Maltego Cheat Blatt¶
_
Im Überblick
Maltego ist ein umfassendes Open Source Intelligence (OSINT) und grafisches Link-Analyse-Tool von Paterva, das es den Ermittlern ermöglicht, Beziehungen zwischen Menschen, Organisationen, Domänen, IP-Adressen und anderen Organisationen zu sammeln, zu analysieren und zu visualisieren. Die Plattform zeichnet sich durch ihren einzigartigen graphischen Visualisierungsansatz durch die Transformation von unterschiedlichen Informationsstücken in handlungsfähige Intelligenz aus, wodurch komplexe Zusammenhänge und Muster sofort für Analysten sichtbar werden. Maltego ist der Branchenstandard für OSINT-Untersuchungen geworden, der weltweit von Strafverfolgungsbehörden, Geheimdienststellen, Sicherheitsteams und Penetrationsprüfern eingesetzt wird.
Die Kernkraft von Maltego liegt in seinem Transformationssystem, das den Prozess der Erfassung von Informationen aus verschiedenen Datenquellen automatisiert und in einem intuitiven grafischen Format präsentiert. Transforms sind automatisierte Abfragen, die eine Eingabeeinheit (wie z.B. einen Domainnamen) und zurückgebende (z.B. IP-Adressen, E-Mail-Adressen oder zugehörige Domains) zusammen mit ihren Beziehungen aufnehmen. Diese Automatisierungsfähigkeit ermöglicht es den Ermittlern, ihr Verständnis der digitalen Fußabdrücke eines Ziels rasch zu erweitern und dabei den visuellen Kontext zu bewahren, wie sich verschiedene Informationsstücke miteinander verbinden.
Maltegos Vielseitigkeit erstreckt sich über traditionelle OSINT-Untersuchungen hinaus, um Bedrohungsanalysen, Betrugsuntersuchungen, digitale Forensik-Unterstützung und soziale Netzwerkanalyse einzubeziehen. Die Plattform unterstützt sowohl manuelle Untersuchungstechniken als auch den automatisierten Datenabbau und eignet sich sowohl für gezielte Untersuchungen als auch für breit angelegte Geheimdienste. Seine Fähigkeit, mit zahlreichen Datenquellen durch Transformationen zu integrieren, kombiniert mit seiner leistungsstarken Visualisierungsmaschine, macht Maltego zu einem unverzichtbaren Werkzeug für jede Organisation, die umfassende Intelligenz Analysefähigkeiten erfordert.
• Installation
Windows Installation¶
Installieren von Maltego auf Windows-Systemen:
# 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¶
Installieren von Maltego auf Linux Distributionen:
# 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 Preferences -> 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 localhost -xkb &
cd /opt/maltego
./bin/maltego
EOF
# Build and run
docker build -t maltego-osint .
docker run -p 5900:5900 maltego-osint
oder Basisnutzung
Initial Setup¶
Maltego für den ersten Gebrauch einrichten:
# 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
# - Threat Intelligence
# - Infrastructure
# Machine Configuration
# 1. Configure machines for automated investigations
# 2. Set up API keys 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
Grundlagenforschung¶
Durchführung grundlegender OSINT-Untersuchungen:
# 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: example.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@example.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¶
Arbeiten mit Einrichtungen und Beziehungen:
# 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
Erweiterte Eigenschaften
Custom Transforms¶
Erstellen und Konfigurieren von benutzerdefinierten Transformationen:
# Transform Development
# 1. Access Transform Hub
# 2. Create new transform
# 3. Configure input/output entities
# 4. Write transform code
# Python Transform Example
#!/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, certificate transparency, etc.
pass
# Transform Configuration
# 1. Set transform name and description
# 2. Configure input entity types
# 3. Set output entity types
# 4. Configure authentication if needed
# 5. Test transform functionality
Maschinenkonfiguration¶
Einrichtung automatisierter Prüfmaschinen:
# Creating Investigation Machines
# 1. Access Machines tab
# 2. Create new machine
# 3. Add transform sequence
# 4. Configure parameters
# 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 Parameters
# - Maximum entities per transform
# - Transform timeout settings
# - API rate limiting
# - Output filtering rules
Datenintegration¶
Integration externer Datenquellen:
# API Integration
# 1. Configure API keys 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 connections
# 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)
Erweiterte Visualisierung¶
Advanced Graph Visualisierung und Analyse:
# Layout Algorithms
# 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
Automatisierungsskripte
Automatisierte OSINT Sammlung¶
#!/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_key, base_url="https://api.maltego.com"):
self.api_key = api_key
self.base_url = base_url
self.headers = \\\\{
"Authorization": f"Bearer \\\\{api_key\\\\}",
"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 target, data in self.results.items():
investigations_html += f"""
<div class="investigation">
<h2>Investigation: \\\\{target\\\\}</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\\\\}")
# Usage
if __name__ == "__main__":
collector = MaltegoOSINTCollector("your_api_key")
# Investigate multiple targets
targets = [
("domain", "example.com"),
("email", "user@example.com"),
("person", "John Doe")
]
for target_type, target_value in targets:
if target_type == "domain":
collector.investigate_domain(target_value)
elif target_type == "email":
collector.investigate_email(target_value)
elif target_type == "person":
collector.investigate_person(target_value)
time.sleep(5) # Rate limiting between investigations
# Export results
collector.export_results()
collector.generate_report()
Bulk Entity Processing¶
#!/usr/bin/env python3
# Bulk entity processing for Maltego
import csv
import json
import time
from datetime import datetime
class MaltegoBulkProcessor:
def __init__(self, maltego_collector):
self.collector = maltego_collector
self.processed_entities = []
self.failed_entities = []
def process_csv_file(self, csv_file, entity_type_column, entity_value_column):
"""Process 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"Processing \\\\{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.processed_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 processing \\\\{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_processing_report(self, output_file="bulk_processing_report.json"):
"""Generate bulk processing report"""
report = \\\\{
"processing_summary": \\\\{
"total_entities": len(self.processed_entities) + len(self.failed_entities),
"successful": len(self.processed_entities),
"failed": len(self.failed_entities),
"success_rate": len(self.processed_entities) / (len(self.processed_entities) + len(self.failed_entities)) * 100
\\\\},
"processed_entities": self.processed_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 processing report saved: \\\\{output_file\\\\}")
return report
# Usage
collector = MaltegoOSINTCollector("your_api_key")
processor = MaltegoBulkProcessor(collector)
# Process entities from CSV
processor.process_csv_file("entities.csv", "type", "value")
# Generate report
processor.generate_processing_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
# Certificate Transparency subdomain discovery
subdomains = cls.discover_subdomains_ct(domain)
for subdomain in subdomains:
entity = response.addEntity("maltego.Domain", subdomain)
entity.addProperty("source", "Certificate Transparency")
return response
@staticmethod
def discover_subdomains_ct(domain):
"""Discover subdomains using Certificate 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
# Usage in Maltego
if __name__ == "__main__":
# This would be called by Maltego transform runner
transforms = register_transforms()
print(f"Registered \\\\{len(transforms)\\\\} custom transforms")
Integrationsbeispiele
Threat Intelligence Integration¶
#!/usr/bin/env python3
# Maltego threat intelligence 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 threat intelligence"""
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 threat intelligence 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=\\\\{"apikey": "your_vt_api_key", "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),
"references": tc_data.get("references", []),
"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 threat intelligence entities to graph"""
for source, data in threat_data.items():
# Add threat intelligence 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")
# Usage
collector = MaltegoOSINTCollector("your_api_key")
threat_intel = ThreatIntelligenceIntegration(collector)
# Investigate domain with threat intelligence
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_keys):
self.collector = maltego_collector
self.api_keys = api_keys
self.setup_apis()
def setup_apis(self):
"""Setup social media API connections"""
# Twitter API
if "twitter" in self.api_keys:
auth = tweepy.OAuthHandler(
self.api_keys["twitter"]["consumer_key"],
self.api_keys["twitter"]["consumer_secret"]
)
auth.set_access_token(
self.api_keys["twitter"]["access_token"],
self.api_keys["twitter"]["access_token_secret"]
)
self.twitter_api = tweepy.API(auth)
# Facebook API
if "facebook" in self.api_keys:
self.facebook_api = facebook.GraphAPI(
access_token=self.api_keys["facebook"]["access_token"]
)
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"] = [
\\\\{
"username": 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_connections(self, username, platform):
"""Analyze social media connections"""
connections = []
if platform == "twitter":
try:
# Get followers
followers = self.twitter_api.get_followers(screen_name=username, count=100)
for follower in followers:
connections.append(\\\\{
"type": "follower",
"username": follower.screen_name,
"name": follower.name,
"relationship": "follows"
\\\\})
except Exception as e:
print(f"Error analyzing Twitter connections: \\\\{e\\\\}")
return connections
# Usage
api_keys = \\\\{
"twitter": \\\\{
"consumer_key": "your_consumer_key",
"consumer_secret": "your_consumer_secret",
"access_token": "your_access_token",
"access_token_secret": "your_access_token_secret"
\\\\}
\\\\}
collector = MaltegoOSINTCollector("your_api_key")
social_media = SocialMediaIntegration(collector, api_keys)
# Search for social profiles
profiles = social_media.search_social_profiles("John Doe")
Fehlerbehebung
Häufige Fragen¶
Transform Fehler:
# Check transform configuration
# 1. Verify API keys 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
```_
**Leistungsfragen:**
```bash
# 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 connection pooling
# 3. Use local data sources when possible
# 4. Optimize API usage patterns
```_
**Datenqualität Ausgaben:**
```bash
# 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 processes
# 4. Document data limitations
```_
### Debugging
Debugging und Protokollierung aktivieren:
```bash
# 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 certificates
# 4. Monitor API rate limits
Sicherheitsbedenken
Operationelle Sicherheit¶
Datenschutz: - Verschlüsselung sensibler Untersuchungsdaten - Verwenden Sie sichere Kommunikationskanäle - Implementierung der richtigen Zugangskontrollen - Regelmäßige Sicherheitsbewertungen - Sichere Entsorgung von Untersuchungsartefakten
API Sicherheit: - Sichere Speicherung der API-Schlüssel - Regelmäßige Schlüsseldrehung - API-Nutzungsmuster überwachen - Leistungsbegrenzung - Verwenden Sie Mindestprivilegprinzipien
Rechtliche und ethische Überlegungen¶
Privacy Compliance: - Datenschutzgesetze und -vorschriften beachten - ordnungsgemäße Genehmigung für Untersuchungen - Implementierung von Datenminimierungsprinzipien - Sicheres Handling personenbezogener Daten - Regelmäßige Compliance Audits
Ethical OSINT: - Nur öffentlich zugängliche Informationen verwenden - Nutzungsbedingungen - Sozialtechnik vermeiden - Pflege professioneller Standards - Methodik der Dokumentenuntersuchung
Referenzen
ANHANG Die offizielle Website von Maltego 2. Maltego Dokumentation 3. Maltego Transform Hub 4. OSINT Framework_ 5. Open Source Intelligence Techniques