Black Hat Ethical Hacking
Malicious Chrome ad blocker injects ads behind the scenes

https://www.blackhatethicalhacking.com/wp-content/uploads/2021/08/Untitled-design-2-1.png Malicious Chrome ad blocker injects ads behind the scenesPost Views: 85
Reading Time: 1 Minute
The AllBlock Chromium ad blocking extension has been found to be injecting hidden affiliate links that generate commissions for the developers.
This extension is still available on Chrome’s Web Store and promotes itself as an ad blocker that focuses on YouTube and Facebook to prevent pop-ups and speed up browsing.

However, according to researchers at Imperva, the extension is actually conducting a deceptive ad-injection campaign that causes legitimate URLs to redirect to affiliate links controlled by the extension’s developers.

Ad injection is the process of inserting advertisements or links into a web page that doesn’t normally host them, allowing the scammers to make money from advertisements or redirect people to affiliate sites to earn commissions.
https://www.bleepstatic.com/images/news/u/1220909/Code%20and%20Details/Ad-Blocker-image-1-1024x419.png.jpg
In August 2021, Imperva’s researchers discovered a set of previously unknown malicious domains distributing an ad injection script.This malicious script would send legitimate URLs to a remote server and receive a list of redirection domains as a response. If a user clicks on an altered link, the user is redirected to a different page, typically, an affiliate link.

The ad-injecting script even features evasion techniques such as excluding large Russian search engines, clearing the debugging console every 100 ms, and active detection of initialized Firebug variables.

By taking a deeper look at AllBlock, Imperva’s team found the script they were hunting for in “bg.js,” which injects code into every new tab opened on the browser.
https://www.bleepstatic.com/images/news/u/1220909/Code%20and%20Details/Ad-blocker-image-4-1024x396.png.jpg
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cellent user reviews because its functionality as an adblocker has been properly implemented. Nonetheless, it introduces deception risks and confuses shoppers.
See Also: Hacking stories – Operation Aurora: When China hacked Google Source: www.bleepingcomputer.com (Click Link)Recent News* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/maxresdefault-90x90.jpg Brizy WordPress Plugin Exploit Chains Allow Full Site Takeovers1 day ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/abstract_mysterysnail-90x90.jpg Microsoft Kills Bug Being Exploited in MysterySnail Espionage Campaign2 days ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/apple-iphone-hacking-90x90.jpg Emergency Apple iOS 15.0.2 update fixes zero-day used in attacks3 days ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/Linux-1280x720-1-90x90.jpg FontOnLake malware infects Linux systems4 days ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/excel-header-90x90.jpg Microsoft is disabling Excel 4.0 macros by default to protect users7 days ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/ezgif.com-gif-maker-1-90x90.jpg Twitch source code and creator payouts part of massive leak1 week ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/Apache-web-server-90x90.png Apache fixes actively exploited zero-day vulnerability, patch now1 week ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/security-breach-freepik-90x90.jpg Encrypted & Fileless Malware Sees Big Growth1 week ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/Digital-Wallet-90x90.jpg MFA Glitch Leads to 6K+ Coinbase Customers Getting Robbed2 weeks ago
* https://www.blackhatethicalhacking.com/wp-content/uploads/2021/10/shutterstock_1156765921-900x506-1-90x90.jpg Google pushes emergency Chrome update to fix two zero-days2 weeks ago
The post Malicious Chrome ad blocker injects ads behind the scenes first appeared on Black Hat Ethical Hacking.

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Share 5,000,000 TOP in the TOP Mainnet Experience Week
https://medium.com/top-network/share-5-000-000-top-in-the-top-mainnet-experience-week-9f8e28b59034?source=rss------bug_bounty-5

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Round 2 Bounty Duration: October 20-November 4(SGT)Continue reading on TOP Network » (https://medium.com/top-network/share-5-000-000-top-in-the-top-mainnet-experience-week-9f8e28b59034?source=rss------bug_bounty-5)

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Share 5,000,000 TOP in the TOP Mainnet Experience Week

Round 2 Bounty Duration: October 20-November 4(SGT)Continue reading on TOP Network »
Read more...

hacking: security in practice
Should people be allowed to biohack their bodies with DIY cybernetic enhancements? (Survey)

I'm doing some research on DIY cybernetic implants. I believe your insights could be extremely helpful.

Here is the survey: https://form.typeform.com/to/djJUA4vD

The survey should take about 5 minutes.

I appreciate your help 🙏

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

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Hacking on Medium
Business Logic Vulnerabilities

https://cdn-images-1.medium.com/max/625/1*2rknqeU80IQccQBNJdjBrA.jpeg
How do Attackers Exploit Business Logic Problems?

Continue reading on Medium »

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Hacking on Medium
Password Policy Best Practices

https://cdn-images-1.medium.com/max/2600/1*6vl6VyzTmZYgtZtNj-jjlw.jpeg
In this article, we will discuss some “uncommon” password policy best practices, that are not followed by a lot of companies. Those are…

Continue reading on Medium »

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Networkit - A Growing Open-Source Toolkit For Large-Scale Network Analysis
http://www.kitploit.com/2021/10/networkit-growing-open-source-toolkit.html

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Requirements
You will need the following software to install NetworKit as a python package: A modern C++ compiler, e.g.: g++ (https://gcc.gnu.org/) (>= 6.1), clang++ (https://clang.llvm.org/) (>= 3.9) or MSVC (>= 14.13) OpenMP for parallelism (usually ships with the compiler) Python3 (3.6 or higher is supported) Development libraries for Python3. The package name depends on your distribution. Examples: Debian/Ubuntu: apt-get install python3-dev RHEL/CentOS: dnf install python3-devel Windows: Use the official release installer from www.python.org (https://www.python.org/downloads/windows/) Pip (https://pypi.python.org/pypi/pip) CMake (https://cmake.org/) version 3.6 or higher (Advised to use system packages if available. Alternative: pip3 install cmake) Build system: Make (https://www.gnu.org/software/make/) or Ninja (https://ninja-build.org/) Cython version 0.29 or higher (e.g., pip3 install cython)
Install
In order to use NetworKit, you can either install it via package managers or build the Python module from source.
Install via package manager
While the most recent version is in general available for all package managers, the number of older downloadable versions differ.
pip
pip3 install [--user] networkit

conda (channel conda-forge)
conda config --add channels conda-forge
conda install networkit [-c conda-forge]

brew
brew install networkit

spack
spack install py-networkit

Building the Python module from source
git clone https://github.com/networkit/networkit networkit
cd networkit
python3 setup.py build_ext [-jX]
pip3 install -e .
The script will call cmake and ninja (make as fallback) to compile NetworKit as a library, build the extensions and copy it to the top folder. By default, NetworKit will be built with the amount of available cores in optimized mode. It is possible the add the option -jN the number of threads used for compilation.
Usage example
To get an overview and learn about NetworKit's different functions/classes, have a look at our interactive notebooks-section (https://github.com/networkit/networkit/blob/master/notebooks/), especially the Networkit UserGuide (https://github.com/networkit/networkit/blob/master/notebooks/User-Guide.ipynb). Note: To view and edit the computed output from the notebooks, it is recommended to use Jupyter Notebook (https://jupyter.org/install.html). This requires the prior installation of NetworKit. You should really check that out before start working on your network analysis. We also provide a Binder-instance of our notebooks. To access (https://www.kitploit.com/search/label/Access) this service, you can either click on the badge at the top or follow this link (https://mybinder.org/v2/gh/networkit/networkit/master?urlpath=lab/tree/notebooks). Disclaimer: Due to rebuilds of the underlying image, it can takes some time until your Binder instance is ready for usage. If you only want to see in short how NetworKit is used - the following example provides a climpse at that. Here we generate a random hyperbolic graph with 100k nodes and compute its communities with the PLM method: >> import networkit as nk >>> g = nk.generators.HyperbolicGenerator(1e5).generate() >>> communities = nk.community.detectCommunities(g, inspect=True) PLM(balanced,pc,turbo) detected communities in 0.14577102661132812 [s] solution properties: ------------------- ----------- # communities 4536 min community size 1 max community size 2790 avg. community size 22.0459 modularity 0.987243 ------------------- ----------- ">>>> import networkit as nk
>>> g = nk.generators.HyperbolicGenerator(1e5).generate()
>>> communities = nk.community.detectCommunities(g, inspect=True)
PLM(balanced,pc,turbo) detected communities in 0.14577102661132812 [s]
solution properties:
------------------- -----------
# communities 4536
min community size 1
max community size 2790

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avg. community size 22.0459
modularity 0.987243
------------------- -----------

Install the C++ Core only
In case you only want to work with NetworKit's C++ core, you can either install it via package managers or build it from source.
Install C++ core via package manager

conda (channel conda-forge)
conda config --add channels conda-forge
conda install libnetworkit [-c conda-forge]

brew
brew install libnetworkit

spack
spack install libnetworkit

Building the C++ core from source
We recommend CMake (https://cmake.org/) and your preferred build system for building the C++ part of NetworKit. The following description shows how to use CMake (https://cmake.org/) in order to build the C++ Core only: First you have to create and change to a build directory: (in this case named build) mkdir build
cd build
Then call CMake (https://cmake.org/) to generate files for the make build system, specifying the directory of the root CMakeLists.txt file (e.g., ..). After this make is called to start the build process: cmake ..
make -jX
To speed up the compilation with make a multi-core machine, you can append -jX where X denotes the number of threads to compile with.
Use NetworKit as a library
This paragraph explains how to use the NetworKit core C++ library in case it has been built from source. For how to use it when installed via package managers, best refer to the official documentation (brew (https://brew.sh/), conda (https://docs.conda.io/), spack (https://spack.readthedocs.io/en/latest)). In order to use the previous compiled networkit library, you need to have it installed, and link it while compiling your project. Use these instructions to compile and install NetworKit in /usr/local: cmake ..
make -jX install
Once NetworKit has been installed, you can use include directives in your C++-application as follows: ">#include
You can compile your source as follows: g++ my_file.cpp -lnetworkit

Unit tests
Building and running NetworKit unit tests is not mandatory. However, as a developer you might want to write and run unit tests for your code, or if you experience any issues with NetworKit, you might want to check if NetworKit runs properly. The unit tests can only be run from a clone or copy of the repository and not from a pip installation. In order to run the unit tests, you need to compile them first. This is done by setting the CMake (https://cmake.org/) NETWORKI_BUILD_TESTS flag to ON: cmake -DNETWORKIT_BUILD_TESTS=ON ..
Unit tests are implemented using GTest macros such as TEST_F(CentralityGTest, testBetweennessCentrality). Single tests can be executed with: ./networkit_tests --gtest_filter=CentralityGTest.testBetweennessCentrality
Additionally, one can specify the level of the logs outputs by adding --loglevel ; supported log levels are: TRACE, DEBUG, INFO, WARN, ERROR, and FATAL.
Compiling with address/leak sanitizers
Sanitizers are great tools to debug your code. NetworKit provides additional Cmake (https://cmake.org/) flags to enable address, leak, and undefined behavior sanitizers. To compile your code with sanitizers, set the CMake (https://cmake.org/) NETWORKIT_WITH_SANITIZERS to either address or leak: cmake -DNETWORKIT_WITH_SANITIZERS=leak ..
By setting this flag to address, your code will be compiled with the address and the undefined sanitizers. Setting it to leak also adds the leak sanitizer.
Documentation
The most recent version of the documentation can be found online (https://networkit.github.io/dev-docs/index.html).
Contact
For questions regarding NetworKit, have a look at our issues-section (https://github.com/networkit/networkit/issues) and see if there is already an open discussion. If not feel free to open a new issue. To stay updated about this project, subscribe to our mailing list (https://sympa.cms.hu-berlin.de/sympa/subscribe/networkit).
Contributions

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We encourage contributions to the NetworKit source code. See the development guide (https://networkit.github.io/dev-docs/DevGuide.html#devGuide) for instructions. For support please contact the mailing list (https://sympa.cms.hu-berlin.de/sympa/subscribe/networkit).
Credits
List of contributors can be found on the NetworKit (https://networkit.github.io/credits.html)website (https://www.kitploit.com/search/label/Website) credits page.
External Code
The program source includes: the TLX (https://github.com/tlx/tlx/) library the TTMath (http://www.ttmath.org/) bignum library
License
The source code of this program is released under the MIT License (http://opensource.org/licenses/MIT). We ask you to cite us if you use this code in your project (c.f. the publications section below and especially the technical report (https://arxiv.org/abs/1403.3005)). Feedback is also welcome.
Publications
The NetworKit publications page (https://networkit.github.io/publications.html) lists the publications on NetworKit as a toolkit, on algorithms available in NetworKit, and simply using NetworKit. We ask you to cite the appropriate ones if you found NetworKit useful for your own research.

Download Networkit (https://github.com/networkit/networkit)

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Black Hat Ethical Hacking
Offensive Security Tool: Dalfox

https://www.blackhatethicalhacking.com/wp-content/uploads/2021/08/Untitled-design-2-1.png Offensive Security Tool: DalfoxPost Views: 23 https://www.blackhatethicalhacking.com/wp-content/uploads/2021/08/BECOME-A-PATRON-AND-UNLOCK-EXCLUSIVE-VIDEOS-1.png Reading Time: 5 Minutes

Offensive Security Tool: Dalfox GitHub Link What is DalFoxDalFox by hahwul, is a fast and powerful parameter analysis and XSS scanner, based on a golang/DOM parser. It supports friendly Pipeline, CI/CD and testing of different types of XSS. In regards to the naming: Dal(달) is the Korean pronunciation of moon and fox was made into Fox (Find Of XSS).

This tool is very powerful and fast. The fact that you can use piping and can chain several other tools using it, makes it really effective especially when you want to do your 1 liner attack, combining the recon process to it.

It also means that you can do things like 1 liner powerful attacks as a tip from BHEH:

cat “domain”.txt | gf xss | sed ‘s/=.*/=/’ | sed ‘s/URL: //’ | tee domain_temp_xss.txt | dalfox pipe -H “AuthToken: bbadsfkasdfadsf87”

Meaning you can chain several commands, and even find cross site scripting attacks (XSS) and more! Its highly customizable, so we recommend you check the complete documentation. TOC* Key features
* How to Install
* Usage
* POC format
* In the Code
* Screenshots
* Wiki
* Contribute
* Contributors
See Also: Malicious Chrome ad blocker injects ads behind the scenes Key featuresMode: url sxss pipe file server payload
Class Key Feature Description Discovery Parameter analysis – Find reflected param
– Find alive/bad special chars, event handler and attack code
– Identification of injection points(HTML/JS/Attribute)
inHTML-none inJS-none inJS-double inJS-single inJS-backtick inATTR-none inATTR-double inATTR-single Static analysis – Check bad-header like CSP, XFO, etc.. with req/res base BAV analysis – Testing BAV(Basic Another Vulnerability) , e.g sqli ssti open-redirects, crlf Parameter Mining – Find new param with Dictonary attack (default is GF-Patterns)- Support custom dictonary file (–mining-dict-word)
– Find new param with DOM
– Use remote wordlist to mining (–remote-wordlists) Built-in Grepping – It Identify the basic info leak of SSTi, Credential, SQL Error, and so on WAF Detection and Evasion – Detect to WAF(Web Application Firewall).
– if found waf and using special flag, evasion using slow request
– –waf-evasion Scanning XSS Scanning – Reflected XSS / Stored XSS / DOM XSS
– DOM base verifying
– Headless base verifying
– Blind XSS testing with param, header(-b , –blind options)
– Only testing selected parameters (-p, –param)
– Only testing parameter analysis (–only-discovery) Friendly Pipeline – Single url mode (dalfox url)
– From file mode (dalfox file urls.txt)
– From IO(pipeline) mode (dalfox pipe)
– From raw http request file mode (dalfox file raw.txt –rawdata) Optimizaion query of payloads – Check the injection point through abstraction and generated the fit payload.
– Eliminate unnecessary payloads based on badchar Encoder – All test payloads(build-in, your custom/blind) are tested in parallel with the encoder.
– To Double URL Encoder
– To HTML Hex Encoder Sequence – Auto-check the special page for stored xss (–trigger)
– Support (–sequence) options for Stored XSS , only sxss mode HTTP HTTP Options – Overwrite HTTP Method (-X, –method)
– Follow redirects (–follow-redirects)
– Add header (-H, –header)
– Add cookie (-C, –cookie)
– Add User-Agent (–user-agent)
– Set timeout (–timeout)
– Set Delay (–delay)
– Set Proxy (–proxy)
– Set ignore return codes (–ignore-return)
– Load cookie from raw request (–cookie-from-raw) Concurrency Worker – Set worker’s number(-w, –worker) N * hosts – Use multica[...]

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st mode (–multicast) , only file / pipe mode Output Output – Only the PoC code and useful information is write as Stdout
– Save output (-o, –output) Format – JSON / Plain (–format) Printing – Silence mode (–silence)
– You may choose not to print the color (–no-color)
– You may choose not to print the spinner (–no-spinner)
– You may choose show only special poc code (–only-poc) Extensibility REST API – API Server and Swagger (dalfox server) Payload Mode – Generate and Enumerate Payloads for XSS Testing (dalfox payload) Found Action – Lets you specify the actions to take when detected.
– Notify, for example (–found-action) Custom Grepping – Can grep with custom regular expressions on response
– If duplicate detection, it performs deduplication (–grep) Custom Payloads – Use custom payloads list file (–custom-payload)
– Custom alert value (–custom-alert-value)
– Custom alert type (–custom-alert-type) Remote Payloads – Use remote payloads from portswigger, payloadbox, etc.. (–remote-payloads) Package Package manager – pkg.go.dev
– homebrew with tap
– snapcraft Docker ENV – docker hub
– gitub package of docker Other – github action
And the various options required for the testing. How to InstallFrom sourcego1.17 go install github.com/hahwul/dalfox/v2@latest

go1.16 GO111MODULE=on go get github.com/hahwul/dalfox/v2 Using homebrew (macos)brew tap hahwul/dalfox
brew install dalfox Using snapcraft (ubuntu)sudo snap install dalfox More information? Please read Installation guide UsageModes:
file          Use file mode(targets list or rawdata)
help        Help about any command
payload   Payload mode, make and enum payloads
pipe        Use pipeline mode
server     Start API Server
sxss        Use Stored XSS mode
url          Use single target mode
version    Show version
Global Flags:
-b, –blind string                       Add your blind xss
* Example: -b hahwul.xss.ht
–config string Using config from file
-C,    –cookie string                    Add custom cookie
–cookie-from-raw string      Load cookie from burp raw http request
* Example: –cookie-from-raw request.txt
–custom-alert-type string       Change alert value type
* Example: –custom-alert-type=none / –custom-alert-type=str,none (default “none”)
–custom-alert-value string      Change alert value
* Example: –custom-alert-value=document.cookie (default “1”)
–custom-payload string          Add custom payloads from file
-d, –data string                          Using POST Method and add Body data
–debug                                 debug mode, save all log using -o option
–deep-domxss                       DOM XSS Testing with more payloads on headless [so slow]
–delay int                              Milliseconds between send to same host (1000==1s)
-F, –follow-redirects                     Following redirection
–format string                        Stdout output format
* Supported: plain / json (default “plain”)
–found-action string               If found weak/vuln, action(cmd) to next
* Example: –found-action=’./notify.sh’
–found-action-shell string       Select shell application for –found-action (default “bash”)
–grep string                          Using custom grepping file
* Example: –grep ./samples/sample_grep.json
-H, –header strings                     Add custom headers
–ignore-return string              Ignore scanning from return code
* Example: –ignore-return 302,403,404
-X, –method string                     Force overriding HTTP Method
* Example: -X PUT (default “GET”)
–mining-dict                        Find new parameter with dictionary attack, default is Gf-Patterns=>XSS (default true)
-W, –mining-dict-word string       Custom wordlist file for param mining
* Example: –mining-dict-word word.txt
–mining-dom                        Find new parameter in DOM (attribute/js value) (default true)
–no-color                              Not use coloriz[...]

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