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Hacking on Medium
Kaseya Received The Universal Decryptor For REvil Ransomware Attack. — CyberWorkx
https://cdn-images-1.medium.com/max/600/0*h__sdCLkyMj6dRYH
Kaseya, the MSP who had faced the zero day attack (CVE-2021–30116) on its VSA product and then escalated into the supply chain attack by…
Continue reading on Medium »
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Kaseya Received The Universal Decryptor For REvil Ransomware Attack. — CyberWorkx
https://cdn-images-1.medium.com/max/600/0*h__sdCLkyMj6dRYH
Kaseya, the MSP who had faced the zero day attack (CVE-2021–30116) on its VSA product and then escalated into the supply chain attack by…
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Medium
Kaseya Received The Universal Decryptor For REvil Ransomware Attack. — CyberWorkx
Kaseya, the MSP who had faced the zero day attack (CVE-2021–30116) on its VSA product and then escalated into the supply chain attack by…
Hacking Articles Tips Tricks Videos Tutorials
Photo
Deep Web
cafedread.com - An announcement from dread.
https://external-preview.redd.it/VSlBP-bLbsx-Uptzi0eryUFhpm-CZoAuMGPob6ucGjs.jpg?width=640&crop=smart&auto=webp&s=fb0f7647ee368231fbaad1dd4038df9c91628a32 submitted by /u/immabookkryptkeeper
[link] [comments]
___________________________
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cafedread.com - An announcement from dread.
https://external-preview.redd.it/VSlBP-bLbsx-Uptzi0eryUFhpm-CZoAuMGPob6ucGjs.jpg?width=640&crop=smart&auto=webp&s=fb0f7647ee368231fbaad1dd4038df9c91628a32 submitted by /u/immabookkryptkeeper
[link] [comments]
___________________________
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@Hacking_Video
reddit
cafedread.com - An announcement from dread.
Posted in r/deepweb by u/immabookkryptkeeper • 1 point and 1 comment
Deep Web
No .onion sites loading
Anyone experienced this problem before? I’ve read some people say it’s due to the clock on the computer but that doesn’t seem to fix it. Normal websites load just not .onion
submitted by /u/TexScot
[link] [comments]
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No .onion sites loading
Anyone experienced this problem before? I’ve read some people say it’s due to the clock on the computer but that doesn’t seem to fix it. Normal websites load just not .onion
submitted by /u/TexScot
[link] [comments]
___________________________
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reddit
No .onion sites loading
Anyone experienced this problem before? I’ve read some people say it’s due to the clock on the computer but that doesn’t seem to fix it. Normal...
In0ri - Defacement Detection With Deep Learning
http://www.kitploit.com/2021/07/in0ri-defacement-detection-with-deep.html
___________________________
@hacking_Attack
@Hacking_Video
http://www.kitploit.com/2021/07/in0ri-defacement-detection-with-deep.html
___________________________
@hacking_Attack
@Hacking_Video
KitPloit - PenTest & Hacking Tools
In0ri - Defacement Detection With Deep Learning
In0ri is a defacement detection system utilizing a image-classification convolutional neural network.
Introduction
When monitoring a website, In0ri will periodically take a screenshot (https://www.kitploit.com/search/label/Screenshot) of the website (https://www.kitploit.com/search/label/Website) then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.
Requirement
Python3 (version >=3.6) Docker Docker-compose
Installation
Cloning the repository
git clone https://github.com/J4FSec/In0ri.git
cd In0ri
Configuring email credentials (https://www.kitploit.com/search/label/Credentials) to send notifications and agent keys from
Edit the file FlaskApp/sendEmail.py EMAIL_ADDRESS = "foo@gmail.com"
EMAIL_PASSWORD = "$uper$ecurePa$$word"
Configure Telegram (https://www.kitploit.com/search/label/Telegram) notification
Edit the file chatbot.py CHAT_ID= 'foo' # Channel ID to send notifications to
TOKEN = 'bar' # Bot token retrieved from @BotFather
Starting In0ri
docker-compose up -d
Usage
There's two ways to deploy and using In0ri: Running off crontab by periodically visiting the url. Internal agent running off the web server
First Method: URL Check
Visit the WebUI on https://:8080/ and click on "Register" then fill in the form and submit it.
Second Method: Internal Agent
Visit the WebUI on https://:8080/ and click on "Register" then fill in the form and submit it. Click on "Create Agent" then fill in the form and check your email for the Agent's key. On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository Installing the required packages for the internal Agent python3 -m pip install watchdog
python3 -m pip install requests Edit the file config.json in the same folder as agent nano config.json A key is sent to your email after registering the Agent on the WebUI rootPath is the root directory of the web application that you want to be monitored exludePath are the subfolders that you wants excluded from the scans apiServer is the URL to the API server of In0ri serverIP is the IP of the API server of In0ri :8088/checkdeface" } '>{
"id":"01",
"key":"123123123",
"rootPath":"/var/www/html",
"excludePath":"",
"apiServer":"http://:8088/checkdeface"
} And run the Agent: python3 agent.py
References
Model training is handled by Shu (https://github.com/J4FSec/Shu)
Authors
In0ri is built by Echidna (https://www.kitploit.com/search/label/Echidna) with the help of Cu64 and Klone.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Download In0ri (https://github.com/J4FSec/In0ri)
___________________________
@hacking_Attack
@Hacking_Video
Introduction
When monitoring a website, In0ri will periodically take a screenshot (https://www.kitploit.com/search/label/Screenshot) of the website (https://www.kitploit.com/search/label/Website) then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.
Requirement
Python3 (version >=3.6) Docker Docker-compose
Installation
Cloning the repository
git clone https://github.com/J4FSec/In0ri.git
cd In0ri
Configuring email credentials (https://www.kitploit.com/search/label/Credentials) to send notifications and agent keys from
Edit the file FlaskApp/sendEmail.py EMAIL_ADDRESS = "foo@gmail.com"
EMAIL_PASSWORD = "$uper$ecurePa$$word"
Configure Telegram (https://www.kitploit.com/search/label/Telegram) notification
Edit the file chatbot.py CHAT_ID= 'foo' # Channel ID to send notifications to
TOKEN = 'bar' # Bot token retrieved from @BotFather
Starting In0ri
docker-compose up -d
Usage
There's two ways to deploy and using In0ri: Running off crontab by periodically visiting the url. Internal agent running off the web server
First Method: URL Check
Visit the WebUI on https://:8080/ and click on "Register" then fill in the form and submit it.
Second Method: Internal Agent
Visit the WebUI on https://:8080/ and click on "Register" then fill in the form and submit it. Click on "Create Agent" then fill in the form and check your email for the Agent's key. On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository Installing the required packages for the internal Agent python3 -m pip install watchdog
python3 -m pip install requests Edit the file config.json in the same folder as agent nano config.json A key is sent to your email after registering the Agent on the WebUI rootPath is the root directory of the web application that you want to be monitored exludePath are the subfolders that you wants excluded from the scans apiServer is the URL to the API server of In0ri serverIP is the IP of the API server of In0ri :8088/checkdeface" } '>{
"id":"01",
"key":"123123123",
"rootPath":"/var/www/html",
"excludePath":"",
"apiServer":"http://:8088/checkdeface"
} And run the Agent: python3 agent.py
References
Model training is handled by Shu (https://github.com/J4FSec/Shu)
Authors
In0ri is built by Echidna (https://www.kitploit.com/search/label/Echidna) with the help of Cu64 and Klone.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Download In0ri (https://github.com/J4FSec/In0ri)
___________________________
@hacking_Attack
@Hacking_Video
KitPloit - PenTest & Hacking Tools
Leading source of security tools, hacking tools, cybersecurity and network security. Learn about new tools and updates in one place.
Hacking Articles Tips Tricks Videos Tutorials
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hacking: security in practice
Serial Swatter Who Caused Death Gets Five Years in Prison
https://external-preview.redd.it/FT-JNmsiSHvG9OUScqH7Edwqa0hcBG2j3b5BOZ-I1jg.jpg?width=320&crop=smart&auto=webp&s=387f7b1574ee27e8c6bebd12c3ab524e0f0635c9 submitted by /u/DrinkMoreCodeMore
[link] [comments]
___________________________
@hacking_Attack
@Hacking_Video
Serial Swatter Who Caused Death Gets Five Years in Prison
https://external-preview.redd.it/FT-JNmsiSHvG9OUScqH7Edwqa0hcBG2j3b5BOZ-I1jg.jpg?width=320&crop=smart&auto=webp&s=387f7b1574ee27e8c6bebd12c3ab524e0f0635c9 submitted by /u/DrinkMoreCodeMore
[link] [comments]
___________________________
@hacking_Attack
@Hacking_Video
reddit
Serial Swatter Who Caused Death Gets Five Years in Prison
Posted in r/hacking by u/DrinkMoreCodeMore • 2 points and 0 comments
Realizations of a Beginner Bug Bounty Hunter
Hey there , I am Abhishek aka p3g4sus (don’t let the fancy handle deceive you, am the naivest of all the hunters).Continue reading on Medium »
Read more...
Hey there , I am Abhishek aka p3g4sus (don’t let the fancy handle deceive you, am the naivest of all the hunters).Continue reading on Medium »
Read more...
In0ri - Defacement Detection With Deep Learning
In0ri is a defacement detection system utilizing a image-classification convolutional neural network. Introduction When monitoring a website, In0ri will periodically take a screenshot of the website then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.Requirement Python3 (version >=3.6) Docker Docker-compose Installation Cloning the repository git clone https://github.com/J4FSec/In0ri.gitcd In0ri Configuring email credentials to send notifications and agent keys from Edit the file FlaskApp/sendEmail.py EMAIL_ADDRESS = "foo@gmail.com"EMAIL_PASSWORD = "$uper$ecurePa$$word" Configure Telegram notification Edit the file chatbot.py CHAT_ID= 'foo' # Channel ID to send notifications toTOKEN = 'bar' # Bot token retrieved from @BotFather Starting In0ri docker-compose up -d Usage There's two ways to deploy and using In0ri: Running off crontab by periodically visiting the url. Internal agent running off the web server First Method: URL Check Visit the WebUI on https://<serverIP>:8080/ and click on "Register" then fill in the form and submit it. Second Method: Internal Agent Visit the WebUI on https://<serverIP>:8080/ and click on "Register" then fill in the form and submit it. Click on "Create Agent" then fill in the form and check your email for the Agent's key. On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository Installing the required packages for the internal Agent python3 -m pip install watchdogpython3 -m pip install requests Edit the file config.json in the same folder as agent nano config.json A key is sent to your email after registering the Agent on the WebUI rootPath is the root directory of the web application that you want to be monitored exludePath are the subfolders that you wants excluded from the scans apiServer is the URL to the API server of In0ri serverIP is the IP of the API server of In0ri { "id":"01", "key":"123123123", "rootPath":"/var/www/html", "excludePath":"", "apiServer":"http://<serverIP>:8088/checkdeface"} And run the Agent: python3 agent.py References Model training is handled by Shu Authors In0ri is built by Echidna with the help of Cu64 and Klone. Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Download In0ri
Read more...
In0ri is a defacement detection system utilizing a image-classification convolutional neural network. Introduction When monitoring a website, In0ri will periodically take a screenshot of the website then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.Requirement Python3 (version >=3.6) Docker Docker-compose Installation Cloning the repository git clone https://github.com/J4FSec/In0ri.gitcd In0ri Configuring email credentials to send notifications and agent keys from Edit the file FlaskApp/sendEmail.py EMAIL_ADDRESS = "foo@gmail.com"EMAIL_PASSWORD = "$uper$ecurePa$$word" Configure Telegram notification Edit the file chatbot.py CHAT_ID= 'foo' # Channel ID to send notifications toTOKEN = 'bar' # Bot token retrieved from @BotFather Starting In0ri docker-compose up -d Usage There's two ways to deploy and using In0ri: Running off crontab by periodically visiting the url. Internal agent running off the web server First Method: URL Check Visit the WebUI on https://<serverIP>:8080/ and click on "Register" then fill in the form and submit it. Second Method: Internal Agent Visit the WebUI on https://<serverIP>:8080/ and click on "Register" then fill in the form and submit it. Click on "Create Agent" then fill in the form and check your email for the Agent's key. On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository Installing the required packages for the internal Agent python3 -m pip install watchdogpython3 -m pip install requests Edit the file config.json in the same folder as agent nano config.json A key is sent to your email after registering the Agent on the WebUI rootPath is the root directory of the web application that you want to be monitored exludePath are the subfolders that you wants excluded from the scans apiServer is the URL to the API server of In0ri serverIP is the IP of the API server of In0ri { "id":"01", "key":"123123123", "rootPath":"/var/www/html", "excludePath":"", "apiServer":"http://<serverIP>:8088/checkdeface"} And run the Agent: python3 agent.py References Model training is handled by Shu Authors In0ri is built by Echidna with the help of Cu64 and Klone. Contributing Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change. Download In0ri
Read more...
Modelling and Detecting Lateral Movement
https://www.reddit.com/r/redteamsec/comments/oqciuf/modelling_and_detecting_lateral_movement/
submitted by /u/dmchell (https://www.reddit.com/user/dmchell)
[link] (https://arxiv.org/pdf/2105.13442.pdf) [comments] (https://www.reddit.com/r/redteamsec/comments/oqciuf/modelling_and_detecting_lateral_movement/)
___________________________
@hacking_Attack
@Hacking_Video
https://www.reddit.com/r/redteamsec/comments/oqciuf/modelling_and_detecting_lateral_movement/
submitted by /u/dmchell (https://www.reddit.com/user/dmchell)
[link] (https://arxiv.org/pdf/2105.13442.pdf) [comments] (https://www.reddit.com/r/redteamsec/comments/oqciuf/modelling_and_detecting_lateral_movement/)
___________________________
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Reddit
r/redteamsec on Reddit: Modelling and Detecting Lateral Movement
Posted by u/dmchell - 16 votes and no comments
Hacking Articles Tips Tricks Videos Tutorials
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KitPloit - PenTest Tools!
In0ri - Defacement Detection With Deep Learning
https://1.bp.blogspot.com/-37Gj6hYYBwE/YPifykm91UI/AAAAAAAAjUE/HMeWGZxigQEHDTmjKnmvF4eLBAUKfZ6cwCNcBGAsYHQ/w640-h640/logo_transparent.png
In0ri is a defacement detection system utilizing a image-classification convolutional neural network.
Introduction
When monitoring a website, In0ri will periodically take a screenshot of the website then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.
Requirement
* Python3 (version >=3.6)
* Docker
* Docker-compose
Installation
Cloning the repository
Configuring email credentials to send notifications and agent keys from
Edit the file
Configure Telegram notification
Edit the file
Starting In0ri
Usage
There's two ways to deploy and using In0ri:
* Running off crontab by periodically visiting the url.
* Internal agent running off the web server
First Method: URL Check
Visit the WebUI on https://and click on "Register" then fill in the form and submit it.
Second Method: Internal Agent
Visit the WebUI on https://and click on "Register" then fill in the form and submit it.
Click on "Create Agent" then fill in the form and check your email for the Agent's key.
On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository
Installing the required packages for the internal Agent
Edit the file
A
{
"id":"01",
"key":"123123123",
"rootPath":"/var/www/html",
"excludePath":"",
"apiServer":"http://
And run the Agent:
References
Model training is handled by Shu
Authors
In0ri is built by Echidna with the help of Cu64 and Klone.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Download In0ri
___________________________
@hacking_Attack
@Hacking_Video
In0ri - Defacement Detection With Deep Learning
https://1.bp.blogspot.com/-37Gj6hYYBwE/YPifykm91UI/AAAAAAAAjUE/HMeWGZxigQEHDTmjKnmvF4eLBAUKfZ6cwCNcBGAsYHQ/w640-h640/logo_transparent.png
In0ri is a defacement detection system utilizing a image-classification convolutional neural network.
Introduction
When monitoring a website, In0ri will periodically take a screenshot of the website then put it through a preprocessor that will resize the image down to 250x250px and numericalize the image before passing it onto the classifier. The core of the classifier is a convolutional neural network that is trained to detect the defacement of a website. If the monitored website is indeed, defaced, In0ri will send out warnings via email to the user.
Requirement
* Python3 (version >=3.6)
* Docker
* Docker-compose
Installation
Cloning the repository
git clone https://github.com/J4FSec/In0ri.git
cd In0riConfiguring email credentials to send notifications and agent keys from
Edit the file
FlaskApp/sendEmail.pyEMAIL_ADDRESS = "foo@gmail.com"
EMAIL_PASSWORD = "$uper$ecurePa$$word"Configure Telegram notification
Edit the file
chatbot.pyCHAT_ID= 'foo' # Channel ID to send notifications to
TOKEN = 'bar' # Bot token retrieved from @BotFatherStarting In0ri
docker-compose up -dUsage
There's two ways to deploy and using In0ri:
* Running off crontab by periodically visiting the url.
* Internal agent running off the web server
First Method: URL Check
Visit the WebUI on https://and click on "Register" then fill in the form and submit it.
Second Method: Internal Agent
Visit the WebUI on https://and click on "Register" then fill in the form and submit it.
Click on "Create Agent" then fill in the form and check your email for the Agent's key.
On the web server that you wants to be monitored by In0ri, download the Agent folder from Github repository
Installing the required packages for the internal Agent
python3 -m pip install watchdog
python3 -m pip install requestsEdit the file
config.jsonin the same folder as agentnano config.jsonA
keyis sent to your email after registering the Agent on the WebUI rootPathis the root directory of the web application that you want to be monitored exludePathare the subfolders that you wants excluded from the scans apiServeris the URL to the API server of In0ri serverIPis the IP of the API server of In0ri{
"id":"01",
"key":"123123123",
"rootPath":"/var/www/html",
"excludePath":"",
"apiServer":"http://
And run the Agent:
python3 agent.pyReferences
Model training is handled by Shu
Authors
In0ri is built by Echidna with the help of Cu64 and Klone.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Download In0ri
___________________________
@hacking_Attack
@Hacking_Video
KitPloit - PenTest & Hacking Tools
In0ri - Defacement Detection With Deep Learning
Hacking Articles Tips Tricks Videos Tutorials
Photo
Hacking on Medium
Tools to reset your computer password when you have no USB backups or ways to format the hard disk.
[Note: There is a disclaimer below]
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Tools to reset your computer password when you have no USB backups or ways to format the hard disk.
[Note: There is a disclaimer below]
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Medium
Tools to reset your computer password when you have no USB backups or ways to format the hard disk.
[Note: There is a disclaimer below]
Hacking Articles Tips Tricks Videos Tutorials
Photo
Hacking on Medium
¿Pueden espiarnos los gobiernos y los ciberdelincuentes?
https://cdn-images-1.medium.com/max/2600/1*WljTKs4MX02yqiqbVPIpMA.jpeg
Mito o realidad sobre el espionaje informático a gran escala o de manera individual.
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
¿Pueden espiarnos los gobiernos y los ciberdelincuentes?
https://cdn-images-1.medium.com/max/2600/1*WljTKs4MX02yqiqbVPIpMA.jpeg
Mito o realidad sobre el espionaje informático a gran escala o de manera individual.
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Medium
¿Pueden espiarnos los gobiernos y los ciberdelincuentes?
Mito o realidad sobre el espionaje informático a gran escala o de manera individual.
Hacking Articles Tips Tricks Videos Tutorials
Photo
Hacking on Medium
Полезные Telegram-боты 2021 часть 2
https://cdn-images-1.medium.com/max/800/0*Tdtjw-HUFk22qfiR.jpg
Привет любителям ботов, захотелось дополнить статью “Часть 1 тык” еще полезными работающими ботами.
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Полезные Telegram-боты 2021 часть 2
https://cdn-images-1.medium.com/max/800/0*Tdtjw-HUFk22qfiR.jpg
Привет любителям ботов, захотелось дополнить статью “Часть 1 тык” еще полезными работающими ботами.
Continue reading on Medium »
___________________________
@hacking_Attack
@Hacking_Video
Medium
Полезные Telegram-боты 2021 часть 2
Привет любителям ботов, захотелось дополнить статью “Часть 1 тык” еще полезными работающими ботами.