Threat Intelligence Fundamentals: Building a CTI Program

Published on January 5, 2024

Introduction

Cyber Threat Intelligence (CTI) is the collection, analysis, and dissemination of information about cyber threats. A well-structured CTI program can significantly enhance an organization’s security posture by providing actionable insights into potential threats.

Types of Threat Intelligence

Strategic Intelligence

• High-level threat landscape analysis
• Threat actor motivations and capabilities
• Industry-specific threat trends
• Executive decision support

Tactical Intelligence

• Specific threat actor TTPs
• Malware families and capabilities
• Attack vectors and techniques
• Technical indicators

Operational Intelligence

• Real-time threat feeds
• IOC sharing and correlation
• Incident response support
• Threat hunting guidance

Intelligence Lifecycle

1. Planning and Direction

Define intelligence requirements:

• What threats are most relevant?
• What information do we need?
• How will intelligence be used?
• Who are the stakeholders?

2. Collection

Gather information from multiple sources:

# Example: Threat feed collection
import requests
import json

def collect_threat_feeds():
    feeds = [
        "https://api.abuseipdb.com/api/v2/blacklist",
        "https://urlhaus.abuse.ch/downloads/csv/",
        "https://raw.githubusercontent.com/firehol/blocklist-ipsets/master/firehol_level1.netset"
    ]
    
    for feed in feeds:
        response = requests.get(feed)
        if response.status_code == 200:
            process_feed_data(response.text)

3. Processing

Transform raw data into structured intelligence:

• Data normalization
• Deduplication
• Enrichment
• Validation

4. Analysis

Apply analytical techniques:

• Pattern recognition
• Trend analysis
• Threat modeling
• Risk assessment

5. Dissemination

Share intelligence with stakeholders:

• Automated alerts
• Regular reports
• Briefings
• Integration with security tools

Intelligence Sources

Open Source Intelligence (OSINT)

• Social media monitoring
• Dark web forums
• Security blogs and reports
• Public threat feeds
• Vulnerability databases

Commercial Intelligence

• Threat intelligence platforms
• Security vendor reports
• Industry-specific feeds
• Professional services

Internal Intelligence

• Security logs
• Incident reports
• Network telemetry
• User behavior analytics

Intelligence Tools and Platforms

Open Source Tools

# MISP - Threat intelligence sharing
git clone https://github.com/MISP/MISP.git
cd MISP
./INSTALL/INSTALL.sh

# YARA - Pattern matching
pip install yara-python

# TheHive - Case management
docker run -d -p 9000:9000 thehive4/thehive4

Commercial Platforms

• Recorded Future: Threat intelligence platform
• FireEye iSIGHT: Threat intelligence
• IBM X-Force Exchange: Threat intelligence sharing
• Anomali STAXX: Threat intelligence feeds

Intelligence Analysis Techniques

Threat Modeling

graph TD
    A[Threat Actor] --> B[Capabilities]
    B --> C[Motivations]
    C --> D[Targets]
    D --> E[Attack Vectors]
    E --> F[Impact Assessment]

Indicator Analysis

• IOC correlation
• TTP mapping
• Campaign attribution
• Threat actor profiling

Trend Analysis

• Attack frequency
• Target industry patterns
• Geographic distribution
• Temporal patterns

Intelligence Products

Daily Threat Briefs

• Top threats of the day
• New vulnerabilities
• Active campaigns
• Recommended actions

Weekly Intelligence Reports

• Threat landscape overview
• Trend analysis
• Case studies
• Strategic recommendations

Monthly Executive Summaries

• High-level threat assessment
• Risk analysis
• Strategic implications
• Resource recommendations

Integration with Security Operations

SIEM Integration

# Example: SIEM alert enrichment
def enrich_alert_with_intel(alert):
    iocs = get_relevant_iocs(alert)
    threat_actors = get_attribution(iocs)
    ttp = get_ttp_mapping(alert)
    
    return {
        'alert': alert,
        'intelligence': {
            'iocs': iocs,
            'threat_actors': threat_actors,
            'ttp': ttp,
            'risk_score': calculate_risk_score(iocs, threat_actors)
        }
    }

Incident Response

• Threat context for incidents
• IOC hunting guidance
• Attribution support
• Response recommendations

Threat Hunting

• Hypothesis development
• Hunting playbooks
• Tool selection
• Analysis support

Best Practices

1. Define clear requirements: Understand what intelligence is needed and why
2. Use multiple sources: Don’t rely on a single intelligence source
3. Validate information: Verify intelligence before acting on it
4. Share intelligence: Contribute to the broader security community
5. Measure effectiveness: Track how intelligence improves security outcomes
6. Automate where possible: Use tools to process and disseminate intelligence
7. Maintain context: Understand the broader threat landscape

Challenges and Solutions

Common Challenges

• Information overload
• False positives
• Timeliness
• Relevance
• Integration complexity

Solutions

• Automated filtering and scoring
• Contextual analysis
• Real-time feeds
• Customized intelligence
• API-based integration

Conclusion

Effective threat intelligence requires a structured approach, the right tools, and continuous refinement. The goal is to transform raw threat data into actionable intelligence that enhances security decision-making and incident response capabilities.

Remember: Intelligence is only valuable if it’s actionable, timely, and relevant to your organization’s specific needs.

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