hacking: security in practice
Public Wifi

Hello everyone. Little do I know about hacking but 1 thing I'm staying away from is public Wifi.

It made me curios how "safe" it is if I'm connected to someone's Mobile Hotspot that's connected to a public wifi.

I'm feeling that it would most likely be the same as if I'm directly connected to the wifi but I was wondering if access to my device would be a bit harder to obtain

submitted by /u/DoongoLoongo
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Kali Linux Tutorials
Tracgram : Use Instagram location features to track an account

TrackgramUse Instagram location features to track an account.

Usage
At this moment the usage of Trackgram is extremly simple:

1. Download this repository

2. Go through the instalation steps

3. Change the parameters in the tracgram main method directly:
+ Mandatory:
- NICKNAME: your username on Instagram
- PASSWORD: your instagram password
- OBJECTIVE: your objective username

+ Optional:
- path_to_csv: the path were the csv file will be stored, including the name


4. Execute it with python3 tracgram.py


Installation steps

1. Download with $ git clone https://github.com/initzerCreations/Tracgram
2. Install dependencies using pip install -r requirements.txt
3. Congrats! by now you should be able to run it: python3 tracgram.py

Screenshots
https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhG1c9MIh7Cb90yGsQAQmwnKwU8Olo6p0-PQw-BrRnbcwQQQ4Wv1xs4xTJ4T5GRKkS-tLbspzBeIZCEOMxzvIcvCvbw3SXwahLVFV4AshsESpdhtgPy608KRhUay7WOIhYTKIP6iLAMBpjyrY6KPy0spSCyo4Gg-t68fk3_2XZRwRN1sZj4BHhCMAJp/s16000/heatmap.png

https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjIZqpY1iIcTwoDfYLAfbOhIrs6lxuDXyXEXWqXA8hPrsBkQUCubymoafJWCUeFMzM7yEnD-yhMnexOSen6N9RIdcIF1xiE8UlFJ4AXNB-rpVGBKeZ7tVZMexnWuc64bha8XX29EdbxrpdBG3S_uBu0nRq7lmAhZisY54sgAK8j81rBVpHDe7gZJxa7/s16000/markers.png https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxh5DYaEnSTnRnym0IKFLK3yeG_hioCe5fimAEFtisRgItmRmQ6Zyj2Fu9ebJQ_hZRpGq2-zSjckhziA83XFbgagbEtyec2lNdkk8pY_4bguh0Nq8kq9GA4h7To_RDVCeFTevV5ZTxXBQS9oB5XS78RDZ130roWDNcBqLTbZehMFIubYCPDJ9Tg0dS/s16000/posts_per_location.png
Features

1. Provides a heatmap based on the location frequency
2. Markers displayed on the heatmap indicating:
* Exact location name
* Time when relate post was made
* Link to Google Maps address

3. Graph relating the posts count for an specific location
4. Generate a easy to process .CSV file
Click Here To Download

Directory Traversal and LFI worth $400
https://medium.com/@hritkmjth/directory-traversal-and-lfi-worth-400-c4422785d3bd?source=rss------bug_bounty-5

A Directory Traversal and Local File Inclusion bug couldn’t be simpler than this, which eventually led to a bounty worth $400.Continue reading on Medium » (https://medium.com/@hritkmjth/directory-traversal-and-lfi-worth-400-c4422785d3bd?source=rss------bug_bounty-5)

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

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This article is written for educational purposes only

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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?

submitted by /u/Old_Trash_4340
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