Maltego aide-mémoire
Overview
Maltego is a comprehensive open source intelligence (OSINT) and graphical link analysis tool developed by Paterva that enables investigators to gather, analyze, and visualize relationships between people, organizations, domains, IP addresses, and other entities. The platform excels at transforming disparate pieces of information into actionable intelligence through its unique graph-based visualization approach, making complex relationships and patterns immediately apparent to analysts. Maltego has become the industry standard for OSINT investigations, used extensively by law enforcement, intelligence agencies, corporate security teams, and penetration testers worldwide.
The core strength of Maltego lies in its transform system, which automates the processus of gathering information from various data sources and presenting it in an intuitive graphical format. Transforms are automated queries that take an input entity (such as a domain name) and return related entities (such as IP addresses, email addresses, or associated domains) along with their relationships. This automation capability allows investigators to rapidly expand their understanding of a cible's digital footprint while maintaining visual context of how different pieces of information connect to each other.
Maltego's versatility extends beyond traditional OSINT investigations to include Renseignement sur les Menaces analysis, fraud investigation, criminalistique numérique support, and social Analyse Réseau. The platform supports both manual investigation techniques and automated data mining, making it suitable for both cibleed investigations and broad intelligence gathering operations. Its ability to integrate with numerous data sources through transforms, combined with its powerful visualization engine, makes Maltego an indispensable tool for any organization requiring comprehensive intelligence analysis capabilities.
Installation
Windows Installation
Installing Maltego on Windows systems:
# Download Maltego installer
# Visit: https://www.maltego.com/downloads/
# Run installer as administrator
maltego-4.6.0-windows.exe
# Choose Installation directory
# Default: C:\Program Files\Maltego
# Configure Java settings
# Minimum 4GB RAM recommended
# Java 8 or higher required
# Launch Maltego
# Start Menu -> Maltego
# Initial setup
# Create Maltego account
# Choose license type (Community/Commercial)
# Configure transform hub
Linux Installation
Installing Maltego on Linux distributions:
# Download Linux installer
wget https://downloads.maltego.com/maltego-v4/linux/Maltego.v4.6.0.deb
# Install on Ubuntu/Debian
sudo dpkg -i Maltego.v4.6.0.deb
sudo apt-get install -f
# Install dependencies if needed
sudo apt install openjdk-11-jre
# Alternative: Download tar.gz
wget https://downloads.maltego.com/maltego-v4/linux/Maltego.v4.6.0.linux.zip
unzip Maltego.v4.6.0.linux.zip
cd Maltego.v4.6.0
# Make executable
chmod +x bin/maltego
# Run Maltego
./bin/maltego
# Create desktop shortcut
cp maltego.desktop ~/.local/share/applications/
macOS Installation
# Download macOS installer
# Visit: https://www.maltego.com/downloads/
# Install DMG package
# Drag Maltego to Applications folder
# Install Java if needed
brew install openjdk@11
# Launch from Applications
# Or from terminal
/Applications/Maltego.app/Contents/MacOS/maltego
# Configure security settings
# System Préférences -> Security & Privacy
# Allow Maltego to run
Docker Installation
# Create Maltego Docker environment
cat > Dockerfile << 'EOF'
FROM ubuntu:20.04
ENV DEBIAN_FRONTEND=noninteractive
RUN apt-get update && apt-get install -y \
openjdk-11-jre wget unzip \
xvfb x11vnc fluxbox
# Download and install Maltego
RUN wget https://downloads.maltego.com/maltego-v4/linux/Maltego.v4.6.0.linux.zip
RUN unzip Maltego.v4.6.0.linux.zip
RUN mv Maltego.v4.6.0 /opt/maltego
# Setup VNC
EXPOSE 5900
# Start script
COPY start.sh /start.sh
RUN chmod +x /start.sh
CMD ["/start.sh"]
EOF
# Create start script
cat > start.sh << 'EOF'
#!/bin/bash
Xvfb :1 -screen 0 1024x768x16 &
export DISPLAY=:1
fluxbox &
x11vnc -display :1 -nopw -listen localhôte -xkb &
cd /opt/maltego
./bin/maltego
EOF
# Build and run
docker build -t maltego-osint .
docker run -p 5900:5900 maltego-osint
Basic utilisation
Initial Setup
Setting up Maltego for first use:
# Launch Maltego
maltego
# Account Setup
# 1. Create Maltego account or login
# 2. Choose license type:
# - Community Edition (free, limited)
# - Commercial License (full features)
# Transform Hub configuration
# 1. Access Transform Hub
# 2. Install transform packages:
# - Standard Transforms
# - Social Networks
# - Renseignement sur les Menaces
# - Infrastructure
# Machine configuration
# 1. Configure machines for automated investigations
# 2. Set up API clés for data sources
# 3. Configure proxy settings if needed
# Workspace Setup
# 1. Create new graph
# 2. Configure entity palette
# 3. Set up custom entity types if needed
Basic Investigation
Performing basic OSINT investigations:
# Starting an Investigation
# 1. Create new graph
# 2. Add initial entity (domain, person, email)
# 3. Right-click entity -> Run Transform
# Domain Investigation
# Add Domain entity: exemple.com
# Run transforms:
# - To DNS Name [DNS]
# - To IP Address [DNS]
# - To MX Record [DNS]
# - To Website [HTTP]
# Email Investigation
# Add Email Address entity: user@exemple.com
# Run transforms:
# - To Domain [Email]
# - To Person [Email]
# - To Social Network Profile
# Person Investigation
# Add Person entity: John Doe
# Run transforms:
# - To Email Address [Search Engines]
# - To Social Network Profile
# - To Phone Number
# - To Address
Entity Management
Working with entities and relationships:
# Adding Entities
# 1. Drag from Entity Palette
# 2. Right-click graph -> Add Entity
# 3. Import from file (CSV, XML)
# Entity Properties
# 1. Select entity
# 2. View Properties tab
# 3. Edit entity details
# 4. Add custom properties
# Relationship Management
# 1. Select two entities
# 2. Right-click -> Add Link
# 3. Choose link type
# 4. Set link properties
# Entity Grouping
# 1. Select multiple entities
# 2. Right-click -> Group
# 3. Name the group
# 4. Set group properties
Advanced Features
Custom Transforms
Creating and configuring custom transforms:
# Transform Development
# 1. Access Transform Hub
# 2. Create new transform
# 3. Configure input/output entities
# 4. Write transform code
# Python Transform exemple
#!/usr/bin/env python3
from maltego_trx.maltego import UIM_TYPES
from maltego_trx.transform import DiscoverableTransform
class DomainToSubdomains(DiscoverableTransform):
@classmethod
def create_entities(cls, request, response):
domain = request.Value
# Custom subdomain discovery logic
subdomains = discover_subdomains(domain)
for subdomain in subdomains:
response.addEntity("maltego.Domain", subdomain)
return response
def discover_subdomains(domain):
# Implementation for subdomain discovery
# Using DNS queries, certificat transparency, etc.
pass
# Transform configuration
# 1. Set transform name and Description
# 2. Configure input entity types
# 3. Set output entity types
# 4. Configure authentification if needed
# 5. Test transform functionality
Machine configuration
Setting up automated investigation machines:
# Creating Investigation Machines
# 1. Access Machines tab
# 2. Create new machine
# 3. Add transform sequence
# 4. Configure paramètres
# Domain Investigation Machine
# Sequence:
# 1. Domain -> DNS Names
# 2. Domain -> IP Addresses
# 3. Domain -> MX Records
# 4. Domain -> Subdomains
# 5. IP Address -> Geolocation
# 6. IP Address -> Network Block
# Person Investigation Machine
# Sequence:
# 1. Person -> Email Addresses
# 2. Email -> Domains
# 3. Person -> Social Profiles
# 4. Person -> Phone Numbers
# 5. Phone -> Location
# Machine paramètres
# - Maximum entities per transform
# - Transform timeout settings
# - API rate limiting
# - Output filtering rules
Data Integration
Integrating external data sources:
# API Integration
# 1. Configure API clés in Transform Hub
# 2. Available APIs:
# - VirusTotal
# - Shodan
# - PassiveTotal
# - ThreatCrowd
# - Social media APIs
# Custom Data Sources
# 1. Create CSV import templates
# 2. Configure entity mappings
# 3. Import data files
# 4. Validate imported entities
# Database Integration
# 1. Configure database connexions
# 2. Create SQL-based transforms
# 3. Map database fields to entities
# 4. Set up automated queries
# File Import/Export
# Supported formats:
# - CSV (entities and links)
# - XML (Maltego format)
# - GraphML
# - JSON
# - KML (geolocation data)
Advanced Visualization
Advanced graph visualization and analysis:
# Layout algorithmes
# 1. Hierarchical Layout
# 2. Circular Layout
# 3. Organic Layout
# 4. Force-Directed Layout
# 5. Geographic Layout
# Filtering and Selection
# 1. Filter by entity type
# 2. Filter by property values
# 3. Filter by link types
# 4. Time-based filtering
# 5. Custom filter expressions
# Graph Analysis
# 1. Centrality analysis
# 2. Clustering detection
# 3. Path analysis
# 4. Network metrics
# 5. Pattern recognition
# Visualization Customization
# 1. Entity icons and colors
# 2. Link styles and colors
# 3. Label customization
# 4. Size scaling by properties
# 5. Conditional formatting
Automation Scripts
Automated OSINT Collection
#!/usr/bin/env python3
# Automated OSINT collection using Maltego API
import requests
import json
import time
from datetime import datetime
class MaltegoOSINTCollector:
def __init__(self, api_clé, base_url="https://api.maltego.com"):
self.api_clé = api_clé
self.base_url = base_url
self.headers = \\\\{
"autorisation": f"Bearer \\\\{api_clé\\\\}",
"Content-Type": "application/json"
\\\\}
self.results = \\\\{\\\\}
def create_graph(self, name, Description=""):
"""Create new investigation graph"""
data = \\\\{
"name": name,
"Description": Description,
"created": datetime.now().isoformat()
\\\\}
response = requests.post(
f"\\\\{self.base_url\\\\}/graphs",
headers=self.headers,
json=data
)
if response.status_code == 201:
graph_data = response.json()
return graph_data["id"]
else:
print(f"Error creating graph: \\\\{response.status_code\\\\}")
return None
def add_entity(self, graph_id, entity_type, value, properties=None):
"""Add entity to graph"""
data = \\\\{
"type": entity_type,
"value": value,
"properties": properties or \\\\{\\\\}
\\\\}
response = requests.post(
f"\\\\{self.base_url\\\\}/graphs/\\\\{graph_id\\\\}/entities",
headers=self.headers,
json=data
)
if response.status_code == 201:
return response.json()["id"]
else:
print(f"Error adding entity: \\\\{response.status_code\\\\}")
return None
def run_transform(self, graph_id, entity_id, transform_name):
"""Run transform on entity"""
data = \\\\{
"transform": transform_name,
"entity_id": entity_id
\\\\}
response = requests.post(
f"\\\\{self.base_url\\\\}/graphs/\\\\{graph_id\\\\}/transforms",
headers=self.headers,
json=data
)
if response.status_code == 200:
return response.json()
else:
print(f"Error running transform: \\\\{response.status_code\\\\}")
return None
def run_machine(self, graph_id, entity_id, machine_name):
"""Run investigation machine"""
data = \\\\{
"machine": machine_name,
"entity_id": entity_id,
"max_entities": 100,
"timeout": 300
\\\\}
response = requests.post(
f"\\\\{self.base_url\\\\}/graphs/\\\\{graph_id\\\\}/machines",
headers=self.headers,
json=data
)
if response.status_code == 200:
job_id = response.json()["job_id"]
return self.wait_for_job(job_id)
else:
print(f"Error running machine: \\\\{response.status_code\\\\}")
return None
def wait_for_job(self, job_id, timeout=600):
"""Wait for job completion"""
start_time = time.time()
while time.time() - start_time < timeout:
response = requests.get(
f"\\\\{self.base_url\\\\}/jobs/\\\\{job_id\\\\}",
headers=self.headers
)
if response.status_code == 200:
job_data = response.json()
status = job_data["status"]
if status == "completed":
return job_data["results"]
elif status == "failed":
print(f"Job failed: \\\\{job_data.get('error', 'Unknown error')\\\\}")
return None
else:
time.sleep(10) # Wait 10 seconds before checking again
else:
print(f"Error checking job status: \\\\{response.status_code\\\\}")
return None
print("Job timeout")
return None
def investigate_domain(self, domain):
"""Comprehensive domain investigation"""
print(f"Starting investigation of domain: \\\\{domain\\\\}")
# Create graph
graph_id = self.create_graph(f"Domain Investigation: \\\\{domain\\\\}")
if not graph_id:
return None
# Add domain entity
entity_id = self.add_entity(graph_id, "maltego.Domain", domain)
if not entity_id:
return None
# Run domain investigation machine
results = self.run_machine(graph_id, entity_id, "Domain Investigation")
if results:
self.results[domain] = \\\\{
"graph_id": graph_id,
"investigation_results": results,
"timestamp": datetime.now().isoformat()
\\\\}
print(f"Investigation completed for \\\\{domain\\\\}")
return results
else:
print(f"Investigation failed for \\\\{domain\\\\}")
return None
def investigate_email(self, email):
"""Comprehensive email investigation"""
print(f"Starting investigation of email: \\\\{email\\\\}")
# Create graph
graph_id = self.create_graph(f"Email Investigation: \\\\{email\\\\}")
if not graph_id:
return None
# Add email entity
entity_id = self.add_entity(graph_id, "maltego.EmailAddress", email)
if not entity_id:
return None
# Run email investigation transforms
transforms = [
"To Domain [Email]",
"To Person [Email]",
"To Social Network Profile",
"To Breach Data"
]
results = \\\\{\\\\}
for transform in transforms:
print(f"Running transform: \\\\{transform\\\\}")
result = self.run_transform(graph_id, entity_id, transform)
if result:
results[transform] = result
time.sleep(2) # Rate limiting
self.results[email] = \\\\{
"graph_id": graph_id,
"investigation_results": results,
"timestamp": datetime.now().isoformat()
\\\\}
return results
def investigate_person(self, person_name):
"""Comprehensive person investigation"""
print(f"Starting investigation of person: \\\\{person_name\\\\}")
# Create graph
graph_id = self.create_graph(f"Person Investigation: \\\\{person_name\\\\}")
if not graph_id:
return None
# Add person entity
entity_id = self.add_entity(graph_id, "maltego.Person", person_name)
if not entity_id:
return None
# Run person investigation machine
results = self.run_machine(graph_id, entity_id, "Person Investigation")
if results:
self.results[person_name] = \\\\{
"graph_id": graph_id,
"investigation_results": results,
"timestamp": datetime.now().isoformat()
\\\\}
print(f"Investigation completed for \\\\{person_name\\\\}")
return results
else:
print(f"Investigation failed for \\\\{person_name\\\\}")
return None
def export_results(self, output_file="maltego_results.json"):
"""Export investigation results"""
with open(output_file, 'w') as f:
json.dump(self.results, f, indent=2)
print(f"Results exported to \\\\{output_file\\\\}")
def generate_report(self, output_file="maltego_report.html"):
"""Generate HTML investigation report"""
html_template = """
<!DOCTYPE html>
<html>
<head>
<title>Maltego OSINT Investigation Report</title>
<style>
body \\\\{ font-family: Arial, sans-serif; margin: 20px; \\\\}
.header \\\\{ background-color: #f0f0f0; padding: 20px; \\\\}
.investigation \\\\{ margin: 20px 0; border: 1px solid #ccc; padding: 15px; \\\\}
.entity \\\\{ margin: 10px 0; padding: 10px; background-color: #f9f9f9; \\\\}
.results \\\\{ margin: 10px 0; \\\\}
</style>
</head>
<body>
<div class="header">
<h1>Maltego OSINT Investigation Report</h1>
<p>Generated: \\\\{timestamp\\\\}</p>
<p>Total Investigations: \\\\{total_investigations\\\\}</p>
</div>
\\\\{investigations\\\\}
</body>
</html>
"""
investigations_html = ""
for cible, data in self.results.items():
investigations_html += f"""
<div class="investigation">
<h2>Investigation: \\\\{cible\\\\}</h2>
<p>Timestamp: \\\\{data['timestamp']\\\\}</p>
<p>Graph ID: \\\\{data['graph_id']\\\\}</p>
<div class="results">
<h3>Results Summary</h3>
<p>Entities discovered: \\\\{len(data.get('investigation_results', \\\\{\\\\}))\\\\}</p>
</div>
</div>
"""
html_content = html_template.format(
timestamp=datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
total_investigations=len(self.results),
investigations=investigations_html
)
with open(output_file, 'w') as f:
f.write(html_content)
print(f"Report generated: \\\\{output_file\\\\}")
# utilisation
if __name__ == "__main__":
collector = MaltegoOSINTCollector("your_api_clé")
# Investigate multiple cibles
cibles = [
("domain", "exemple.com"),
("email", "user@exemple.com"),
("person", "John Doe")
]
for cible_type, cible_value in cibles:
if cible_type == "domain":
collector.investigate_domain(cible_value)
elif cible_type == "email":
collector.investigate_email(cible_value)
elif cible_type == "person":
collector.investigate_person(cible_value)
time.sleep(5) # Rate limiting between investigations
# Export results
collector.export_results()
collector.generate_report()
Bulk Entity processusing
#!/usr/bin/env python3
# Bulk entity processusing for Maltego
import csv
import json
import time
from datetime import datetime
class MaltegoBulkprocessusor:
def __init__(self, maltego_collector):
self.collector = maltego_collector
self.processused_entities = []
self.failed_entities = []
def processus_csv_file(self, csv_file, entity_type_column, entity_value_column):
"""processus entities from CSV file"""
with open(csv_file, 'r') as f:
reader = csv.DictReader(f)
for row in reader:
entity_type = row[entity_type_column]
entity_value = row[entity_value_column]
print(f"processusing \\\\{entity_type\\\\}: \\\\{entity_value\\\\}")
try:
if entity_type.lower() == "domain":
result = self.collector.investigate_domain(entity_value)
elif entity_type.lower() == "email":
result = self.collector.investigate_email(entity_value)
elif entity_type.lower() == "person":
result = self.collector.investigate_person(entity_value)
else:
print(f"Unknown entity type: \\\\{entity_type\\\\}")
continue
if result:
self.processused_entities.append(\\\\{
"type": entity_type,
"value": entity_value,
"status": "success",
"timestamp": datetime.now().isoformat()
\\\\})
else:
self.failed_entities.append(\\\\{
"type": entity_type,
"value": entity_value,
"status": "failed",
"timestamp": datetime.now().isoformat()
\\\\})
except Exception as e:
print(f"Error processusing \\\\{entity_value\\\\}: \\\\{e\\\\}")
self.failed_entities.append(\\\\{
"type": entity_type,
"value": entity_value,
"status": "error",
"error": str(e),
"timestamp": datetime.now().isoformat()
\\\\})
# Rate limiting
time.sleep(10)
def generate_processusing_report(self, output_file="bulk_processusing_report.json"):
"""Generate bulk processusing report"""
report = \\\\{
"processusing_summary": \\\\{
"total_entities": len(self.processused_entities) + len(self.failed_entities),
"successful": len(self.processused_entities),
"failed": len(self.failed_entities),
"success_rate": len(self.processused_entities) / (len(self.processused_entities) + len(self.failed_entities)) * 100
\\\\},
"processused_entities": self.processused_entities,
"failed_entities": self.failed_entities,
"report_timestamp": datetime.now().isoformat()
\\\\}
with open(output_file, 'w') as f:
json.dump(report, f, indent=2)
print(f"Bulk processusing report saved: \\\\{output_file\\\\}")
return report
# utilisation
collector = MaltegoOSINTCollector("your_api_clé")
processusor = MaltegoBulkprocessusor(collector)
# processus entities from CSV
processusor.processus_csv_file("entities.csv", "type", "value")
# Generate report
processusor.generate_processusing_report()
Transform Development Framework
#!/usr/bin/env python3
# Maltego transform development framework
from maltego_trx.maltego import UIM_TYPES
from maltego_trx.transform import DiscoverableTransform
import requests
import dns.resolver
import whois
import socket
class CustomDomainTransforms:
"""Collection of custom domain-related transforms"""
class DomainToSubdomains(DiscoverableTransform):
@classmethod
def create_entities(cls, request, response):
domain = request.Value
# certificat Transparency subdomain discovery
subdomains = cls.discover_subdomains_ct(domain)
for subdomain in subdomains:
entity = response.addEntity("maltego.Domain", subdomain)
entity.addProperty("source", "certificat Transparency")
return response
@staticmethod
def discover_subdomains_ct(domain):
"""Discover subdomains using certificat Transparency"""
subdomains = set()
try:
url = f"https://crt.sh/?q=%.\\\\{domain\\\\}&output;=json"
response = requests.get(url, timeout=30)
if response.status_code == 200:
data = response.json()
for cert in data:
name_value = cert.get('name_value', '')
for name in name_value.split('\n'):
name = name.strip()
if name.endswith(f'.\\\\{domain\\\\}') and '*' not in name:
subdomains.add(name)
except Exception as e:
print(f"Error discovering subdomains: \\\\{e\\\\}")
return list(subdomains)
class DomainToTechnologies(DiscoverableTransform):
@classmethod
def create_entities(cls, request, response):
domain = request.Value
# Technology detection
technologies = cls.detect_technologies(domain)
for tech in technologies:
entity = response.addEntity("maltego.Website", tech['name'])
entity.addProperty("technology.version", tech.get('version', ''))
entity.addProperty("technology.confidence", tech.get('confidence', ''))
return response
@staticmethod
def detect_technologies(domain):
"""Detect web technologies"""
technologies = []
try:
# Simple technology detection based on headers
response = requests.get(f"http://\\\\{domain\\\\}", timeout=10)
headers = response.headers
# Server detection
server = headers.get('Server', '')
if server:
technologies.append(\\\\{
'name': server,
'type': 'Web Server',
'confidence': 'high'
\\\\})
# Framework detection
x_powered_by = headers.get('X-Powered-By', '')
if x_powered_by:
technologies.append(\\\\{
'name': x_powered_by,
'type': 'Framework',
'confidence': 'high'
\\\\})
# Content analysis
content = response.text.lower()
# WordPress detection
if 'wp-content' in content or 'wordpress' in content:
technologies.append(\\\\{
'name': 'WordPress',
'type': 'CMS',
'confidence': 'high'
\\\\})
# jQuery detection
if 'jquery' in content:
technologies.append(\\\\{
'name': 'jQuery',
'type': 'JavaScript Library',
'confidence': 'medium'
\\\\})
except Exception as e:
print(f"Error detecting technologies: \\\\{e\\\\}")
return technologies
class DomainToWhoisInfo(DiscoverableTransform):
@classmethod
def create_entities(cls, request, response):
domain = request.Value
# WHOIS lookup
whois_info = cls.get_whois_info(domain)
if whois_info:
# Add registrar
if 'registrar' in whois_info:
entity = response.addEntity("maltego.Organization", whois_info['registrar'])
entity.addProperty("organization.type", "Registrar")
# Add registrant
if 'registrant' in whois_info:
entity = response.addEntity("maltego.Person", whois_info['registrant'])
entity.addProperty("person.role", "Registrant")
# Add creation date
if 'creation_date' in whois_info:
entity = response.addEntity("maltego.Date", str(whois_info['creation_date']))
entity.addProperty("date.type", "Domain Creation")
return response
@staticmethod
def get_whois_info(domain):
"""Get WHOIS information"""
try:
w = whois.whois(domain)
return \\\\{
'registrar': w.registrar,
'registrant': w.registrant,
'creation_date': w.creation_date,
'expiration_date': w.expiration_date,
'name_servers': w.name_servers
\\\\}
except Exception as e:
print(f"Error getting WHOIS info: \\\\{e\\\\}")
return None
# Transform registration
def register_transforms():
"""Register custom transforms"""
transforms = [
CustomDomainTransforms.DomainToSubdomains,
CustomDomainTransforms.DomainToTechnologies,
CustomDomainTransforms.DomainToWhoisInfo
]
return transforms
# utilisation in Maltego
if __name__ == "__main__":
# This would be called by Maltego transform runner
transforms = register_transforms()
print(f"Registered \\\\{len(transforms)\\\\} custom transforms")
Integration exemples
Renseignement sur les Menaces Integration
#!/usr/bin/env python3
# Maltego Renseignement sur les Menaces integration
import requests
import json
class ThreatIntelligenceIntegration:
def __init__(self, maltego_collector):
self.collector = maltego_collector
self.threat_feeds = \\\\{
"virustotal": "https://www.virustotal.com/vtapi/v2",
"threatcrowd": "https://www.threatcrowd.org/searchApi/v2",
"otx": "https://otx.alienvault.com/api/v1"
\\\\}
def enrich_with_threat_intel(self, graph_id, entity_id, entity_value, entity_type):
"""Enrich entity with Renseignement sur les Menaces"""
threat_data = \\\\{\\\\}
if entity_type == "domain":
threat_data = self.check_domain_reputation(entity_value)
elif entity_type == "ip":
threat_data = self.check_ip_reputation(entity_value)
elif entity_type == "hash":
threat_data = self.check_file_reputation(entity_value)
# Add Renseignement sur les Menaces entities to graph
if threat_data:
self.add_threat_entities(graph_id, entity_id, threat_data)
def check_domain_reputation(self, domain):
"""Check domain reputation across threat feeds"""
reputation_data = \\\\{\\\\}
# VirusTotal domain report
try:
vt_response = requests.get(
f"\\\\{self.threat_feeds['virustotal']\\\\}/domain/report",
params=\\\\{"apiclé": "your_vt_api_clé", "domain": domain\\\\}
)
if vt_response.status_code == 200:
vt_data = vt_response.json()
reputation_data["virustotal"] = \\\\{
"positives": vt_data.get("positives", 0),
"total": vt_data.get("total", 0),
"scan_date": vt_data.get("scan_date", "")
\\\\}
except Exception as e:
print(f"Error checking VirusTotal: \\\\{e\\\\}")
# ThreatCrowd domain report
try:
tc_response = requests.get(
f"\\\\{self.threat_feeds['threatcrowd']\\\\}/domain/report",
params=\\\\{"domain": domain\\\\}
)
if tc_response.status_code == 200:
tc_data = tc_response.json()
reputation_data["threatcrowd"] = \\\\{
"votes": tc_data.get("votes", 0),
"références": tc_data.get("références", []),
"resolutions": tc_data.get("resolutions", [])
\\\\}
except Exception as e:
print(f"Error checking ThreatCrowd: \\\\{e\\\\}")
return reputation_data
def add_threat_entities(self, graph_id, entity_id, threat_data):
"""Add Renseignement sur les Menaces entities to graph"""
for source, data in threat_data.items():
# Add Renseignement sur les Menaces source
ti_entity_id = self.collector.add_entity(
graph_id,
"maltego.ThreatIntelligence",
source,
\\\\{"source": source, "data": json.dumps(data)\\\\}
)
# Link to original entity
if ti_entity_id:
self.collector.add_link(graph_id, entity_id, ti_entity_id, "threat_intelligence")
# utilisation
collector = MaltegoOSINTCollector("your_api_clé")
threat_intel = ThreatIntelligenceIntegration(collector)
# Investigate domain with Renseignement sur les Menaces
graph_id = collector.create_graph("Threat Intel Investigation")
entity_id = collector.add_entity(graph_id, "maltego.Domain", "suspicious-domain.com")
threat_intel.enrich_with_threat_intel(graph_id, entity_id, "suspicious-domain.com", "domain")
Social Media Integration
#!/usr/bin/env python3
# Maltego social media integration
import tweepy
import facebook
import linkedin
class SocialMediaIntegration:
def __init__(self, maltego_collector, api_clés):
self.collector = maltego_collector
self.api_clés = api_clés
self.setup_apis()
def setup_apis(self):
"""Setup social media API connexions"""
# Twitter API
if "twitter" in self.api_clés:
auth = tweepy.OAuthHandler(
self.api_clés["twitter"]["consumer_clé"],
self.api_clés["twitter"]["consumer_secret"]
)
auth.set_access_jeton(
self.api_clés["twitter"]["access_jeton"],
self.api_clés["twitter"]["access_jeton_secret"]
)
self.twitter_api = tweepy.API(auth)
# Facebook API
if "facebook" in self.api_clés:
self.facebook_api = facebook.GraphAPI(
access_jeton=self.api_clés["facebook"]["access_jeton"]
)
def search_social_profiles(self, person_name):
"""Search for social media profiles"""
profiles = \\\\{\\\\}
# Twitter search
try:
twitter_users = self.twitter_api.search_users(person_name, count=10)
profiles["twitter"] = [
\\\\{
"nom d'utilisateur": user.screen_name,
"name": user.name,
"followers": user.followers_count,
"verified": user.verified
\\\\}
for user in twitter_users
]
except Exception as e:
print(f"Error searching Twitter: \\\\{e\\\\}")
return profiles
def analyze_social_connexions(self, nom d'utilisateur, platform):
"""Analyze social media connexions"""
connexions = []
if platform == "twitter":
try:
# Get followers
followers = self.twitter_api.get_followers(screen_name=nom d'utilisateur, count=100)
for follower in followers:
connexions.append(\\\\{
"type": "follower",
"nom d'utilisateur": follower.screen_name,
"name": follower.name,
"relationship": "follows"
\\\\})
except Exception as e:
print(f"Error analyzing Twitter connexions: \\\\{e\\\\}")
return connexions
# utilisation
api_clés = \\\\{
"twitter": \\\\{
"consumer_clé": "your_consumer_clé",
"consumer_secret": "your_consumer_secret",
"access_jeton": "your_access_jeton",
"access_jeton_secret": "your_access_jeton_secret"
\\\\}
\\\\}
collector = MaltegoOSINTCollector("your_api_clé")
social_media = SocialMediaIntegration(collector, api_clés)
# Search for social profiles
profiles = social_media.search_social_profiles("John Doe")
dépannage
Common Issues
Transform Errors:
# Check transform configuration
# 1. Verify API clés are correct
# 2. Check transform permissions
# 3. Validate input entity types
# 4. Review transform logs
# Debug transform execution
# 1. Run transform manually
# 2. Check network connectivity
# 3. Verify data source availability
# 4. Review rate limiting settings
# Transform timeout issues
# 1. Increase timeout settings
# 2. Optimize transform code
# 3. Implement proper error handling
# 4. Add retry mechanisms
Performance Issues:
# Optimize graph performance
# 1. Limit entity count per transform
# 2. Use filtering to reduce noise
# 3. Implement entity grouping
# 4. Regular graph cleanup
# Memory management
# 1. Close unused graphs
# 2. Clear transform cache
# 3. Restart Maltego periodically
# 4. Monitor system resources
# Network optimization
# 1. Configure proxy settings
# 2. Implement connexion pooling
# 3. Use local data sources when possible
# 4. Optimize API utilisation patterns
Data Quality Issues:
# Validate data sources
# 1. Check data freshness
# 2. Verify source reliability
# 3. Cross-reference multiple sources
# 4. Implement data validation
# Handle incomplete data
# 1. Implement fallback sources
# 2. Use data enrichment services
# 3. Manual verification processuses
# 4. Document data limitations
Debugging
Enable detailed debugging and logging:
# Enable Maltego debugging
# 1. Help -> Debug Information
# 2. Enable verbose logging
# 3. Check log files in:
# - Windows: %APPDATA%\Maltego\logs
# - Linux: ~/.maltego/logs
# - macOS: ~/Library/Application Support/Maltego/logs
# Transform debugging
# 1. Add debug prints to transform code
# 2. Use transform testing framework
# 3. Monitor API responses
# 4. Check entity property validation
# Network debugging
# 1. Use network monitoring tools
# 2. Check proxy configurations
# 3. Verify SSL certificats
# 4. Monitor API rate limits
Security Considerations
Operational Security
Data Protection: - Encrypt sensitive investigation data - Use secure communication channels - Implement proper Contrôle d'Accèss - Regular security assessments - Secure disposal of investigation artifacts
Sécurité API: - Secure storage of API clés - Regular clé rotation - Monitor API utilisation patterns - Implement rate limiting - Use least privilege principles
Legal and Ethical Considerations
Privacy Compliance: - Respect privacy laws and regulations - Obtain proper autorisation for investigations - Implement data minimization principles - Secure handling of personal information - Regular compliance audits
Ethical OSINT: - Use only publicly available information - Respect terms of service - Avoid ingénierie sociale - Maintain professional standards - Document investigation methodology