{"id":600,"date":"2025-04-19T10:57:46","date_gmt":"2025-04-19T10:57:46","guid":{"rendered":"http:\/\/localhost\/?p=600"},"modified":"2025-04-19T10:57:46","modified_gmt":"2025-04-19T10:57:46","slug":"pano-advanced-osint-investigation-platform-combining-graph-visualization-timeline-analysis-and-ai-as","status":"publish","type":"post","link":"https:\/\/zero.redgem.net\/?p=600","title":{"rendered":"PANO – Advanced OSINT Investigation Platform Combining Graph Visualization, Timeline Analysis, And AI Assistance To Uncover Hidden Connections In Data"},"content":{"rendered":"
\n

Vulnerability Details<\/h2>\n
\n

Basic Information<\/h3>\n\n\n\n\n\n\n
Title<\/th>\nPANO – Advanced OSINT Investigation Platform Combining Graph Visualization, Timeline Analysis, And AI Assistance To Uncover Hidden Connections In Data<\/td>\n<\/tr>\n
Type<\/th>\nkitploit<\/td>\n<\/tr>\n
Published<\/th>\n2025-04-17T19:48:00<\/td>\n<\/tr>\n
Last Seen<\/th>\n2025-04-17T19:58:55<\/td>\n<\/tr>\n
CVSS Score<\/th>\n0.0 ()<\/td>\n<\/tr>\n<\/table><\/div>\n
\n

CVSS v3 Details<\/h3>\n\n\n\n\n\n\n\n\n\n
Attack Vector<\/th>\n<\/td>\n<\/tr>\n
Attack Complexity<\/th>\n<\/td>\n<\/tr>\n
Privileges Required<\/th>\n<\/td>\n<\/tr>\n
User Interaction<\/th>\n<\/td>\n<\/tr>\n
Scope<\/th>\n<\/td>\n<\/tr>\n
Confidentiality Impact<\/th>\n<\/td>\n<\/tr>\n
Integrity Impact<\/th>\n<\/td>\n<\/tr>\n
Availability Impact<\/th>\n<\/td>\n<\/tr>\n<\/table><\/div>\n
\n

CVE Information<\/h3>\n\n\n\n\n
CVE IDs<\/th>\n<\/td>\n<\/tr>\n
CWE<\/th>\n<\/td>\n<\/tr>\n
Bulletin Family<\/th>\ntools<\/td>\n<\/tr>\n<\/table><\/div>\n
\n

Description<\/h3>\n
\n ![](https:\/\/blogger.googleusercontent.com\/img\/a\/AVvXsEi-GNkZ9AQKBUuEi_hbgq_mCfNERx02d3ANc-wURH6kRZXWnpTlPksoR_Bv45npcp1roIpGm6WHUeIuNBz0durnjsKgzGqp0K-0MQiyTyhpX0cBoGDPKbtjJvLS75f7Pb9x4ZA8B5Tz2Izs9QeXFJEqkRcc4B_9FzTELkeDujjNh0Z855ZsDT42W79ApnU=w640-h356)<\/p>\n

**PANO** is a powerful OSINT investigation platform that combines graph visualization, timeline analysis, and AI-powered tools to help you uncover hidden connections and patterns in your data. <\/p>\n

## Getting Started<\/p>\n

1. Clone the repository: `bash git clone https:\/\/github.com\/ALW1EZ\/PANO.git cd PANO`<\/p>\n

2. Run the application:<\/p>\n

3. Linux: `.\/start_pano.sh`
\n 4. Windows: `start_pano.bat`<\/p>\n

The startup script will automatically: – Check for updates – Set up the Python environment – Install dependencies – Launch PANO<\/p>\n

In order to use Email Lookup transform You need to login with GHunt first. After starting the pano via starter scripts;<\/p>\n

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

## \ud83d\udca1 Quick Start Guide<\/p>\n

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

## \ud83d\udd0d Features<\/p>\n

### \ud83d\udd78\ufe0f Core Functionality<\/p>\n

* **Interactive Graph Visualization**
\n * Drag-and-drop entity creation
\n * Multiple layout algorithms (Circular, Hierarchical, Radial, Force-Directed)
\n * Dynamic relationship mapping
\n * Visual node and edge styling<\/p>\n

* **TimelineAnalysis**<\/p>\n

* Chronological event visualization
\n * Interactive timeline navigation
\n * Event filtering and grouping
\n * Temporal relationship analysis<\/p>\n

* **Map Integration**<\/p>\n

* Geographic data visualization
\n * Location-based analysis
\n * Interactive mapping features
\n * Coordinate plotting and tracking<\/p>\n

### \ud83c\udfaf Entity Management<\/p>\n

* **Supported Entity Types**
\n * \ud83d\udce7 Email addresses
\n * \ud83d\udc64 Usernames
\n * \ud83c\udf10 Websites
\n * \ud83d\uddbc\ufe0f Images
\n * \ud83d\udccd Locations
\n * \u23f0 Events
\n * \ud83d\udcdd Text content
\n * \ud83d\udd27 Custom entity types<\/p>\n

### \ud83d\udd04 Transform System<\/p>\n

* **Email Analysis**
\n * Google account investigation
\n * Calendar event extraction
\n * Location history analysis
\n * Connected services discovery<\/p>\n

* **Username Analysis**<\/p>\n

* Cross-platform username search
\n * Social media profile discovery
\n * Platform correlation
\n * Web presence analysis<\/p>\n

* **Image Analysis**<\/p>\n

* Reverse image search
\n * Visual content analysis
\n * Metadata extraction
\n * Related image discovery<\/p>\n

### \ud83e\udd16 AI Integration<\/p>\n

* **PANAI**
\n * Natural language investigation assistant
\n * Automated entity extraction and relationship mapping
\n * Pattern recognition and anomaly detection
\n * Multi-language support
\n * Context-aware suggestions
\n * Timeline and graph analysis<\/p>\n

## \ud83e\udde9 Core Components<\/p>\n

### \ud83d\udce6 Entities<\/p>\n

Entities are the fundamental building blocks of PANO. They represent distinct pieces of information that can be connected and analyzed:<\/p>\n

* **Built-in Types**
\n * \ud83d\udce7 Email: Email addresses with service detection
\n * \ud83d\udc64 Username: Social media and platform usernames
\n * \ud83c\udf10 Website: Web pages with metadata
\n * \ud83d\uddbc\ufe0f Image: Images with EXIF and analysis
\n * \ud83d\udccd Location: Geographic coordinates and addresses
\n * \u23f0 Event: Time-based occurrences
\n * \ud83d\udcdd Text: Generic text content<\/p>\n

* **Properties System**<\/p>\n

* Type-safe property validation
\n * Automatic property getters
\n * Dynamic property updates
\n * Custom property types
\n * Metadata support<\/p>\n

### \u26a1 Transforms<\/p>\n

Transforms are automated operations that process entities to discover new information and relationships:<\/p>\n

* **Operation Types**
\n * \ud83d\udd0d Discovery: Find new entities from existing ones
\n * \ud83d\udd17 Correlation: Connect related entities
\n * \ud83d\udcca Analysis: Extract insights from entity data
\n * \ud83c\udf10 OSINT: Gather open-source intelligence
\n * \ud83d\udd04 Enrichment: Add data to existing entities<\/p>\n

* **Features**<\/p>\n

* Async operation support
\n * Progress tracking
\n * Error handling
\n * Rate limiting
\n * Result validation<\/p>\n

### \ud83d\udee0\ufe0f Helpers<\/p>\n

Helpers are specialized tools with dedicated UIs for specific investigation tasks:<\/p>\n

* **Available Helpers**
\n * \ud83d\udd0d Cross-Examination: Analyze statements and testimonies
\n * \ud83d\udc64 Portrait Creator: Generate facial composites
\n * \ud83d\udcf8 Media Analyzer: Advanced image processing and analysis
\n * \ud83d\udd0d Base Searcher: Search near places of interest
\n * \ud83d\udd04 Translator: Translate text between languages<\/p>\n

* **Helper Features**<\/p>\n

* Custom Qt interfaces
\n * Real-time updates
\n * Graph integration
\n * Data visualization
\n * Export capabilities<\/p>\n

## \ud83d\udc65 Contributing<\/p>\n

We welcome contributions! To contribute to PANO:<\/p>\n

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

> **Note** : We use a single `main` branch for development. All pull requests should be made directly to `main`.<\/p>\n

## \ud83d\udcd6 Development Guide<\/p>\n

Click to expand development documentation ### System Requirements – Operating System: Windows or Linux – Python 3.11+ – PySide6 for GUI – Internet connection for online features ### Custom Entities Entities are the core data structures in PANO. Each entity represents a piece of information with specific properties and behaviors. To create a custom entity: 1. Create a new file in the `entities` folder (e.g., `entities\/phone_number.py`) 2. Implement your entity class: <\/p>\n

from dataclasses import dataclass
\n from typing import ClassVar, Dict, Any
\n from .base import Entity <\/p>\n

@dataclass
\n class PhoneNumber(Entity):
\n name: ClassVar[str] = “Phone Number”
\n description: ClassVar[str] = “A phone number entity with country code and validation” <\/p>\n

def init_properties(self):
\n “””Initialize phone number properties”””
\n self.setup_properties({
\n “number”: str,
\n “country_code”: str,
\n “carrier”: str,
\n “type”: str, # mobile, landline, etc.
\n “verified”: bool
\n }) <\/p>\n

def update_label(self):
\n “””Update the display label”””
\n self.label = self.format_label([“country_code”, “number”]) <\/p>\n

### Custom Transforms Transforms are operations that process entities and generate new insights or relationships. To create a custom transform: 1. Create a new file in the `transforms` folder (e.g., `transforms\/phone_lookup.py`) 2. Implement your transform class: <\/p>\n

from dataclasses import dataclass
\n from typing import ClassVar, List
\n from .base import Transform
\n from entities.base import Entity
\n from entities.phone_number import PhoneNumber
\n from entities.location import Location
\n from ui.managers.status_manager import StatusManager <\/p>\n

@dataclass
\n class PhoneLookup(Transform):
\n name: ClassVar[str] = “Phone Number Lookup”
\n description: ClassVar[str] = “Lookup phone number details and location”
\n input_types: ClassVar[List[str]] = [“PhoneNumber”]
\n output_types: ClassVar[List[str]] = [“Location”] <\/p>\n

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

status = StatusManager.get()
\n operation_id = status.start_loading(“Phone Lookup”) <\/p>\n

try:
\n # Your phone number lookup logic here
\n # Example: query an API for phone number details
\n location = Location(properties={
\n “country”: “Example Country”,
\n “region”: “Example Region”,
\n “carrier”: “Example Carrier”,
\n “source”: “PhoneLookup transform”
\n }) <\/p>\n

return [location] <\/p>\n

except Exception as e:
\n status.set_text(f”Error during phone lookup: {str(e)}”)
\n return [] <\/p>\n

finally:
\n status.stop_loading(operation_id) <\/p>\n

### Custom Helpers Helpers are specialized tools that provide additional investigation capabilities through a dedicated UI interface. To create a custom helper: 1. Create a new file in the `helpers` folder (e.g., `helpers\/data_analyzer.py`) 2. Implement your helper class: <\/p>\n

from PySide6.QtWidgets import (
\n QWidget, QVBoxLayout, QHBoxLayout, QPushButton,
\n QTextEdit, QLabel, QComboBox
\n )
\n from .base import BaseHelper
\n from qasync import asyncSlot <\/p>\n

class DummyHelper(BaseHelper):
\n “””A dummy helper for testing””” <\/p>\n

name = “Dummy Helper”
\n description = “A dummy helper for testing” <\/p>\n

def setup_ui(self):
\n “””Initialize the helper’s user interface”””
\n # Create input text area
\n self.input_label = QLabel(“Input:”)
\n self.input_text = QTextEdit()
\n self.input_text.setPlaceholderText(“Enter text to process…”)
\n self.input_text.setMinimumHeight(100) <\/p>\n

# Create operation selector
\n operation_layout = QHBoxLayout()
\n self.operation_label = QLabel(“Operation:”)
\n self.operation_combo = QComboBox()
\n self.operation_combo.addItems([“Uppercase”, “Lowercase”, “Title Case”])
\n operation_layout.addWidget(self.operation_label)
\n operation_layout.addWidget(self.operation_combo) <\/p>\n

# Create process button
\n self.process_btn = QPushButton(“Process”)
\n self.process_btn.clicked.connect(self.process_text) <\/p>\n

# Create output text area
\n self.output_label = QLabel(“Output:”)
\n self.output_text = QTextEdit()
\n self.output_text.setReadOnly(True)
\n self.output_text.setMinimumHeight(100) <\/p>\n

# Add widgets to main layout
\n self.main_layout.addWidget(self.input_label)
\n self.main_layout.addWidget(self.input_text)
\n self.main_layout.addLayout(operation_layout)
\n self.main_layout.addWidget(self.process_btn)
\n self.main_layout.addWidget(self.output_label)
\n self.main_layout.addWidget(self.output_text) <\/p>\n

# Set dialog size
\n self.resize(400, 500) <\/p>\n

@asyncSlot()
\n async def process_text(self):
\n “””Process the input text based on selected operation”””
\n text = self.input_text.toPlainText()
\n operation = self.operation_combo.currentText() <\/p>\n

if operation == “Uppercase”:
\n result = text.upper()
\n elif operation == “Lowercase”:
\n result = text.lower()
\n else: # Title Case
\n result = text.title() <\/p>\n

self.output_text.setPlainText(result) <\/p>\n

## \ud83d\udcc4 License<\/p>\n

This project is licensed under the Creative Commons Attribution-NonCommercial (CC BY-NC) License.<\/p>\n

**You are free to:** \\- \u2705 Share: Copy and redistribute the material – \u2705 Adapt: Remix, transform, and build upon the material<\/p>\n

**Under these terms:** \\- \u2139\ufe0f Attribution: You must give appropriate credit – \ud83d\udeab NonCommercial: No commercial use – \ud83d\udd13 No additional restrictions<\/p>\n

## \ud83d\ude4f Acknowledgments<\/p>\n

Special thanks to all library authors and contributors who made this project possible.<\/p>\n

## \ud83d\udc68\u200d\ud83d\udcbb Author<\/p>\n

Created by ALW1EZ with AI \u2764\ufe0f<\/p>\n

**Download PANO**<\/p><\/div>\n<\/p><\/div>\n

\n

Impact Assessment<\/h3>\n\n\n\n
Base Score<\/th>\n0.0<\/td>\n<\/tr>\n
Severity<\/th>\n<\/td>\n<\/tr>\n<\/table><\/div>\n
\n

View full CVE details<\/a><\/p>\n<\/p><\/div>\n<\/div>\n