' Fires in particular give you incredible flexbility. Each individual Fire in your DumpsterFire event chain takes any shell commands that are appropriate for the host's OS:
Example: Linux/Unix (& OSX terminal)
find /home -name '*.bash_history' -exec cat {} ; ; echo "Never gonna give you up"> rickroll.txt ; wall rickroll.txt

Write Your Own Custom Fire Modules
DumpsterFire is ready to use out of the box, but it's real value is in how easily you can extend DumpsterFire's scenario toolchest by creating your own custom Fire modules. By creating and tailoring Fire modules to match your specific needs, you can quickly expand the types of DumpsterFire scenarios you can build and execute. Simply write your new Fire module and drop it into an existing directory under FireModules/ and the DumpsterFire toolset will automatically load it at runtime & make it available.
Want to keep your custom Fire modules completely separate in their own Category? Easy! Just create a new directory under FireModules/ and the DumpsterFire toolset will auto-detect and make it available as a new Category of Fires.
NOTE: Be sure your new directory has an empty file named __init__.py otherwise the Python package manager won't be able to find it, and DumpsterFire won't see it.



Your Fire module inherits from a class called FireModule. As a starting point, you can copy an existing Fire module. Be sure to change the filename and all classname references in the file to match your new Fire. (Update the Category path references in the class's constructor methods too, if needed.)
Required Class Methods:
Configure() - Prompts user for input, populates FireModule’s parameters
Description() - Return a string containing a description of the FireModule
GetParameters() - Returns a single string of Fire's parameters
SetParameters( string ) - Takes a single string & populates Fire's members
ActivateLogging( boolean ) - Sets flag for Fire to generate a log of its activities (great for review) NOTE: For initial release, logging to stdout is always on.
Ignite() - Executes Fire's actions

Utility Scripts
Testing Python classes can be annoying, especially when you want to unit test each of the class's methods, forcing you to slog through all the application's use cases to make sure each class method is executed in proper order. Bleh. So I've written and included a script that will properly invoke each method of your new FireModule-derived classes, enabling you to quickly churn-and-burn your way through debugging. You're welcome. :-) Also a great way to run a Fire by itself to test your settings, see what it does, etc.
At the command line, give the testFireModule.py script the relative filepath to your custom Fire module. The test script will call each of the required FireModule methods for you, in proper sequence (getting configuration prior to saving, etc.). The test script doesn't use exception handling, because Python only gives you useful errors (like pointing out that missing double-quote) when it crashes. Crash and burn your way to a successful custom Fire!


Enigma - Multiplatform Payload Dropper

SpookFlare - Meterpreter Loader Generator With Multiple Features For Bypassing Client-Side And Network-Side Countermeasures

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SpookFlare has a different perspective to bypass security measures and it gives you the opportunity to bypass the endpoint countermeasures at the client-side detection and network-side detection. SpookFlare is a loader generator for Meterpreter Reverse HTTP and HTTPS stages. SpookFlare has custom encrypter with string obfuscation and run-time code compilation features so you can bypass the countermeasures of the target systems like a boss until they “learn” the technique and behavior of SpookFlare payloads.
  • Obfuscation
  • Runtime Code Compiling
  • Source Code Encryption
  • Patched Meterpreter Stage Support
     ___ ___  ___   ___  _  __  ___ _      _   ___ ___
/ __| _ \/ _ \ / _ \| |/ / | __| | /_\ | _ \ __|
\__ \ _/ (_) | (_) | '< | _|| |__ / _ \| / _|
|___/_| \___/ \___/|_|\_\ |_| |____/_/ \_\_|_\___|

Version : 1.0
Author : Halil Dalabasmaz
WWW : artofpwn.com
Twitter : @hlldz
Github : @hlldz
Licence : Apache License 2.0
Note : Stay in shadows!

-------------------------------------------------------

[*] You can use "help" command for access help section.

spookflare > help

list : List payloads
generate : Generate payloads
exit : Exit from program

[!] Important: Use x86 listener for x86 payloads and x64 listener for x64 payloads otherwise the process will crash!

spookflare > list

SpookFlare can generate following payloads.

[*] Meterpreter Loader (.EXE) with Custom Encrypter and Custom Stub:

- Meterpreter Reverse HTTP x86/x64
- Meterpreter Reverse HTTPS x86/x64

Technical Details
https://artofpwn.com/spookflare.html

Usage Video


Phishing Catcher - Catching malicious phishing domain names using Certstream SSL certificates live stream

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Catching malicious phishing domain names using certstream SSL certificates live stream.
This is just a working PoC, feel free to contribute and tweak the code to fit your needs.
Installation
The script should work fine using Python2 or Python3.
You will need the following python packages installed: certstream, tqdm, entropy, termcolor, tld, python_Levenshtein
pip install -r requirements.txt

Usage
$ ./catch_phishing.py

Example phishing caught



Excalibur - An Eternalblue exploit payload based Powershell

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Excalibur is an Eternalblue exploit based "Powershell" for the Bashbunny project. It's purpose is to reflect on how a "simple" USB drive can execute the 7 cyber kill chain. Excalibur may be used only for demostrations purposes only, and the developers are not responsible to any misuse or illeagal usage.
What does it do?
When Excalibur gets connected to the machine, it will run the following:
  1. Trys to bypass UAC, or just get administrative rights
  2. Gets interface info (IP addresses) and build a network map inside a TXT file.
  3. Scans port 445 for the known "MS10-17" ("EternalBlue") vulnerability in every segment found.
  4. Exploits every machine and drop a shell to a remote machine.

How to?
Follow the steps here to compile a shellcode: https://github.com/vivami/MS17-010
  1. Copy payload.txt to the switch folder.
  2. Copy the "eternablblue_exploit7.py" and compile it using Pyinstaller:
  • "pip install pyinstaller"
  • "pipinstaller --onefile eternablblue_exploit7.py"
  1. Add your shellcode and the compiled exploiter into "a.zip" and copy it to the "loot" folder".
  • a.zip needs to contain a compiled, standalone eternalblue exploiter from "vivami's" repo and the shellcode.
  1. Copy the powershell script to (p_v2.ps1) to the loot folder.

TODO
  1. Add persistency in terms of add a new user account, and persistent shell.
  2. Exploit other machines and applications in the network, with the credentials added in the persistency step.
  3. Exfiltrate sensitive data from the network, outside.
  4. Bug fixes, and exploits stabilizations.

Notes
Excalibur is still in Beta, bugs are iminent.



Pentester Academy - Windows Forensics

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This course will familiarize students with all aspects of Windows forensics.By the end of this course students will be able to perform live analysis, capture volatile data, make images of media, analyze filesystems, analyze network traffic, analyze files, perform memory analysis, and analyze malware for a Windows subject on a Linux system with readily available free and open source tools.  Students will also gain an in-depth understanding of how Windows works under the covers.
Year : 2016 
Manufacturer : Pentester Academy Manufacturer 
Website : pentesteracademy.com/course?id=23 
Duration : 07:38:54 
Distribution Type : Video Tutorial 
Language : English



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Download distribution on magnet-link · 1.26 GB

wavecrack - Wavestone's web interface for password cracking with hashcat

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The homepage

A user-friendly Web interface to share an hashcat cracking box among multiple users with some pre-defined options.

Adding an hash to crack

Outline

  • This Web application can be used to launch asynchronous password cracks with hashcat.
  • The interface tries to be as user-friendly as possible and facilitates the password cracking method choice and to automate the succession of various attack modes.
  • It also displays statistics regarding the cracked passwords and allows to export the cracked password list in CSV.
  • The application is designed to be used in a multi-user environment with a strict segregation between the cracking results of different users: the user authentication can be done through an LDAP directory or basic auth.

Usage

Wavecrack can be used to do the following:
  • Add new password hashes, choose the attack mode and the crack duration
  • View the past and current cracks for your user with statistics and graphs
  • View the overall load of the platform
  • Upload a password-protected file and extract its hash
The attack modes are followed in the order they are displayed on the hash submit form.
It is also possible to stop a crack. However, every cancelation is final.
A limit to the amount of concurrent cracks can be defined in the settings in order not to reduce the current cracks performance.

Requirements

Installation

  • Install the RabbitMQ server and python-ldap requirements
$ apt-get install libsasl2-dev libldap2-dev libssl-dev rabbitmq-server
$ pip install -r requirements.txt
  • Create a cracker/app_settings.py configuration file from the cracker/app_settings.py.example file and notably edit the Mandatory settings section:
    • The path of hashcat
    • The RabbitMQ connection string: by default, the guest/guest account is used. Be sure to harden your installation
    • The path of the SQLite database
    • The path of the hashcat rules
    • The path of the wordlists
    • The LDAP parameters:
      • IP address
      • port
      • LDAP database for the users
      • Base DN
  • Initialize the local database linked in the cracker/app_settings.py configuration file
$ sqlite3 base.db < base_schema.sql
  • Start the RabbitMQ server
$ sudo service rabbitmq-server start
  • Start Celery from the application folder
$ celery worker -A cracker.celery
Finally, if you don't want to setup your own VM, you can use the Docker-based process described in the docker folder.

ooni-probe - network measurement framework aimed at detecting network interference

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OONI, the Open Observatory of Network Interference, is a global observation network which aims is to collect high quality data using open methodologies, using Free and Open Source Software (FL/OSS) to share observations and data about the various types, methods, and amounts of network tampering in the world.
ooniprobe is the first program that users run to probe their network and to collect data for the OONI project. Are you interested in testing your network for signs of surveillance and censorship? Do you want to collect data to share with others, so that you and others may better understand your network? If so, please read this document and we hope ooniprobe will help you to gather network data that will assist you with your endeavors!

Installation

macOS

You can install ooniprobe on macOS if you have installed homebrew (http://brew.sh/) with:
brew install ooniprobe

Unix systems (with pip)

Make sure you have installed the following dependencies:
  • build-essential
  • python (>=2.7)
  • python-dev
  • pip
  • libgeoip-dev
  • libdumbnet-dev
  • libpcap-dev
  • libssl-dev
  • libffi-dev
  • tor (>=0.2.5.1 to run all the tor related tests)
Optional dependencies:
  • obfs4proxy
On debian based systems this can generally be done by running:
sudo apt-get install -y build-essential libdumbnet-dev libpcap-dev libgeoip-dev libffi-dev python-dev python-pip tor libssl-dev obfs4proxy
Then you should be able to install ooniprobe by running:
sudo pip install ooniprobe
or install ooniprobe as a user:
pip install ooniprobe

Using ooniprobe

Net test is a set of measurements to assess what kind of internet censorship is occurring.
Decks are collections of ooniprobe nettests with some associated inputs.
Collector is a service used to report the results of measurements.
Test helper is a service used by a probe for successfully performing its measurements.
Bouncer is a service used to discover the addresses of test helpers and collectors.

Kali Linux 2017.3 Release - The Best Penetration Testing Distribution

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Kali Linux 2017.3 released, which includes all patches, fixes, updates, and improvements since our last release. In this release, the kernel has been updated to 4.13.10 and it includes some notable improvements:
In addition to the new kernel and all of the updates and fixes we pull from Debian, we have also updated our packages for ReaverPixieWPSBurp SuiteCuckooThe Social Engineering Toolkit, and more. Take a look at the Kali Changelog to see what else has been updated in this release, or read on to see what else is new.



New Tool Additions

Since our last release in September, we’ve added four new tools to the distribution, most of which focus on the always-lucrative open source information gathering. These new tools are not included in the default installation but after an ‘apt update’, you can check out and install the ones that interest you. We, of course, think they’re all interesting and hope you do as well.
InSpy

InSpy is a small but useful utility that performs enumeration on LinkedIn and can find people based on job title, company, or email address.
root@kali:~# apt update && apt -y install inspy
root@kali:~# inspy --empspy /usr/share/inspy/wordlists/title-list-large.txt google

InSpy 2.0.3

2017-11-14 14:04:47 53 Employees identified
2017-11-14 14:04:47 Birkan Cara Product Manager at Google
2017-11-14 14:04:47 Fuller Galipeau Google
2017-11-14 14:04:47 Catalina Alicia Esrat Account Executive at Google
2017-11-14 14:04:47 Coplan Pustell Recruiter at Google
2017-11-14 14:04:47 Kristin Suzanne Lead Recruiter at Google
2017-11-14 14:04:47 Baquero Jahan Executive Director at Google
2017-11-14 14:04:47 Jacquelline Bryan VP, Google and President of Google.org
2017-11-14 14:04:47 Icacan M. de Lange Executive Assistant at Google
...

CherryTree

The oft-requested CherryTree has now been added to Kali for all of your note-taking needs. CherryTree is very easy to use and will be familiar to you if you’ve used any of the “big-name” note organization applications.
root@kali:~# apt update && apt -y install cherrytree


Sublist3r

Sublist3r is a great application that enables you to enumerate subdomains across multiple sources at once. It has integrated the venerable SubBrute, allowing you to also brute force subdomains using a wordlist.
root@kali:~# apt update && apt -y install sublist3r
root@kali:~# sublist3r -d google.com -p 80 -e Bing

____ _ _ _ _ _____
/ ___| _ _| |__ | (_)___| |_|___ / _ __
\___ \| | | | '_ \| | / __| __| |_ \| '__|
___) | |_| | |_) | | \__ \ |_ ___) | |
|____/ \__,_|_.__/|_|_|___/\__|____/|_|

# Coded By Ahmed Aboul-Ela - @aboul3la

[-] Enumerating subdomains now for google.com
[-] Searching now in Bing..
[-] Total Unique Subdomains Found: 46
[-] Start port scan now for the following ports: 80
ads.google.com - Found open ports: 80
adwords.google.com - Found open ports: 80
analytics.google.com - Found open ports: 80
accounts.google.com - Found open ports: 80
aboutme.google.com - Found open ports: 80
adssettings.google.com - Found open ports: 80
console.cloud.google.com - Found open ports: 80
...

OSRFramework

Another excellent OSINT tool that has been added to the repos is OSRFramework, a collection of scripts that can enumerate users, domains, and more across over 200 separate services.
root@kali:~# apt update && apt -y install osrframework
root@kali:~# searchfy.py -q "dookie2000ca"

___ ____ ____ _____ _
/ _ \/ ___|| _ \| ___| __ __ _ _ __ ___ _____ _____ _ __| | __
| | | \___ \| |_) | |_ | '__/ _` | '_ ` _ \ / _ \ \ /\ / / _ \| '__| |/ /
| |_| |___) | _ <| _|| | | (_| | | | | | | __/\ V V / (_) | | | <
\___/|____/|_| \_\_| |_| \__,_|_| |_| |_|\___| \_/\_/ \___/|_| |_|\_

Version: OSRFramework 0.17.2
Created by: Felix Brezo and Yaiza Rubio, (i3visio)



searchfy.py Copyright (C) F. Brezo and Y. Rubio (i3visio) 2014-2017

This program comes with ABSOLUTELY NO WARRANTY. This is free software, and you
are welcome to redistribute it under certain conditions. For additional info,
visit https://www.gnu.org/licenses/agpl-3.0.txt

2017-11-14 14:54:52.535108 Starting search in different platform(s)... Relax!

Press to stop...

2017-11-14 14:55:04.310148 A summary of the results obtained are listed in the following table:

Sheet Name: Profiles recovered (2017-11-14_14h55m).
+---------------------------------+---------------+------------------+
| i3visio_uri | i3visio_alias | i3visio_platform |
+=================================+===============+==================+
| http://github.com/dookie2000ca | dookie2000ca | Github |
+---------------------------------+---------------+------------------+
| http://twitter.com/dookie2000ca | dookie2000ca | Twitter |
+---------------------------------+---------------+------------------+

2017-11-14 14:55:04.327954 You can find all the information collected in the following files:
./profiles.csv

2017-11-14 14:55:04.328012 Finishing execution...

Total time used: 0:00:11.792904
Average seconds/query: 11.792904 seconds

Did something go wrong? Is a platform reporting false positives? Do you need to
integrate a new one and you don't know how to start? Then, you can always place
an issue in the Github project:
https://github.com/i3visio/osrframework/issues
Note that otherwise, we won't know about it!

Massive Maltego Metamorphosis

One of our favourite applications in Kali has always been Maltego, the incredible open-source information gathering tool from Paterva, and the equally incredible Casefile. These two applications had always been separate entities (get it?) but as of late September, they are now combined into one amalgamated application that still allows you to run Maltego Community Edition and Casefile, but now it also works for those of you with Maltego Classic or Maltego XL licenses. As always, the tools perform wonderfully and look great doing it.




WSC2 - A WebSocket C2 Tool

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WSC2 is a PoC of using the WebSockets and a browser process to serve as a C2 communication channel between an agent, running on the target system, and a controller acting as the actuel C2 server.


Background information
Check this blog post to get some context and insight on the developpment of this tool:
Using WebSockets and IE/Edge for C2 communications

Architecture
WSC2 is composed of:
  • a controller, written in Python, which acts as the C2 server
  • an agent running on the target system, delivered to the target system via various initial stagers
  • various flavors of initial stages (created from the controller interface) used for the initial compromission of the target system.

Features
WSC2 main features:
  • Various stager (powershell one liner, various JScript file) - this is not limited, you can easily come up with your own stagers, check the templates folder to get an idea
  • Interactive shell (with environment persistency)
  • File transfer back and forth between the agent and C2
  • Multiple agents support

Installation & Configuration
Installation is pretty straight forward:
  • Git clone this repository: git clone https://github.com/Arno0x/WSC2 WSC2
  • cd into the WSC2 folder: cd WSC2
  • Install the python dependencies: pip install -r requirements.txt
  • Give the execution rights to the main script: chmod +x wsc2.py
Check the configuration file config.py and ensure the default config fits your needs.
Start the controller by typing: ./wsc2.py.

Compiling your own agent
The JScript agent (stager 'jscript1') doesn't need to be compiled.
The 'jscript2', 'jscript3' and 'psoneliner' stagers are based on a .Net assembly DLL that you can choose to build on your own/modify, based on the source code provided.
Although it is perfectly OK to use the provided wsc2.dll, you can very easily compile your own agent, from the source code provided. You'll need Visual Studio installed.
Create a .Net (Visual C#) Class Libray projet. Add the wsc2Agent.cs source file as the main source code file.
Add the following references to your project:
  1. Microsoft HTML Object Library (MSHTML)
  2. Microsoft Internet Controls (SHDocVw)
Build !

Author: Arno0x0x - @Arno0x0x

IP-Biter - The Hacker-friendly E-Mail Tracking Framework

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IP-Biter is an open source, easy to deploy, tracking framework that generate high configurables and uniques tracking images and links to embed in e-mails, sites or chat systems and visualize, in an hacker-friendly dashboard, high detailed reports of the tracked users who visualize the image or open the links.

Features
  • Very high configurable tracking image generation
  • Tracking links generation
  • Tracking hided and not recognizable from the target point of view
  • Integrated Dashboard
  • Self-tracking prevention
  • Possibility to stop and start the tracking at any time
  • Possibility to hide the Dashboard and protect its access with a password
  • Live tracking reports from the Dashboard
  • Tracking reports live delivered to a configurable mail address
  • Different IP analysis services
  • User-Agent analysis service
  • Integrate URL shortening service
  • AllInOne PHP file
  • No need for a Database
  • Open Source
...and many many more!
Give it a try!

Getting Started

Access the Dashboard
  1. Access the dashboard through ipb.php?op=$dashboardPage (or through ipb.php if $dashboardPage=='')
    • If $dashboardPageSecret!='' then a login page will appear asking for the $dashboardPageSecret value

Create a new configuration
  1. When the dashboard is opened without parameters, a new configuration is created
    • Another empty new configuration can be generate clicking the "New" button
  2. Configure the tracking image and the advanced setting if needed
    • It is possible to left the original image url empty. In this case an empty image will be used.
  3. Add tracking links if needed
    • It is possible to left the original link empty. In this case the link will generate a 404 page.
  4. Save the configuration
  5. Distribute the generated image or the links to start the tracking
    • You can click the copy button and paste in a html rich email editor like gmail
    • NOTE: If you try to open the generated image or links but have in the same browser the dashboard page opened and loaded, your request will not be tracked (self-tracking prevention feature)

Load an existing configuration
  1. When the dashboard is opened with the parameter "uuid", the associated configuration is loaded
    • Another configuration can be loaded pasting the "Track UUID" in the dashboard relative field and clicking the "Load" button
  2. The reports will be automatically visualized in the "Tracking Reports" section of the dashboard

Security Notes
  • Change the folders name and the dashboard page in the configuration section in order to improve the security
  • Add the following lines to the .htaccess file in order to deny the access to the "configs" and "reports" folders:
DirectoryIndex ipb.php
<IfModule mod_rewrite.c>
RewriteEngine On
RewriteRule ^(configs/|reports/) - [F]
</IfModule>

Live DEMO
Have a look at the DEMO (notifications limited at 50 mail/day and 1h/day downtime expected)


sAINT - A Spyware Generator for Windows systems written in Java

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(s)AINT is a Spyware Generator for Windows systems written in Java.

Features
  • Keylogger
  • Take Screenshot
  • Webcam Capture
  • Persistence

Tested On
Kali Linux - ROLLING EDITION

How To Use
# Install dependencies (you need Maven and JDK 8 package installed)
$ apt install maven default-jdk default-jre openjdk-8-jdk openjdk-8-jre -y

# To generate a .EXE using launch4j are necessary the following packages
$ apt install zlib1g-dev libncurses5-dev lib32z1 lib32ncurses5 -y

# Clone this repository
$ git clone https://github.com/tiagorlampert/sAINT.git

# Go into the repository
$ cd sAINT

# Install and configure Maven libraries
$ sudo chmod +x configure.sh
$ ./configure.sh

# Run
$ java -jar sAINT.jar
E-mail will be sent when it reaches the specified number of characters. Optionally you can enable Screenshot, Webcam Captureand Persistence.

Screenshot

Maven dependencies


Generate spyware



Run

Install Java JRE 8


Run .EXE


or Run .JAR


Data

Local


E-mail


How to uninstall
To uninstall run UNINSTALL.bat with administrative permissions.



OpenWPM - Web privacy measurement framework

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Web Privacy Measurement is the observation of websites and serves to detect, characterize and quantify privacy-impacting behaviors. Applications of Web Privacy Measurement include the detection of price discrimination, targeted news articles and new forms of browser fingerprinting. Although originally focused solely on privacy violations, WPM now encompasses measuring security violations on the web as well.
For these studies to be truly large-scale and repeatable, creating an automated measurement platform is necessary. At least within the academic literature, measurement infrastructures in the field of WPM have been largely one-off and do not comprehensively address the engineering challenges within this realm.
OpenWPM, a flexible, stable, scalable and general web measurement platform, is our solution to this infrastructure vacuum. This tutorial shows how to get started with OpenWPM, gives an overview of its general functionality and lists some key engineering challenges which are still being solved. We hope that this tool will enable other researchers to perform WPM studies and welcome future collaboration.

Installation

OpenWPM has been developed and tested on Ubuntu 14.04/16.04. An installation script, install.sh is included to install both the system and python dependencies automatically. A few of the python dependencies require specific versions, so you should install the dependencies in a virtual environment if you're installing a shared machine. If you plan to develop OpenWPM's instrumentation extension or run tests you will also need to install the development dependencies included in install-dev.sh.
It is likely that OpenWPM will work on platforms other than Ubuntu, however we do not officially support anything else. For pointers on alternative platform support see the wiki.

Quick Start

Once installed, it is very easy to run a quick test of OpenWPM. Check out demo.py for an example. This will use the default setting specified in automation/default_manager_params.json and automation/default_browser_params.json, with the exception of the changes specified in demo.py.

Instrumentation and Data Access

OpenWPM provides several instrumentation modules which can be enabled independently of each other for each crawl. With the exception of response body content, all instrumentation saves to a SQLite database specified by manager_params['database_name'] in the main output directory. Response bodies are saved to content.ldb. The SQLite schema specified by: automation/schema.sql, instrumentation may specify additional tables necessary for their measurement data (see extension tables).
  • HTTP Request and Response Headers, redirects, and POST request bodies
    • Set browser_params['http_instrument'] = True
    • Data is saved to the http_requestshttp_responses, and http_redirects tables.
      • http_requests schema documentation
      • channel_id can be used to link a request saved in the http_requests table to its corresponding response in the http_responses table.
      • channel_id can also be used to link a request to the subsequent request that results after an HTTP redirect (3XX response). Use the http_redirects table, which includes a mapping between old_channel_id, the channel_id of the HTTP request that resulted in a 3XX response, and new_channel_id, the HTTP request that resulted from that redirect.
    • OCSP POST request bodies are not recorded
    • Note: request and response headers for cached content are also saved, with the exception of images. See: Bug 634073.
  • Javascript Calls
    • Records all method calls (with arguments) and property accesses for APIs of potential fingerprinting interest:
      • HTML5 Canvas
      • HTML5 WebRTC
      • HTML5 Audio
      • Plugin access (via navigator.plugins)
      • MIMEType access (via navigator.mimeTypes)
      • window.Storagewindow.localStoragewindow.sessionStorage, and window.name access.
      • Navigator properties (e.g. appCodeNameoscpuuserAgent, ...)
      • Window properties (via window.screen)
    • Set browser_params['js_instrument'] = True
    • Data is saved to the javascript table.
  • Response body content
    • Saves all files encountered during the crawl to a LevelDB database de-duplicated by the md5 hash of the content.
    • Set browser_params['save_all_content'] = True
    • The content_hash column of the http_responses table contains the md5 hash for each script, and can be used to do content lookups in the LevelDB content database.
    • NOTE: this instrumentation may lead to performance issues when a large number of browsers are in use.
    • Set browser_params['save_javascript'] = True to save only Javascript files. This will lessen the performance impact of this instrumentation when a large number of browsers are used in parallel.
  • Flash Cookies
    • Recorded by scanning the respective Flash directories after each page visit.
    • To enable: call the CommandSequence::dump_flash_cookies command after a page visit. Note that calling this command will close the current tab before recording the cookie changes.
    • Data is saved to the flash_cookies table.
    • NOTE: Flash cookies are shared across browsers, so this instrumentation will not correctly attribute flash cookie changes if more than 1 browser is running on the machine.
  • Cookie Access (Experimental -- Needs tests)
    • Set browser_params['cookie_instrument'] = True
    • Data is saved to the javascript_cookies table.
    • Will record cookies set both by Javascript and via HTTP Responses
  • Content Policy Calls (Experimental -- Needs tests)
    • Set browser_params['cp_instrument'] = True
    • Data is saved to the content_policy table.
    • Provides additional information about what caused a request and what it's for
    • NOTE: This instrumentation is largely unchanged since it was ported from FourthParty, and is not linked to any other instrumentation tables.
  • Cookie Access (Alternate)
    • Recorded by scanning the cookies.sqlite database in the Firefox profile directory.
    • Should contain both cookies added by Javascript and by HTTP Responses
    • To enable: call the CommandSequence::dump_profile_cookies command after a page visit. Note that calling this command will close the current tab before recording the cookie changes.
    • Data is saved to the profile_cookies table
  • Log Files
    • Stored in the directory specified by manager_params['data_directory'].
    • Name specified by manager_params['log_file'].
  • Browser Profile
    • Contains cookies, Flash objects, and so on that are dumped after a crawl is finished
    • Automatically saved when the platform closes or crashes by specifying browser_params['profile_archive_dir'].
    • Save on-demand with the CommandSequence::dump_profile command.
  • Rendered Page Source
    • Save the top-level frame's rendered source with the CommandSequence::dump_page_source command.
    • Save the full rendered source (including all nested iframes) with the CommandSequence::recursive_dump_page_sourcecommand.
      • The page source is saved in the following nested json structure:
      {
      'document_url': "http://example.com",
      'source': "<html> ... </html>",
      'iframes': {
      'frame_1': {'document_url': ...,
      'source': ...,
      'iframes: { ... }},
      'frame_2': {'document_url': ...,
      'source': ...,
      'iframes: { ... }},
      'frame_3': { ... }
      }
      }
  • Screenshots
    • Selenium 3 can be used to screenshot an individual element. None of the built-in commands offer this functionality, but you can use it when writing your own. See the Selenium documentation.
    • Viewport screenshots (i.e. a screenshot of the portion of the website visible in the browser's window) are available with the CommandSequence::save_screenshot command.
    • Full-page screenshots (i.e. a screenshot of the entire rendered DOM) are available with the CommandSequence::screenshot_full_page command.
      • This functionality is not yet supported by Selenium/geckodriver, though it is planned. We produce screenshots by using JS to scroll the page and take a viewport screenshot at each location. This method will save the parts and a stitched version in the screenshot_path.
      • Since the screenshots are stitched they have some limitations:
        • On the area of the page present when the command is called will be captured. Sites which dynamically expand when scrolled (i.e., infinite scroll) will only go as far as the original height.
        • We only scroll vertically, so pages that are wider than the viewport will be clipped.
        • In geckodriver v0.15 doing any scrolling (or having devtools open) seems to break element-only screenshots. So using this command will cause any future element-only screenshots to be misaligned.

Build and Deploy Your First Decentralized App with Ethereum [FREE]

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What Will I Learn?
  • Create Smart Contracts in Solidity
  • Build User Interfaces with Web3
  • Deploy a Smart Contract
  • Work in the TestRPC Environment
  • Work in the Ropsten Test Network
Requirements
  • Basic Understanding of JavaScript
  • Basic Understanding of the Blockchain
  • Basic Understanding of HTML & CSS
Description Welcome to this 100% free course where you're going to learn how to create and deploy Ethereum smart contracts.
Smart contracts allow you to create decentralized apps that can harness the power of the blockchain for a wide variety of use cases.
In this course, I'm assuming you have no prior experience with creating smart contracts. You're going to go from absolute beginner to an intermediate understanding in a very fast amount of time.
The bulk of this course is going to be very hands-on with very little slides. I think we all learn best by doing and not watching powerpoint.
Let's get started!
Who is the target audience?
  • Web Developer
  • App Developer



CryKeX - Linux Memory Cryptographic Keys Extractor

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Properties:
  • Cross-platform
  • Minimalism
  • Simplicity
  • Interactivity
  • Compatibility/Portability
  • Application Independable
  • Process Wrapping
  • Process Injection
Dependencies:
  • Unix - should work on any Unix-based OS
    • BASH - the whole script
    • root privileges (optional)
Limitations:
  • AES and RSA keys only
  • Fails most of the time for Firefox browser
  • Won't work for disk encryption (LUKS) and PGP/GPG
  • Needs proper user privileges and memory authorizations

How it works

Some work has been already published regarding the subject of cryptograhic keys security within DRAM. Basically, we need to find something that looks like a key (entropic and specific length) and then confirm its nature by analyzing the memory structure around it (C data types).
The idea is to dump live memory of a process and use those techniques in order to find probable keys since, memory mapping doesn't change. Thanks-fully, tools exist for that purpose.
The script is not only capable of injecting into already running processes, but also wrapping new ones, by launching them separately and injecting shortly afterwards. This makes it capable of dumping keys from almost any process/binary on the system.
Of course, accessing a memory is limited by kernel, which means that you will still require privileges for a process.
Linux disk ecnryption (LUKS) uses anti-forensic technique in order to mitigate such issue, however, extracting keys from a whole memory is still possible.
Firefox browser uses somehow similar memory management, thus seems not to be affected.
Same goes for PGP/GPG.

HowTo

Installing dependencies:
sudo apt install gdb aeskeyfind rsakeyfind ||echo'have you heard about source compiling?'
An interactive example for OpenSSL AES keys:
openssl aes-128-ecb -nosalt -out testAES.enc
Enter a password twice, then some text and before terminating:
CryKeX.sh openssl
Finally, press Ctrl+D 3 times and check the result.
OpenSSL RSA keys:
openssl genrsa -des3 -out testRSA.pem 2048
When prompted for passphrase:
CryKeX.sh openssl
Verify:
openssl rsa -noout -text -in testRSA.pem
Let's extract keys from SSH:
echo'Ciphers aes256-gcm@openssh.com'>> /etc/ssh/sshd_config
ssh user@server
CryKeX.sh ssh
From OpenVPN:
echo'cipher AES-256-CBC'>> /etc/openvpn/server.conf
openvpn yourConf.ovpn
sudo CryKeX.sh openvpn
TrueCrypt/VeraCrypt is also affected: Select "veracrypt" file in VeraCrypt, mount with password "pass" and:
sudo CryKeX.sh veracrypt
Chromium-based browsers (thanks Google):
CryKeX.sh chromium
CryKeX.sh google-chrome
Despite Firefox not being explicitly affected, Tor Browser Bundle is still susceptible due to tunneling:
CryKeX.sh tor
As said, you can also wrap processes:
apt install libssl-dev
gcc -lcrypto cipher.c -o cipher
CryKeX.sh cipher
wrap
cipher

aletheia - Image steganalysis using state-of-the-art machine learning techniques

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    Aletheia is a steganalysis tool for the detection of hidden messages in images.
    First you need to clone the GIT repository:
    $ git clone https://github.com/daniellerch/aletheia.git
    Inside the Aletheia directory you will find a requirements file for installing Python dependencies with pip:
    $ sudo pip install -r requirements.txt 
    Aletheia uses Octave so you need to install it and some dependencies. You will find the dependencies in the octave-requirements.txt file. In Debian based Linux distributions you can install the dependencies with the following commands. For different distros you can deduce the appropriate ones.
    $ sudo apt-get install octave octave-image
    After that, you can execute Aletheia with:
    $ ./aletheia.py 

    ./aletheia.py <command>

    COMMANDS:

    Attacks to LSB replacement:
    - spa: Sample Pairs Analysis.
    - rs: RS attack.

    Feature extractors:
    - srm: Full Spatial Rich Models.
    - srmq1: Spatial Rich Models with fixed quantization q=1c.

    Embedding simulators:
    - hugo-sim: Embedding using HUGO simulator.
    - wow-sim: Embedding using WOW simulator.
    - s-uniward-sim: Embedding using S-UNIWARD simulator.
    - hill-sim: Embedding using HILL simulator.

    Model training:
    - esvm: Ensemble of Support Vector Machines.
    - e4s: Ensemble Classifiers for Steganalysis.

    Statistical attacks to LSB replacement

    LSB replacement staganographic methods, that is, methods that hide information replacing the least significant bit of each pixel, are flawed. Aletheia implements two attacks to these methods: the Sample Pairs Analysis (SPA) and the RS attack.
    To execute the SPA attack to an included image with LSB replacement data hidden, use the following command:
    $./aletheia.py spa sample_images/lena_lsbr.png 
    Hiden data found in channel R 0.0930809062336
    Hiden data found in channel G 0.0923858529528
    Hiden data found in channel B 0.115466382367
    The command used to perform the RS attack is similar:
    $./aletheia.py rs sample_images/lena_lsbr.png 
    Hiden data found in channel R 0.215602586771
    Hiden data found in channel G 0.210351910548
    Hiden data found in channel B 0.217878287806
    In both cases the results provides an estimation of the embedding rate.

    Machine Learning based attacks

    Most of the state of the art methods in Steganography use some kind of LSB matching. These methods are verify difficult to detect and there is not enough with simple statistical attacks. We need to use machine learning.
    To use machine learning we need to prepare a training dataset, used to train our classifier. For this example we will use a database of grayscale images called Bossbase.
    $ wget http://dde.binghamton.edu/download/ImageDB/BOSSbase_1.01.zip
    $ unzip BOSSbase_1.01.zip
    We are going to build a detector for the HILL algorithm with payload 0.40. So we need to prepare a set of images with data hidden using this algorithm. The following command embeds information into all the images downloaded:
    $ ./aletheia.py hill-sim bossbase 0.40 bossbase_hill040 
    With all the images prepared we need to extract features that can be processes by a machine learning algorithm. Aletheia provides different feature extractors, in this case we will use well known Rich Models. The following commands save the features into two files, on file for cover images and one file for stego images.
    $ ./aletheia.py srm bossbase bossbase.fea 
    $ ./aletheia.py srm bossbase_hill040 bossbase_hill040.fea
    Now, we can train the classifier. Aletheia provides different classifiers, in this case we will use Ensemble Classifiers:
    $ ./aletheia.py e4s bossbase.fea bossbase_hill040.fea hill040.model
    Validation score: 73.0
    As a results, we obtain the score using a validation set (a small subset not used during training). The output is the file "hill040.model", so we can use this for future classifications.
    Finally, we can classifiy an image:
    $ ./aletheia.py e4s-predict hill040.model srm my_test_image.png
    Stego, probability: 0.81

    ratched - Transparent Man-in-the-Middle TLS proxy intended

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    Image result for mitm
    ratched is a Man-in-the-Middle (MitM) proxy that specifically intercepts TLS connections. It is intended to be used in conjunction with the Linux iptabes REDIRECT target; all connections that should be intercepted can be redirected to the local ratched port. Through the SO_ORIGINAL_DST sockopt, ratched can determine the intended destination (before iptables packet mangling) and tries to establish a connection to the original target.
    The thing that sets it apart from other MitM software is the following:
    1. ratched does not intercept traffic indiscriminately. In particular, it first waits for the TLS client to send its ClientHello so that ratched can parse it and decide by the Server Name Indication TLS extension (SNI) if the target should be intercepted or not. This is particularly useful when you have virtual hosting, but only want to intercept connections to a specific hostname.
    2. ratched is not intended to sniff passwords, but only dumps the traffic into a PCAPNG file. The PCAPNG file format was chosen because it allows for annotation of connections with comments (in particular, which hostname was indicated in the SNI extension) and also allows name resolution information to be embedded in the capture file (again, to map the target IP address to the SNI extension's hostname)

    Setup

    Once ratched is listening on the routing machine (in the example, on port 9999), simply add an iptables entry that specifies what traffic you want to capture. For example, to intercept everything from 192.168.1.7 that tries to reach port 443, use:
    iptables -t nat -A PREROUTING -p tcp -s 192.168.1.7 --dport 443 -j REDIRECT --to-ports 9999
    In order to intercept everything that goes to 443, simply do:
    iptables -t nat -A PREROUTING -p tcp --dport 443 -j REDIRECT --to-ports 9999

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