e or password.

⦿ Implement a data protection program at your organization that combines user education around data security best practices that will help prevent data loss due to spear-phishing attacks. Request for advanced phishing attack simulation against employees frequently and not the generic ones that get generated with easy to identify attacks. For midsize to larger corporations, data loss prevention software should be installed to protect sensitive data from unauthorized access or egress, even if a user falls for a phishing scam.
See Also: Hacking stories – Operation Aurora: When China hacked Google
Explore our Store: You can find Apparel & Mugs about Hacking and especially for Offensive Security.
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The post Not all Phishing attack types can be protected using software solutions first appeared on Black Hat Ethical Hacking.

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SharpML - Machine Learning Network Share Password Hunting Toolkit
http://www.kitploit.com/2021/09/sharpml-machine-learning-network-share.html

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SharpML is a proof of concept (https://www.kitploit.com/search/label/Proof%20Of%20Concept) file share data mining tool using Machine Learning (https://www.kitploit.com/search/label/Machine%20Learning) in Python and C#. The tool is discussed in more detail on our blog here (https://blog.hunniccyber.com/password-hunting-with-ml-in-active-directory/index.html), but is summarised below also: SharpML is C# and Python based tool that performs a number of operations with a view to mining file shares, querying Active Directory (https://www.kitploit.com/search/label/Active%20Directory) for users, dropping an ML model and associated rules, perfoming Active Directory authentication (https://www.kitploit.com/search/label/Authentication) checks, with a view to automating the process of hunting for passwords in file shares by feeding the mined data into the ML model.
The ML model is written in Python, and has been developed using a custom algorithm to identify likelyhoods of passwords. The model has been compiled with PyInstaller and sits as resource file in the C# wrapper, which interops between itself, the data and the model. The program logic can be seen below:

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Currently it allows for a single file share to be assessed. You will need to have read access to the file share you are targeting, after which the tool will perform its activities mostly autonomously. There a compiled release in the release section, and it is to be noted that this tool is currently a PoC and subject to numerous improvements.
Usage:
cmd.exe SharpML.exe -u \\fileshare\d$ ">C:\> SharpML.exe -u \\fileshare\d$
Cobalt Strike execute-assembly SharpML.exe -u \\fileshare\d$ ">> execute-assembly SharpML.exe -u \\fileshare\d$

Authors
Marco Valentini Tom Kallo
To Do
When SharpML is run it will attempt to verify all users that it finds. If a restrictive domain lockout policy exits, it may attempt to verify users multiple times and lock the account out in event of multiple failed authentications Some file size limitations need to be implemented in order for larger text based files not to cause a bottle neck when copying the raw data Select the option of running multiple file shares simultaneously. By implementing an automatic share finder, allow SharpML to be completely autonomous and scour the whole network Improve some program logic, including further options such as the choice of cehcking against 10,000 most common passwords (https://www.kitploit.com/search/label/Common%20Passwords) or not

Download SharpML (https://github.com/HunnicCyber/SharpML)

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Why it’s Important to Find and Fix even Non-Critical Bugs?

As a developer, I’ve encountered these kinds of bugs regularly in my programming life, and I’m sure you do too. Sadly, most companies…Continue reading on Level Up Coding »
Read more...

Expect The Unexpected: Discovering fresh ZeroDay for Bounty

Special program announced anyone who find a vulnerability in their scope of IP addresses will be rewarded a enormous bountyContinue reading on Medium »
Read more...

KitPloit - PenTest Tools!
SharpML - Machine Learning Network Share Password Hunting Toolkit

http://2.bp.blogspot.com/-bnswL8b17XE/YUOtLIMkM8I/AAAAAAAAuxA/H9jWrcQoCV03t652i677JpvyBFl1gqvFQCK4BGAYYCw/w640-h400/SharpML_1_sharpml_logic-785687.png
SharpML is a proof of concept file share data mining tool using Machine Learning in Python and C#.

The tool is discussed in more detail on our blog here, but is summarised below also:

SharpML is C# and Python based tool that performs a number of operations with a view to mining file shares, querying Active Directory for users, dropping an ML model and associated rules, perfoming Active Directory authentication checks, with a view to automating the process of hunting for passwords in file shares by feeding the mined data into the ML model.
The ML model is written in Python, and has been developed using a custom algorithm to identify likelyhoods of passwords. The model has been compiled with PyInstaller and sits as resource file in the C# wrapper, which interops between itself, the data and the model. The program logic can be seen below:

http://2.bp.blogspot.com/-bnswL8b17XE/YUOtLIMkM8I/AAAAAAAAuxA/H9jWrcQoCV03t652i677JpvyBFl1gqvFQCK4BGAYYCw/w640-h400/SharpML_1_sharpml_logic-785687.png

Currently it allows for a single file share to be assessed.

You will need to have read access to the file share you are targeting, after which the tool will perform its activities mostly autonomously.

There a compiled release in the release section, and it is to be noted that this tool is currently a PoC and subject to numerous improvements.

Usage:

cmd.exe

C:\> SharpML.exe -u \\fileshare\d$


Cobalt Strike

> execute-assembly SharpML.exe -u \\fileshare\d$


Authors

Marco Valentini

Tom Kallo

To Do

* When SharpML is run it will attempt to verify all users that it finds. If a restrictive domain lockout policy exits, it may attempt to verify users multiple times and lock the account out in event of multiple failed authentications
* Some file size limitations need to be implemented in order for larger text based files not to cause a bottle neck when copying the raw data
* Select the option of running multiple file shares simultaneously. By implementing an automatic share finder, allow SharpML to be completely autonomous and scour the whole network
* Improve some program logic, including further options such as the choice of cehcking against 10,000 most common passwords or not
Download SharpML

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Why it’s Important to Find and Fix even Non-Critical Bugs?
https://levelup.gitconnected.com/why-its-important-to-find-and-fix-even-non-critical-bugs-7abc08d81b1f?source=rss------bug_bounty-5

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As a developer, I’ve encountered these kinds of bugs regularly in my programming life, and I’m sure you do too. Sadly, most companies…Continue reading on Level Up Coding » (https://levelup.gitconnected.com/why-its-important-to-find-and-fix-even-non-critical-bugs-7abc08d81b1f?source=rss------bug_bounty-5)

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Expect The Unexpected: Discovering fresh ZeroDay for Bounty
https://sinsinology.medium.com/expect-the-unexpected-discovering-fresh-zeroday-for-bounty-d074f3175847?source=rss------bug_bounty-5

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Special program announced anyone who find a vulnerability in their scope of IP addresses will be rewarded an enormous bountyContinue reading on Medium » (https://sinsinology.medium.com/expect-the-unexpected-discovering-fresh-zeroday-for-bounty-d074f3175847?source=rss------bug_bounty-5)

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hacking: security in practice
10 Types of Web Vulnerabilities that are Often Missed - Detectify Labs

https://external-preview.redd.it/rwXMc5XFvQSDShujxQ9vVQm0SbV463-JeDX7bOFADqs.jpg?width=640&crop=smart&auto=webp&s=8c5b5d3aed4e3297a6b24d85cbdce6df9bd842b9 submitted by /u/intheclairdelune
[link] [comments]

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hacking: security in practice
Generating desired random numbers

Yesterday, I was watching TechWithTim's video about how random module in python works. He said if the seed was same, the sequence will be the same, that got me into thinking. is it possible to know the seed of the sequence by seeing the actual sequence? and after doing some research (googling) I found out that many random number generators use Seed x 8 modulo 11to generate random numbers. If I had a sequence like 1,3,4,2,1,2,3,2is it possible to find what the seed value was fed into the formula to create this pattern?

submitted by /u/Bharath1910
[link] [comments]

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