Kali Linux Tutorials
ShonyDanza : A Customizable, Easy-To-Navigate Tool For Researching, Pen Testing, And Defending With The Power Of Shodan

ShonyDanza is a customizable, easy-to-navigate tool for researching, pen testing, and defending with the power of Shodan.

With ShonyDanza, you can:

* Obtain IPs based on search criteria
* Automatically exclude honeypots from the results based on your pre-configured thresholds
* Pre-configure all IP searches to filter on your specified net range(s)
* Pre-configure search limits
* Use build-a-search to craft searches with easy building blocks
* Use stock searches and pre-configure your own stock searches
* Check if IPs are known malware C2s
* Get host and domain profiles
* Scan on-demand
* Find exploits
* Get total counts for searches and exploits
* Automatically save exploit code, IP lists, host profiles, domain profiles, and scan results to directories within ShonyDanza

Installation

git clone https://github.com/fierceoj/ShonyDanza.git

Requirements

* python3
* shodan library

cd ShonyDanza
pip3 install -r requirements.txt

Usage

Edit config.py to include your desired configurations
cd configs
sudo nano config.py

config file for shonydanza searches
REQUIRED
maximum number of results that will be returned per search
default is 100
SEARCH_LIMIT = 100
REQUIRED
IPs exceeding the honeyscore limit will not show up in IP results
scale is 0.0 to 1.0
adjust to desired probability to restrict results by threshold, or keep at 1.0 to include all results
HONEYSCORE_LIMIT = 1.0
REQUIRED – at least one key: value pair
add a shodan dork to the dictionary below to add it to your shonydanza stock searches men
see https://github.com/jakejarvis/awesome-shodan-queries for a great source of queries
check into “vuln:” filter if you have Small Business Plan or higher (e.g., vuln:cve-2019-11510)
STOCK_SEARCHES = {
‘ANONYMOUS_FTP’:’ftp anonymous ok’,
‘RDP’:’port:3389 has_screenshot:true’,
‘OPEN_TELNET’:’port:23 console gateway -password’,
‘APACHE_DIR_LIST’:’http.title:”Index of /”‘,
‘SPRING_BOOT’:’http.favicon.hash:116323821′,
‘HP_PRINTERS’:'”Serial Number:” “Built:” “Server: HP HTTP”‘,
‘DOCKER_API’:'”Docker Containers:” port:2375′,
‘ANDROID_ROOT_BRIDGE’:'”Android Debug Bridge” “Device” port:5555′,
‘MONGO_EXPRESS_GUI’:'”Set-Cookie: mongo-express=” “200 OK”‘,
‘CVE-2019-11510_PULSE_VPN’:’http.html:/dana-na/’,
‘CVE-2019-19781_CITRIX_NETSCALER’:’http.waf:”Citrix NetScaler”‘,
‘CVE-2020-5902_F5_BIGIP’:’http.favicon.hash:-335242539 “3992”‘,
‘CVE-2020-3452_CISCO_ASA_FTD’:’200 “Set-Cookie: webvpn;”‘
}
OPTIONAL
IP or cidr range constraint for searches that return list of IP addresses
use comma-separated list to designate multiple (e.g. 1.1.1.1,2.2.0.0/16,3.3.3.3,3.3.3.4)
NET_RANGE = ‘0.0.0.0/0’

Run

cd ../
python3 shonydanza.py
Download

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hacking: security in practice
The Cookies Parasite - Bypassing MFA with cookie theft

https://external-preview.redd.it/O__-2MKmQSwN3UPFQGuAEqQQ5aB_CFps_pbLqKS0VyI.jpg?width=640&crop=smart&auto=webp&s=391a9295219220a4e5e93684e4c237aca0d0e449 submitted by /u/amirshk
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Dark Reading: Attacks/Breaches
Data Privacy Day 2022: How Can AI Help in the Fight Against Ransomware?

Fewer than one-quarter of organizations believe they are fully prepared for a ransomware attack, threatening data privacy

Combobulator - Framework To Detect And Prevent Dependency Confusion Leakage And Potential Attacks
http://www.kitploit.com/2022/01/combobulator-framework-to-detect-and.html

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Dependency Combobulator is an Open-Source, modular and extensible framework to detect and prevent dependency confusion leakage and potential attacks. This facilitates a holistic approach for ensuring secure application releases that can be evaluated against different sources (e.g., GitHub Packages, JFrog Artifactory) and many package management (https://www.kitploit.com/search/label/Management) schemes (e.g., ndm, maven).
Intended Audiences The framework can be used by security auditors, pentesters (https://www.kitploit.com/search/label/Pentesters) and even baked into an enterprise's application security program and release cycle in an automated fashion. Main features Pluggable - interject on commit level, build, release steps in SDLC. Expandable - easily add your own package management scheme or code source of choice General-purpose Heuristic-Engine - an abstract package data model provides agnostic heuristic approach Supporting wide range of technologies Flexible - decision trees can be determined upon insights or verdicts provided by the toolkit Easly exstensible The project is putting practicionar's ability to extend and fit the toolkit to her own specific needs. As such, it is designed to be able to extend it to other sources, public registries, package management schemes and extending the abstract model and accompnaied heuristics engine. Installation Dependency Combobulator is ready to work with as it is - just git clone or download the package from https://github.com/apiiro/combobulator Make sure to install required dependencies by running: pip install -r requirements.txt Arguments (--help) Access Token (Overrides .env file setting) -a {compare,comp,heuristics,heur}, --analysis {compare,comp,heuristics,heur} Required analysis level - compare (comp), heuristics (heur) (default: compare) Apiiro Community"> -h, --help show this help message and exit
-t {npm,NuGet,maven}, --type {npm,NuGet,maven}
Package Manager Type, i.e: npm, NuGet, maven
-l LIST_FROM_FILE, --load_list LIST_FROM_FILE
Load list of dependencies from a file
-d FROM_SRC, --directory FROM_SRC
Extract dependencies from local source repository
-p--package SINGLE Name a single package.
-c CSV, --csv CSV Export packages properties onto CSV file
-gh GITHUB_TOKEN, --github GITHUB_TOKEN
GitHub Access Token (Overrides .env file setting)
-a {compare,comp,heuristics,heur}, --analysis {compare,comp,heuristics,heur}
Required analysis level - compare (comp), heuristics
(heur) (default: compare)

Apiiro Community
Supported package types (-t, --t): npm, maven Supported source dependency assessment: From file containing the dependency identifiers line-by-line. (-l, --load_list) By analyzing the appropriate repo's software bill-of-materials (e.g. package.json, pom.xml) (-d, --directory) Naming a single identifier (https://www.kitploit.com/search/label/Identifier) (-p, --package) Analysis level is customizable (https://www.kitploit.com/search/label/Customizable) as you can build your own preferred analysis profile in seconds. Dependency Combobulator does come with several analysis levels out-of-the-box, selected by -a, --analysis Supported output format: Screen stdout (default) CSV export to designated file -(-CSV)
Credits The project is maintained and sponsored by Apiiro with We honor great developers & AppSec practitioners with a passion for change

Download Combobulator (https://github.com/apiiro/combobulator)

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Deep Web
deep web video story volume 1

https://external-preview.redd.it/m0bD9eW5DYkAuRFooLFAdVYkjYL2uyf5uBrtPBMOKEE.jpg?width=320&crop=smart&auto=webp&s=9802b791b24797e8bbe99647e1ddab84fb88171d submitted by /u/Interesting_Stand877
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Black Hat Ethical Hacking
Offensive Security Tool: Crypto Steganography

https://www.blackhatethicalhacking.com/wp-content/uploads/2021/08/Untitled-design-2-1.png Offensive Security Tool: Crypto SteganographyPost Views: 199 https://www.blackhatethicalhacking.com/wp-content/uploads/2021/08/BECOME-A-PATRON-AND-UNLOCK-EXCLUSIVE-VIDEOS-1.png Reading Time: 4 Minutes

Offensive Security Tool: Crypto Steganography GitHub Link CryptosteganographySteganography is the practice of concealing a message within another message or a physical object. In computing/electronic contexts, a computer file, message, image, or video is concealed within another file, message, image, or video. Can be used as part of advanced Phishing simulation techniques or concealing encrypted secret messages.

It is the art of concealing information within different types of media objects such as images or audio files, in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message. By default steganography is a type of security through obscurity.

Cryptosteganography by Computationalcore is a python steganography module to store messages or files protected with AES-256 encryption inside an image.

Additionally this module also enhance the security of the steganography through data encryption. The data concealed is encrypted using AES 256 encryption, a popular algorithm used in symmetric key cryptography. PrerequisitesPython 3+ pip3

(Most Linux systems comes with python 3 installed by default).
See Also: Recon Tool: WitnessMe Dependencies Installation (Ubuntu)$ sudo apt-get install python3-pip Dependencies Installation (MacOS)To install Python3 its recommended to use Homebrew package manager

The script will explain what changes it will make and prompt you before the installation begins.

$ ruby -e “$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)”

Edit your ~/.profile to include (if it is not already there)

export PATH=/usr/local/bin:/usr/local/sbin:$PATH

To install Python 3:

$ brew install python3
See Also: Apple pays out $100k bounty for Safari webcam hack that imperiled victims’ online accounts InstallationTo install the package just run

$ pip3 install cryptosteganography
See Also: Complete Offensive Security and Ethical Hacking Course UsageUse as a library in a python programStore a message string inside an image

from cryptosteganography import CryptoSteganography

crypto_steganography = CryptoSteganography(‘My secret password key’)

# Save the encrypted file inside the image
crypto_steganography.hide(‘input_image_name.jpg’, ‘output_image_file.png’, ‘My secret message’)

secret = crypto_steganography.retrieve(‘output_image_file.png’)

print(secret)
# My secret message
Store a binary file inside an image

Note: This only works if the concealed file size is smaller than the input image
from cryptosteganography import CryptoSteganography message = None with open('sample.mp3', "rb") as f: message = f.read() crypto_steganography = CryptoSteganography('My secret password key') # Save the encrypted file inside the image crypto_steganography.hide('input_image_name.jpg', 'output_image_file.png', message) # Retrieve the file ( the previous crypto_steganography instance could be used but I instantiate a brand new object # with the same password key just to demonstrate that can it can be used to decrypt) crypto_steganography = CryptoSteganography('My secret password key') decrypted_bin = crypto_steganography.retrieve('output_image_file.png') # Save the data to a new file with open('decrypted_sample.mp3', 'wb') as f: f.write(secret_bin) Use as a python programCheck help at command line prom[...]

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Black Hat Ethical Hacking
Offensive Security Tool: Crypto Steganography

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KitPloit - PenTest Tools!
Combobulator - Framework To Detect And Prevent Dependency Confusion Leakage And Potential Attacks

https://blogger.googleusercontent.com/img/a/AVvXsEj8Pw-5EcaYJCPZ-x5MSGwvKGtGAaUvVN1QwgV2L66Sifv1463cLHjlHFEYn9a7FeFgnaLTrRqpXmyYBzOOebYV2pj94tUW2brKrJFgAfXEKmR3gcKcUX-UZ2tW624hzgsEBZHzKAYn_f-tbgBuZiXhGMhwRaFrChionqo7Y_y2RjwJUDgDZo7VOttF=w640-h388 Dependency Combobulator is an Open-Source, modular and extensible framework to detect and prevent dependency confusion leakage and potential attacks. This facilitates a holistic approach for ensuring secure application releases that can be evaluated against different sources (e.g., GitHub Packages, JFrog Artifactory) and many package management schemes (e.g., ndm, maven). Intended AudiencesThe framework can be used by security auditors, pentesters and even baked into an enterprise's application security program and release cycle in an automated fashion. Main features* Pluggable - interject on commit level, build, release steps in SDLC.
* Expandable - easily add your own package management scheme or code source of choice
* General-purpose Heuristic-Engine - an abstract package data model provides agnostic heuristic approach
* Supporting wide range of technologies
* Flexible - decision trees can be determined upon insights or verdicts provided by the toolkit Easly exstensibleThe project is putting practicionar's ability to extend and fit the toolkit to her own specific needs. As such, it is designed to be able to extend it to other sources, public registries, package management schemes and extending the abstract model and accompnaied heuristics engine. InstallationDependency Combobulator is ready to work with as it is - just git cloneor download the package from https://github.com/apiiro/combobulator

Make sure to install required dependencies by running: pip install -r requirements.txtArguments (--help)Access Token (Overrides .env file setting) -a {compare,comp,heuristics,heur}, --analysis {compare,comp,heuristics,heur} Required analysis level - compare (comp), heuristics (heur) (default: compare) Apiiro -h, --help show this help message and exit
-t {npm,NuGet,maven}, --type {npm,NuGet,maven}
Package Manager Type, i.e: npm, NuGet, maven
-l LIST_FROM_FILE, --load_list LIST_FROM_FILE
Load list of dependencies from a file
-d FROM_SRC, --directory FROM_SRC
Extract dependencies from local source repository
-p--package SINGLE Name a single package.
-c CSV, --csv CSV Export packages properties onto CSV file
-gh GITHUB_TOKEN, --github GITHUB_TOKEN
GitHub Access Token (Overrides .env file setting)
-a {compare,comp,heuristics,heur}, --analysis {compare,comp,heuristics,heur}
Required analysis level - compare (comp), heuristics
(heur) (default: compare)

Apiiro

Supported package types (-t, --t): npm, maven

Supported source dependency assessment:

* From file containing the dependency identifiers line-by-line. (-l, --load_list)
* By analyzing the appropriate repo's software bill-of-materials (e.g. package.json, pom.xml) (-d, --directory)
* Naming a single identifier (-p, --package)

Analysis level is customizable as you can build your own preferred analysis profile in seconds. Dependency Combobulator does come with several analysis levels out-of-the-box, selected by -a, --analysis

Supported output format:

* Screen stdout (default)
* CSV export to designated file -(-CSV) CreditsThe project is maintained and sponsored by Apiiro with

We honor great developers & AppSec practitioners with a passion for change Download Combobulator

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Hacking on Medium
Don’t take it out on the Incident Response Team

https://cdn-images-1.medium.com/max/2048/0*pWZv_V6pJA0FhxlI
DFIR work is like being the grim reaper sometimes, everywhere we go no one is happy to see us. We deliver bad news in every call and our…

Continue reading on Medium »

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Hacking on Medium
TryHackMe — Extending Your Network

https://cdn-images-1.medium.com/max/2600/0*oFFf2Wy6F-VWChzN
Ctf info writeup

Continue reading on InfoSec Write-ups »

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Kali Linux Tutorials
5 Types of Cyber Security Threats

A cyber-attack can cause devastating effects on a business. Not only can it shut down your operations, but your reputation can be significantly impacted.

In order to prevent them from happening as much as possible, it’s essential to know what types of threats there are. Below, we will talk about just five that you should watch out for.

Sound interesting? Then let’s get started.

Malware

Malware is one of the most well-known cyber security threats installed through dangerous links and attachments. It can be used to describe other terms, such as viruses, ransomware, spyware, and worms.

Once your computer or device has become infected, it can cause several issues. For example, some may spam you with advertisements, while others will crack passwords and lock your important files.

This is why it can be worth seeking out a managed security services provider to help you establish a great protection plan. It’s better to focus on prevention before it’s too late.

Phishing

Phishing is an attack that uses an email to trick the recipient into sending personal information, such as credit card details. Often, they are disguised to look exactly like a well-known company.

Some emails will contain malware that is installed after clicking on a link, while others will communicate with the recipient directly. Luckily, there are ways to identify them.

You may notice:

– Grammar and spelling errors

– Inconsistencies in email addresses

– Sense of urgency

–Suspicious attachments

Data Spill

A data spill or data breach is when personal information becomes available to another unauthorized person. This could be due to hacking or something as simple as accidentally sending an email to the wrong person.

In order to prevent these types of breaches from happening, businesses can use a variety of tools, such as XDR or Extended Detection and Response. You can read more about how it works here.

Denial of Service Attack

Also known as DOS, Denial of Service attacks overload your system with requests. This can either cause it to shut down or become inaccessible to users.

Compared to the other threats on this list, DOS attacks don’t necessarily aim to steal information but instead cause a company to lose time and money.

Man in the Middle Attack

Like in a spy movie, a “Man in the Middle” attack occurs when a hacker spies between two people to steal information. They are one of the oldest types of cyber threats and aren’t as common as those mentioned above.

This is because the same effect can generally be done with malware. That being said, it’s still something that can cause a lot of damage.

Final Words

And that’s it. These were five types of cyber security threats. By learning more about them, you can focus on building strategies to help protect you and your information.

However, keep in mind there are many others that you may want to look further into, some of which include:

– SQL Injection

– DNS Tunnelling

– Drive-by Attack

– Password Attack

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hacking: security in practice
How do companies that investigate dark web data dumps make money?

I was listening to Dark Net Diaries (Marq) and we get told how the data he tries to sell on the dark web ends up being bought but an IT security company who purposely access the dark web and buy these data dumps from hackers so they can investigate the data, see who it belongs to, tell the company and hand over info to the FBI.

My question is where exactly in this process does a company like this make money? In this specific example they legit paid $600 worth of BTC for the data dump, so where are they making this money back + profits? Do the FBI pay them for the info? Do the victim company pay them?

submitted by /u/deadassmf
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