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Pip-Intel is a powerful tool designed for OSINT (Open Source Intelligence) and cyber intelligence gathering activities. It consolidates various open-source tools into a single user-friendly interface simplifying the data collection and analysis processes for researchers and cybersecurity professionals.
Pip-Intel utilizes Python-written pip packages to gather information from various data points. This tool is equipped with the capability to collect detailed information through email addresses, phone numbers, IP addresses, and social media accounts. It offers a wide range of functionalities including email-based OSINT operations, phone number-based inquiries, geolocating IP addresses, social media and user analyses, and even dark web searches.
chaos is an 'origin' IP scanner developed by RST in collaboration with ChatGPT. It is a niche utility with an intended audience of mostly penetration testers and bug hunters.
An origin-IP is a term-of-art expression describing the final public IP destination for websites that are publicly served via 3rd parties. If you'd like to understand more about why anyone might be interested in Origin-IPs, please check out our blog post.
chaos was rapidly prototyped from idea to functional proof-of-concept in less than 24 hours using our principles of DevOps with ChatGPT.
FreshRSS 
usage: chaos.py [-h] -f FQDN -i IP [-a AGENT] [-C] [-D] [-j JITTER] [-o OUTPUT] [-p PORTS] [-P] [-r] [-s SLEEP] [-t TIMEOUT] [-T] [-v] [-x]
_..._
.-'` `'-.
__|___________|__
\ /
`._ CHAOS _.'
`-------`
/ \\
/ \\
/ \\
/ \\
/ \\
/ \\
/ \\
/ \\
/ \\
/_____________________\\
CHAtgpt Origin-ip Scanner
_______ _______ _______ _______ _______
|\\ /|\\ /|\\ /|\\ /|\\/|
| +---+ | +---+ | +---+ | +---+ | +---+ |
| |H | | |U | | |M | | |A | | |N | |
| |U | | |S | | |A | | |N | | |C | |
| |M | | |E | | |N | | |D | | |O | |
| |A | | |R | | |C | | | | | |L | |
| +---+ | +---+ | +---+ | +---+ | +---+ |
|/_____|\\_____|\\_____|\\_____|\\_____\\
Origin IP Scanner developed with ChatGPT
cha*os (n): complete disorder and confusion
(ver: 0.9.4)
cd path/to/chaospip3 install -U pip setuptools virtualenvvirtualenv envsource env/bin/activate(env) pip3 install -U -r ./requirements.txt(env) ./chaos.py -h-h, --help show this help message and exit
-f FQDN, --fqdn FQDN Path to FQDN file (one FQDN per line)
-i IP, --ip IP IP address(es) for HTTP requests (Comma-separated IPs, IP networks, and/or files with IP/network per line)
-a AGENT, --agent AGENT
User-Agent header value for requests
-C, --csv Append CSV output to OUTPUT_FILE.csv
-D, --dns Perform fwd/rev DNS lookups on FQDN/IP values prior to request; no impact to testing queue
-j JITTER, --jitter JITTER
Add a 0-N second randomized delay to the sleep value
-o OUTPUT, --output OUTPUT
Append console output to FILE
-p PORTS, --ports PORTS
Comma-separated list of TCP ports to use (default: "80,443")
-P, --no-prep Do not pre-scan each IP/port w ith `GET /` using `Host: {IP:Port}` header to eliminate unresponsive hosts
-r, --randomize Randomize(ish) the order IPs/ports are tested
-s SLEEP, --sleep SLEEP
Add N seconds before thread completes
-t TIMEOUT, --timeout TIMEOUT
Wait N seconds for an unresponsive host
-T, --test Test-mode; don't send requests
-v, --verbose Enable verbose output
-x, --singlethread Single threaded execution; for 1-2 core systems; default threads=(cores-1) if cores>2
Launch python HTTP server
% python3 -u -m http.server 8001
Serving HTTP on :: port 8001 (http://[::]:8001/) ...
Launch ncat as HTTP on a port detected as SSL; use a loop because --keep-open can hang
% while true; do ncat -lvp 8443 -c 'printf "HTTP/1.0 204 Plaintext OK\n\n<html></html>\n"'; done
Ncat: Version 7.94 ( https://nmap.org/ncat )
Ncat: Listening on [::]:8443
Ncat: Listening on 0.0.0.0:8443
Also launch ncat as SSL on a port that will default to HTTP detection
% while true; do ncat --ssl -lvp 8444 -c 'printf "HTTP/1.0 202 OK\n\n<html></html>\n"'; done
Ncat: Version 7.94 ( https://nmap.org/ncat )
Ncat: Generating a temporary 2048-bit RSA key. Use --ssl-key and --ssl-cert to use a permanent one.
Ncat: SHA-1 fingerprint: 0208 1991 FA0D 65F0 608A 9DAB A793 78CB A6EC 27B8
Ncat: Listening on [::]:8444
Ncat: Listening on 0.0.0.0:8444
Prepare an FQDN file:
% cat ../test_localhost_fqdn.txt
www.example.com
localhost.example.com
localhost.local
localhost
notreally.arealdomain
Prepare an IP file / list:
% cat ../test_localhost_ips.txt
127.0.0.1
127.0.0.0/29
not_an_ip_addr
-6.a
=4.2
::1
Run the scan
% ./chaos.py -f ../test_localhost_fqdn.txt -i ../test_localhost_ips.txt,::1/126 -p 8001,8443,8444 -x -s0.2 -t1
2023-06-21 12:48:33 [WARN] Ignoring invalid FQDN value: localhost.local
2023-06-21 12:48:33 [WARN] Ignoring invalid FQDN value: localhost
2023-06-21 12:48:33 [WARN] Ignoring invalid FQDN value: notreally.arealdomain
2023-06-21 12:48:33 [WARN] Error: invalid IP address or CIDR block =4.2
2023-06-21 12:48:33 [WARN] Error: invalid IP address or CIDR block -6.a
2023-06-21 12:48:33 [WARN] Error: invalid IP address or CIDR block not_an_ip_addr
2023-06-21 12:48:33 [INFO] * ---- <META> ---- *
2023-06-21 12:48:33 [INFO] * Version: 0.9.4
2023-06-21 12:48:33 [INFO] * FQDN file: ../test_localhost_fqdn.txt
2023-06-21 12:48:33 [INFO] * FQDNs loaded: ['www.example.com', 'localhost.example.com']
2023-06-21 12:48:33 [INFO] * IP input value(s): ../test_localhost_ips.txt,::1/126
2023-06-21 12:48:33 [INFO] * Addresses pars ed from IP inputs: 12
2023-06-21 12:48:33 [INFO] * Port(s): 8001,8443,8444
2023-06-21 12:48:33 [INFO] * Thread(s): 1
2023-06-21 12:48:33 [INFO] * Sleep value: 0.2
2023-06-21 12:48:33 [INFO] * Timeout: 1.0
2023-06-21 12:48:33 [INFO] * User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.80 Safari/537.36 ch4*0s/0.9.4
2023-06-21 12:48:33 [INFO] * ---- </META> ---- *
2023-06-21 12:48:33 [INFO] 36 unique address/port addresses for testing
Prep Tests: 100%|█████████████████████████████████████████████████████████████████&# 9608;██████████████████████████████████████████████████████████████████████████████| 36/36 [00:29<00:00, 1.20it/s]
2023-06-21 12:49:03 [INFO] 9 IP/ports verified, reducing test dataset from 72 entries
2023-06-21 12:49:03 [INFO] 18 pending tests remain after pre-testing
2023-06-21 12:49:03 [INFO] Queuing 18 threads
++RCVD++ (200 OK) www.example.com @ :::8001
++RCVD++ (204 Plaintext OK) www.example.com @ :::8443
++RCVD++ (202 OK) www.example.com @ :::8444
++RCVD++ (200 OK) www.example.com @ ::1:8001
++RCVD++ (204 Plaintext OK) www.example.com @ ::1:8443
++RCVD++ (202 OK) www.example.com @ ::1:8444
++RCVD++ (200 OK) www.example.com @ 127.0.0.1:8001
++RCVD++ (204 Plaintext OK) www.example.com @ 127.0.0.1:8443
++RCVD++ (202 OK) www.example.com @ 127.0.0.1:8444
++RCVD++ (200 OK) localhost.example.com @ :::8001
++RCVD++ (204 Plaintext OK) localhost.example.com @ :::8443
++RCVD+ + (202 OK) localhost.example.com @ :::8444
++RCVD++ (200 OK) localhost.example.com @ ::1:8001
++RCVD++ (204 Plaintext OK) localhost.example.com @ ::1:8443
++RCVD++ (202 OK) localhost.example.com @ ::1:8444
++RCVD++ (200 OK) localhost.example.com @ 127.0.0.1:8001
++RCVD++ (204 Plaintext OK) localhost.example.com @ 127.0.0.1:8443
++RCVD++ (202 OK) localhost.example.com @ 127.0.0.1:8444
Origin Scan: 100%|█████████████████████████████████████████████████████████████████████████████████████` 08;█████████████████████████████████████████████████████████| 18/18 [00:06<00:00, 2.76it/s]
2023-06-21 12:49:09 [RSLT] Results from 5 FQDNs:
::1
::1:8444 => (202 / OK)
::1:8443 => (204 / Plaintext OK)
::1:8001 => (200 / OK)
127.0.0.1
127.0.0.1:8001 => (200 / OK)
127.0.0.1:8443 => (204 / Plaintext OK)
127.0.0.1:8444 => (202 / OK)
::
:::8001 => (200 / OK)
:::8443 => (204 / Plaintext OK)
:::8444 => (202 / OK)
www.example.com
:::8001 => (200 / OK)
:::8443 => (204 / Plaintext OK)
:::8444 => (202 / OK)
::1:8001 => (200 / OK)
::1:8443 => (204 / Plaintext OK)
::1:8444 => (202 / OK)
127.0.0.1:8001 => (200 / OK)
127.0.0.1:8443 => (204 / Plaintext OK)
127.0.0.1:8444 => (202 / OK)
localhost.example.com
:::8001 => (200 / OK)
:::8443 => (204 / Plaintext OK)
:::8444 => (202 / OK)
::1:8001 => (200 / OK)
::1:8443 => (204 / Plaintext OK)
::1:8444 => (202 / OK)
127.0.0.1:8001 => (200 / OK)
127.0.0.1:8443 => (204 / Plaintext OK)
127.0.0.1:8444 => (202 / OK)
rst@r57 chaos %
-T runs in test mode (do everything except send requests)
-v verbose option provides additional output
An advance cross-platform and multi-feature GUI web spider/crawler for cyber security proffesionals. Spider Suite can be used for attack surface mapping and analysis. For more information visit SpiderSuite's website.
Spider Suite is designed for easy installation and usage even for first timers.
First, download the package of your choice.
Then install the downloaded SpiderSuite package.
See First time crawling with SpiderSuite article for tutorial on how to get started.
For complete documentation of Spider Suite see wiki.
Can you translate?
Visit SpiderSuite's translation project to make translations to your native language.
Not a developer?
You can help by reporting bugs, requesting new features, improving the documentation, sponsoring the project & writing articles.
For More information see contribution guide.
Contributers
This product includes software developed by the following open source projects:
A multi-purpose toolkit for gathering and managing OSINT-Data with a neat web-interface.
Seekr is a multi-purpose toolkit for gathering and managing OSINT-data with a sleek web interface. The backend is written in Go and offers a wide range of features for data collection, organization, and analysis. Whether you're a researcher, investigator, or just someone looking to gather information, seekr makes it easy to find and manage the data you need. Give it a try and see how it can streamline your OSINT workflow!
Check the wiki for setup guide, etc.
Seekr combines note taking and OSINT in one application. Seekr can be used alongside your current tools. Seekr is desingned with OSINT in mind and optimized for real world usecases.
Download the latest exe here
Download the latest stable binary here
To install seekr on linux simply run:
git clone https://github.com/seekr-osint/seekr
cd seekr
go run main.goNow open the web interface in your browser of choice.
Seekr is build with NixOS in mind and therefore supports nix flakes. To run seekr on NixOS run following commands.
nix shell github:seekr-osint/seekr
seekrjourney
title How to Intigrate seekr into your current workflow.
section Initial Research
Create a person in seekr: 100: seekr
Simple web research: 100: Known tools
Account scan: 100: seekr
section Deeper account investigation
Investigate the accounts: 100: seekr, Known tools
Keep notes: 100: seekr
section Deeper Web research
Deep web research: 100: Known tools
Keep notes: 100: seekr
section Finishing the report
Export the person with seekr: 100: seekr
Done.: 100
We would love to hear from you. Tell us about your opinions on seekr. Where do we need to improve?... You can do this by just opeing up an issue or maybe even telling others in your blog or somewhere else about your experience.
This tool is intended for legitimate and lawful use only. It is provided for educational and research purposes, and should not be used for any illegal or malicious activities, including doxxing. Doxxing is the practice of researching and broadcasting private or identifying information about an individual, without their consent and can be illegal. The creators and contributors of this tool will not be held responsible for any misuse or damage caused by this tool. By using this tool, you agree to use it only for lawful purposes and to comply with all applicable laws and regulations. It is the responsibility of the user to ensure compliance with all relevant laws and regulations in the jurisdiction in which they operate. Misuse of this tool may result in criminal and/or civil prosecut ion.
This is a Proof Of Concept application that demostrates how AI can be used to generate accurate results for vulnerability analysis and also allows further utilization of the already super useful ChatGPT.
openai.api_key = "__API__KEY" # Enter your API keypip3 install -r requirements.txt
or
pip install -r requirements.txtSupported in both windows and linux
Profiles:
| Parameter | Return data | Description | Nmap Command |
|---|---|---|---|
p1 | json | Effective Scan | -Pn -sV -T4 -O -F |
p2 | json | Simple Scan | -Pn -T4 -A -v |
p3 | json | Low Power Scan | -Pn -sS -sU -T4 -A -v |
p4 | json | Partial Intense Scan | -Pn -p- -T4 -A -v |
p5 | json | Complete Intense Scan | -Pn -sS -sU -T4 -A -PE -PP -PS80,443 -PA3389 -PU40125 -PY -g 53 --script=vuln |
The profile is the type of scan that will be executed by the nmap subprocess. The Ip or target will be provided via argparse. At first the custom nmap scan is run which has all the curcial arguments for the scan to continue. nextly the scan data is extracted from the huge pile of data which has been driven by nmap. the "scan" object has a list of sub data under "tcp" each labled according to the ports opened. once the data is extracted the data is sent to openai API davenci model via a prompt. the prompt specifically asks for an JSON output and the data also to be used in a certain manner.
The entire structure of request that has to be sent to the openai API is designed in the completion section of the Program.
def profile(ip):
nm.scan('{}'.format(ip), arguments='-Pn -sS -sU -T4 -A -PE -PP -PS80,443 -PA3389 -PU40125 -PY -g 53 --script=vuln')
json_data = nm.analyse_nmap_xml_scan()
analize = json_data["scan"]
# Prompt about what the quary is all about
prompt = "do a vulnerability analysis of {} and return a vulnerabilty report in json".format(analize)
# A structure for the request
completion = openai.Completion.create(
engine=model_engine,
prompt=prompt,
max_tokens=1024,
n=1,
stop=None,
)
response = completion.choices[0].text
return response
AzureGraph is an Azure AD information gathering tool over Microsoft Graph.
Thanks to Microsoft Graph technology, it is possible to obtain all kinds of information from Azure AD, such as users, devices, applications, domains and much more.
This application, allows you to query this data through the API in an easy and simple way through a PowerShell console. Additionally, you can download all the information from the cloud and use it completely offline.
It's recommended to clone the complete repository or download the zip file.
You can do this by running the following command:
git clone https://github.com/JoelGMSec/AzureGraph
.\AzureGraph.ps1 -h
_ ____ _
/ \ _____ _ _ __ ___ / ___|_ __ __ _ _ __ | |__
/ _ \ |_ / | | | '__/ _ \ | _| '__/ _' | '_ \| '_ \
/ ___ \ / /| |_| | | | __/ |_| | | | (_| | |_) | | | |
/_/ \_\/___|\__,_|_| \___|\____|_| \__,_| .__/|_| |_|
|_|
-------------------- by @JoelGMSec --------------------
Info: This tool helps you to obtain information from Azure AD
like Users or Devices, using de Microsft Graph REST API
Usage: .\AzureGraph.ps1 -h
Show this help, more info on my blog: darkbyte.net
.\AzureGraph.ps1
Execute AzureGraph in fully interactive mode
Warning: You need previously generated MS Graph token to use it
You can use a refresh token too, or generate a new one
https://darkbyte.net/azuregraph-enumerando-azure-ad-desde-microsoft-graph
This project is licensed under the GNU 3.0 license - see the LICENSE file for more details.
This tool has been created and designed from scratch by Joel Gámez Molina // @JoelGMSec
This software does not offer any kind of guarantee. Its use is exclusive for educational environments and / or security audits with the corresponding consent of the client. I am not responsible for its misuse or for any possible damage caused by it.
For more information, you can find me on Twitter as @JoelGMSec and on my blog darkbyte.net.
