KitPloit - PenTest Tools!
FindUncommonShares - A Python Equivalent Of PowerView's Invoke-ShareFinder.ps1 Allowing To Quickly Find Uncommon Shares In Vast Windows Domains

https://blogger.googleusercontent.com/img/a/AVvXsEgfoW7Db08N9MM7hMlq9ztJEYDQhJTIs1LZBJNTskWE6QOiGCLbnynxr5XRFSIhDc28tWofeG9xhz5kB5qaC9m1lBipIYeYn4bxGEn0Te66zjTl0UZRlv6z2bcb7UGvRtgWkKqoO39vl7wzyf6A3a0CTcydRh5liLjwLx2EzEMHxeghnpa3w23KLU1UKA=w640-h356 The script FindUncommonShares.py is a Python equivalent of PowerView's Invoke-ShareFinder.ps1 allowing to quickly find uncommon shares in vast Windows Active Directory Domains. Features* Only requires a low privileges domain user account.
* Automatically gets the list of all computers from the domain controller's LDAP.
* Ignore the hidden shares (ending with $) with --ignore-hidden-shares.
* Multithreaded connections to discover SMB shares.
* Export results in JSON with IP, name, comment, flags and UNC path with --export-json <file.json.
* Export results in XLSX with IP, name, comment, flags and UNC path with --export-xlsx <file.xlsx.
* Export results in SQLITE3 with IP, name, comment, flags and UNC path with --export-sqlite <file.db.
* Iterate on LDAP result pages to get every computer of the domain, no matter the size. Usage$ ./FindUncommonShares.py -h
FindUncommonShares v2.4 - by @podalirius_

usage: FindUncommonShares.py [-h] [--use-ldaps] [-q] [--debug] [-no-colors] [-I] [-t THREADS] [--export-xlsx EXPORT_XLSX] [--export-json EXPORT_JSON] [--export-sqlite EXPORT_SQLITE] --dc-ip ip address [-d DOMAIN] [-u USER]
[--no-pass | -p PASSWORD | -H [LMHASH:]NTHASH | --aes-key hex key] [-k]

Find uncommon SMB shares on remote machines.

optional arguments:
-h, --help show this help message and exit
--use-ldaps Use LDAPS instead of LDAP
-q, --quiet Show no information at all.
--debug Debug mode.
-no-colors Disables colored output mode
-I, --ignore-hidden-shares
Ignores hidden shares (shares ending with $)
-t THREADS, --threads THREADS
Number of threads (default: 20)

Output fi les:
--export-xlsx EXPORT_XLSX
Output XLSX file to store the results in.
--export-json EXPORT_JSON
Output JSON file to store the results in.
--export-sqlite EXPORT_SQLITE
Output SQLITE3 file to store the results in.

Authentication & connection:
--dc-ip ip address IP Address of the domain controller or KDC (Key Distribution Center) for Kerberos. If omitted it will use the domain part (FQDN) specified in the identity parameter
-d DOMAIN, --domain DOMAIN
(FQDN) domain to authenticate to
-u USER, --user USER user to authenticate with

Credentials:
--no-pass Don't ask for password (useful for -k)
-p PASSWORD, --password PASSWORD
Password to authenticate w ith
-H [LMHASH:]NTHASH, --hashes [LMHASH:]NTHASH
NT/LM hashes, format is LMhash:NThash
--aes-key hex key AES key to use for Kerberos Authentication (128 or 256 bits)
-k, --kerberos Use Kerberos authentication. Grabs credentials from .ccache file (KRB5CCNAME) based on target parameters. If valid credentials cannot be found, it will use the ones specified in the command line Examples :$ ./FindUncommonShares.py -u 'user1' -d 'LAB.local' -p 'P@ssw0rd!' --dc-ip 192.168.2.1
FindUncommonShares v2.3 - by @podalirius_

[>] Extracting all computers ...
[+] Found 2 computers.

[>] Enumerating shares ...
[>] Found 'Users' on 'DC01.LAB.local'
[>] Found 'WeirdShare' on 'DC01.LAB.local' (comment: 'Test comment')
[>] Found 'AnotherShare' on 'PC01.LAB.local'
[>] Found 'Users' on 'PC01.LAB.local
$ Each JSON entry looks like this: {
"computer": {
"fqdn": "DC01.LAB.local",
"ip": "192.168.1.1"
},
"share": {
"name": "ADMIN$",
"comment": "Remote Admin",
"hidden": true,
"uncpath": "\\\\192.168.1.46\\ADMIN$\\",
"type": {
"stype_value": 2147483648,
"stype_flags": [
"STYPE_DISKTREE",
"STYPE_TEMPORARY"
]
}
}
}Credits* Feature suggested in impacket issue #1176 by @CaledoniaProject Download FindUncommonShares

Hacking on Medium
SQL Injection (the_coding_hacker)

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WindowInjector Malware Tool

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Introduction

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ChatGPT, AI, and Companies’ 2023 Cybersecurity Challenges and Impact

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Insights on ChatGPT and the Evolving Cybersecurity Threat Landscape and Strategies for Companies in 2023.

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Hacking on Medium
How to create a RAT payload using msfvenom

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This article is written for educational purposes only

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Hacking on Medium
Hack The Box Templated Challenge Writeup

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Açıklama: Selam arkadaşlar, Hack the Box platformunda bulunan ‘Templated’ isimli challenge çözümünü sizinle paylaşıyor olacağım. Burada…

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hacking: security in practice
Machines abroad

Are chinese or russian machines ( webservers vulnerable computers ,routers etc) configured in their respective languages ?

Would you see Cyrillic if you got root privileges on a russian server or chinese characters on one of theirs on the command line?

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hacking: security in practice
Festival Wrist band cloning. Possible?

I have 2 wristbands registered and activated and 2 that haven't. (Ultra Music Festival)

Can we clone and use the active ones with a reader/writer?

​

They don't require you to scan out of an area, only to get in. I would assume it's not as easy as just copying the RFID chip in the band, or is it?

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Wifi_Db - Script To Parse Aircrack-ng Captures To A SQLite Database
http://www.kitploit.com/2023/03/wifidb-script-to-parse-aircrack-ng.html

Script to parse Aircrack-ng (https://www.kitploit.com/search/label/Aircrack-ng) captures into a SQLite database and extract useful information like handshakes (in 22000 hashcat format), MGT identities, interesting relations between APs, clients and it's Probes, WPS information and a global view of all the APs seen. _ __ _ _ _
__ __(_) / _|(_) __| || |__
\ \ /\ / /| || |_ | | / _` || '_ \
\ V V / | || _|| | | (_| || |_) |
\_/\_/ |_||_| |_| _____ \__,_||_.__/
|_____|
by r4ulcl
Features Displays if a network is cloaked (hidden) even if you have the ESSID. Shows a detailed table of connected clients and their respective APs. Identifies client probes connected to APs, providing insight into potential security risks usin Rogue APs. Extracts handshakes for use with hashcat, facilitating password cracking. Displays identity information from enterprise networks, including the EAP method used for authentication. Generates a summary of each AP group by ESSID and encryption, giving an overview of the security status of nearby networks. Provides a WPS info table for each AP, detailing information about the Wi-Fi Protected Setup configuration of the network. Logs all instances when a client or AP has been seen with the GPS data and timestamp, enabling location-based analysis. Upload files with capture folder or file. This option supports the use of wildcards (*) to select multiple files or folders. Docker version in Docker Hub to avoid dependencies. Obfuscated mode for demonstrations and conferences. Possibility to add static GPS data. Install From DockerHub (https://hub.docker.com/r/r4ulcl/wifi_db) (RECOMMENDED) docker pull r4ulcl/wifi_db Manual installation Debian based systems (Ubuntu, Kali, Parrot, etc.) Dependencies: python3 python3-pip tshark hcxtools sudo apt install tshark
sudo apt install python3 python3-pip

git clone https://github.com/ZerBea/hcxtools.git
cd hcxtools
make
sudo make install
cd .. Installation git clone https://github.com/r4ulcl/wifi_db
cd wifi_db
pip3 install -r requirements.txt Arch Dependencies: python3 python3-pip tshark hcxtools sudo pacman -S wireshark-qt
sudo pacman -S python-pip python

git clone https://github.com/ZerBea/hcxtools.git
cd hcxtools
make
sudo make install
cd .. Installation git clone https://github.com/r4ulcl/wifi_db
cd wifi_db
pip3 install -r requirements.txt Usage Scan with airodump-ng Run airodump-ng (https://www.kitploit.com/search/label/Airodump-ng) saving the output with -w: sudo airodump-ng wlan0mon -w scan --manufacturer --wps --gpsd Create the SQLite database using Docker #Folder with captures
CAPTURESFOLDER=/home/user/wifi

# Output database
touch db.SQLITE

docker run -t -v $PWD/db.SQLITE:/db.SQLITE -v $CAPTURESFOLDER:/captures/ r4ulcl/wifi_db -v $PWD/db.SQLITE:/db.SQLITE: To save de output in current folder db.SQLITE file -v $CAPTURESFOLDER:/captures/: To share the folder with the captures with the docker

Create the SQLite database using manual installation Once the capture is created, we can create the database by importing the capture. To do this, put the name of the capture without format. python3 wifi_db.py scan-01 In the event that we have multiple captures we can load the folder in which they are directly. And with -d we can rename the output database. python3 wifi_db.py -d database.sqlite scan-folder

Open database The database can be open with: sqlitebrowser (https://sqlitebrowser.org/)