Deep Web
New to the deep web, I’ve seen some archives. What do I do next?

How do you find sites that aren’t as well known or “explore” the deep web?

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Karton - Distributed Malware Processing Framework Based On Python, Redis And MinIO
http://www.kitploit.com/2021/08/karton-distributed-malware-processing.html

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Distributed malware processing framework based on Python, Redis and MinIO.
The idea
Karton is a robust framework for creating flexible and lightweight malware analysis (https://www.kitploit.com/search/label/Malware%20Analysis) backends. It can be used to connect malware* analysis systems into a robust pipeline with very little effort. We've been in the automation (https://www.kitploit.com/search/label/Automation) business for a long time. We're dealing with more and more threats, and we have to automate everything to keep up with incidents. Because of this, we often end up with many scripts stuck together with duck duct tape and WD-40. These scripts are written by analysts in the heat of the moment, fragile and ugly - but they work, and produce intel that must be stored, processed further, sent to other systems or shared with other organisations. We needed a way to take our PoC scripts and easily insert them into our analysis pipeline. We also wanted to monitor their execution, centralise logging, improve robustness, reduce development inertia... For this exact purpose, we created Karton. * while Karton was designed with malware analysis in mind, it works nicely in every microservice-oriented project.
Installation
Installation is as easy as a single pip install command: pip3 install karton-core
In order to setup the whole backend environment you will also need MinIO and Redis, see the docs (https://karton-core.readthedocs.io/en/latest/getting_started.html#installation) for details.
Example usage
To use karton you have to provide class that inherits from Karton. None: # Get sample object packed_sample = task.get_resource('sample') # Log with self.log self.log.info(f"Hi {packed_sample.name}, let me analyze you!") ... # Send our results for further processing or reporting task = Task( { "type": "sample", "kind": "raw" }, payload = { "parent": packed_sample, "sample": Resource(filename, unpacked) }) self.send_task(task) if __name__ == "__main__": # Here comes the main loop GenericUnpacker().loop() ">from karton.core import Karton, Task, Resource

class GenericUnpacker(Karton):
"""
Performs sample unpacking
"""
identity = "karton.generic-unpacker"
filters = [
{
"type": "sample",
"kind": "runnable",
"platform": "win32"
}
]

def process(self, task: Task) -> None:
# Get sample object
packed_sample = task.get_resource('sample')
# Log with self.log
self.log.info(f"Hi {packed_sample.name}, let me analyze you!")
...
# Send our results for further processing or reporting
task = Task(
{
"type": "sample",
"kind": "raw"
}, payload = {
"parent": packed_sample,
"sample": Resource(filename, unpacked)
})
self.send_task(task)< br/>
if __name__ == "__main__":
# Here comes the main loop
GenericUnpacker().loop()
Karton systems
Some Karton systems are universal and useful to everyone. We decided to share them with the community.
karton (https://github.com/CERT-Polska/karton)
This repository. It contains the karton.system service - main service, responsible for dispatching tasks within the system. It also contains the karton.core module, that is used as a library by other systems.
karton-dashboard (https://github.com/CERT-Polska/karton-dashboard)
A small Flask dashboard (https://www.kitploit.com/search/label/Dashboard) for task and queue management (https://www.kitploit.com/search/label/Management) and monitoring.
karton-classifier (https://github.com/CERT-Polska/karton-classifier)

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The "router". It recognises samples/files and produces various task types depending on the file format. Thanks to this, other systems may only listen for tasks with a specific format (for example, only zip archives).
karton-archive-extractor (https://github.com/CERT-Polska/karton-archive-extractor)
Generic archive unpacker. Archives uploaded into the system will be extracted, and every file will be processed individually.
karton-config-extractor (https://github.com/CERT-Polska/karton-config-extractor)
Malware extractor. It uses Yara rules and Python modules to extract static configuration from malware samples (https://www.kitploit.com/search/label/Malware%20Samples) and analyses. It's a fishing rod, not a fish - we don't share the modules themselves. But it's easy to write your own!
karton-mwdb-reporter (https://github.com/CERT-Polska/karton-mwdb-reporter)
A very important part of the pipeline. Reporter submits all files, tags, comments and other intel produced during the analysis to MWDB (https://github.com/CERT-Polska/mwdb-core). If you don't use MWDB yet or just prefer other backends, it's easy to write your own reporter.
karton-yaramatcher (https://github.com/CERT-Polska/karton-yaramatcher)
Automatically runs Yara rules on all files in the pipeline, and tags samples appropriately. Rules not included ;).
karton-asciimagic (https://github.com/CERT-Polska/karton-asciimagic)
Karton system that decodes files encoded with common methods, like hex, base64, etc. (You wouldn't believe how common it is).
karton-autoit-ripper (https://github.com/CERT-Polska/karton-autoit-ripper)
A small wrapper around AutoIt-Ripper (https://github.com/nazywam/AutoIt-Ripper) that extracts embedded AutoIt scripts and resources from compiled AutoIt executables.
DRAKVUF Sandbox (https://github.com/CERT-Polska/drakvuf-sandbox)
Automated black-box malware analysis system with DRAKVUF engine under the hood, which does not require an agent on guest OS. Coming soon:
karton-misp-pusher
A reporter, that submits observed events to MISP. This is how these systems can be used to form a basic malware analysis pipeline:

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Download Karton (https://github.com/CERT-Polska/karton)

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KitPloit - PenTest Tools!
Karton - Distributed Malware Processing Framework Based On Python, Redis And MinIO

https://1.bp.blogspot.com/-M70yae7UU1M/YRIMOxB0jAI/AAAAAAAApsg/68Huf72xtrY5-zMbnE94Q1zvJrVsc8PZgCNcBGAsYHQ/w640-h248/karton.png Distributed malware processing framework based on Python, Redis and MinIO. The ideaKarton is a robust framework for creating flexible and lightweight malware analysis backends. It can be used to connect malware* analysis systems into a robust pipeline with very little effort.

We've been in the automation business for a long time. We're dealing with more and more threats, and we have to automate everything to keep up with incidents. Because of this, we often end up with many scripts stuck together with duck duct tape and WD-40. These scripts are written by analysts in the heat of the moment, fragile and ugly - but they work, and produce intel that must be stored, processed further, sent to other systems or shared with other organisations.

We needed a way to take our PoC scripts and easily insert them into our analysis pipeline. We also wanted to monitor their execution, centralise logging, improve robustness, reduce development inertia... For this exact purpose, we created Karton.

* while Karton was designed with malware analysis in mind, it works nicely in every microservice-oriented project. InstallationInstallation is as easy as a single pip installcommand: pip3 install karton-core In order to setup the whole backend environment you will also need MinIO and Redis, see the docs for details. Example usageTo use karton you have to provide class that inherits from Karton.

None: # Get sample object packed_sample = task.get_resource('sample') # Log with self.log self.log.info(f"Hi {packed_sample.name}, let me analyze you!") ... # Send our results for further processing or reporting task = Task( { "type": "sample", "kind": "raw" }, payload = { "parent": packed_sample, "sample": Resource(filename, unpacked) }) self.send_task(task) if __name__ == "__main__": # Here comes the main loop GenericUnpacker().loop() ">from karton.core import Karton, Task, Resource

class GenericUnpacker(Karton):
"""
Performs sample unpacking
"""
identity = "karton.generic-unpacker"
filters = [
{
"type": "sample",
"kind": "runnable",
"platform": "win32"
}
]

def process(self, task: Task) -> None:
# Get sample object
packed_sample = task.get_resource('sample')
# Log with self.log
self.log.info(f"Hi {packed_sample.name}, let me analyze you!")
...
# Send our results for further processing or reporting
task = Task(
{
"type": "sample",
"kind": "raw"
}, payload = {
"parent": packed_sample,
"sample": Resource(filename, unpacked)
})
self.send_task(task)< br/>
if __name__ == "__main__":
# Here comes the main loop
GenericUnpacker().loop() Karton systemsSome Karton systems are universal and useful to everyone. We decided to share them with the community. kartonThis repository. It contains the karton.systemservice - main service, responsible for dispatching tasks within the system. It also contains the karton.coremodule, that is used as a library by other systems. karton-dashboardA small Flask dashboard for task and queue management and monitoring. karton-classifierThe "router". It recognises samples/files and produces various task types depending on the file format. Thanks to this, other systems may only listen for tasks with a specific format (for example, only ziparchives). karton-archive-extractorGeneric archive unpacker. Archives uploaded into the system wil[...]

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@Hacking_Video

l be extracted, and every file will be processed individually. karton-config-extractorMalware extractor. It uses Yara rules and Python modules to extract static configuration from malware samples and analyses. It's a fishing rod, not a fish - we don't share the modules themselves. But it's easy to write your own! karton-mwdb-reporterA very important part of the pipeline. Reporter submits all files, tags, comments and other intel produced during the analysis to MWDB. If you don't use MWDB yet or just prefer other backends, it's easy to write your own reporter. karton-yaramatcherAutomatically runs Yara rules on all files in the pipeline, and tags samples appropriately. Rules not included ;). karton-asciimagicKarton system that decodes files encoded with common methods, like hex, base64, etc. (You wouldn't believe how common it is). karton-autoit-ripperA small wrapper around AutoIt-Ripper that extracts embedded AutoIt scripts and resources from compiled AutoIt executables. DRAKVUF SandboxAutomated black-box malware analysis system with DRAKVUF engine under the hood, which does not require an agent on guest OS.

Coming soon: karton-misp-pusherA reporter, that submits observed events to MISP.

This is how these systems can be used to form a basic malware analysis pipeline: https://1.bp.blogspot.com/-M70yae7UU1M/YRIMOxB0jAI/AAAAAAAApsg/68Huf72xtrY5-zMbnE94Q1zvJrVsc8PZgCNcBGAsYHQ/w640-h248/karton.png Download Karton

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Deep Web
where to find deep web websites

what can i use to find deepweb websites?

submitted by /u/Clorox_bleach_spray
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hacking: security in practice
Dump for the conti ransomeware gang?

Is there a dump of the original files anywhere?

submitted by /u/jesus-da-wizard
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hacking: security in practice
Which language?

I know this is super super cliche but I’m not sure which language to go for.

I messed around and am still playing with python a lot, I don’t know it too well but still.

I wanna get into hacking, not for anything unethical but I want the skills for it.

I hear Java or JavaScript but I’m not sure what’s good for effectiveness and for a beginner like me.

All help is appreciated and feel free to ask questions!

submitted by /u/Polypgb
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hacking: security in practice
API For Apple Air Tag?

Hey has anyone developed a API or something to get the GPS location of an Air tag they own? Im trying to make my own tracker using google maps to access on my android or windows device but can't since apple wont offer such

submitted by /u/SteinsGates
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hacking: security in practice
Microsoft Exchange email hack was caused by China, U.S. says

https://external-preview.redd.it/cYw1jQqe-r2TOpOKFCTleiqzvVx5kFJ70PJXjfJLW8w.jpg?width=640&crop=smart&auto=webp&s=574ec6ea0e19d773952d7d311ed512c31587f050 submitted by /u/snooshoe
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Dexfolio x Immunifi: $12,000 Bug Bounty
https://dexfolio.medium.com/dexfolio-x-immunifi-12-000-bug-bounty-366061b9ad16?source=rss------bug_bounty-5

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With the largest hack in DEFI history — $600M stolen through Poly Network—every project should be thinking about how to make their funds…Continue reading on Medium » (https://dexfolio.medium.com/dexfolio-x-immunifi-12-000-bug-bounty-366061b9ad16?source=rss------bug_bounty-5)

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Hacking on Medium
The Biggest Hack in crypto history

11th August 2021
The Biggest Hack in cryptocurrency history!

Continue reading on Medium »

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