GIAC Cyber Threat Intelligence (GCTI) Expert - Led Video Course
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Lesson 1: Introduction to Cyber Threat Intelligence
1.1 Definition and scope of CTI
1.2 Role of CTI in cybersecurity
1.3 Intelligence lifecycle overview
1.4 Strategic, operational, tactical intelligence
1.5 Benefits of threat intelligence to organizations
1.6 Key challenges in CTI adoption
1.7 Use cases of CTI in enterprises
1.8 CTI stakeholders and consumers
1.9 CTI maturity models
1.10 Common myths and misconceptions
Lesson 2: Intelligence Requirements Development
2.1 Identifying intelligence gaps
2.2 Prioritizing collection needs
2.3 Defining Priority Intelligence Requirements (PIRs)
2.4 Aligning CTI with business goals
2.5 Translating risks into requirements
2.6 CTI requirements vs. security operations
2.7 Stakeholder interviews for intelligence scoping
2.8 Communicating requirements effectively
2.9 Requirements documentation templates
2.10 Continuous refinement of requirements
Lesson 3: Threat Landscape Fundamentals
3.1 Cybercrime vs. nation-state threats
3.2 Hacktivist and insider threats
3.3 Organized cybercriminal groups
3.4 Nation-state APT actors
3.5 Emerging threat trends
3.6 Cybercrime-as-a-service economy
3.7 Motivations behind cyberattacks
3.8 Strategic geopolitical influences
3.9 Industry-specific threat landscapes
3.10 Case studies of past threat campaigns
Lesson 4: Intelligence Collection Fundamentals
4.1 Collection management basics
4.2 Internal data sources
4.3 External intelligence providers
4.4 OSINT (Open-Source Intelligence)
4.5 HUMINT (Human Intelligence)
4.6 SIGINT (Signals Intelligence)
4.7 Dark web monitoring
4.8 Malware repositories and feeds
4.9 Threat sharing communities (ISACs, CERTs)
4.10 Collection prioritization
Lesson 5: Open-Source Intelligence (OSINT)
5.1 OSINT frameworks
5.2 Publicly available information (PAI)
5.3 Social media intelligence (SOCMINT)
5.4 WHOIS and DNS intelligence
5.5 GitHub and developer repositories
5.6 OSINT automation tools
5.7 OSINT ethics and legality
5.8 Validating OSINT sources
5.9 Case study: OSINT in APT tracking
5.10 OSINT pitfalls and limitations
Lesson 6: Technical Intelligence Collection
6.1 Malware analysis for indicators
6.2 Endpoint telemetry sources
6.3 Network traffic collection
6.4 Honeypots and deception systems
6.5 Email and phishing artifacts
6.6 Sandbox environments
6.7 Threat intel feeds (STIX/TAXII)
6.8 Vulnerability intelligence
6.9 Cloud and SaaS log sources
6.10 Correlating technical indicators
Lesson 7: Dark Web and Deep Web Intelligence
7.1 Surface, deep, and dark web distinctions
7.2 Darknet marketplaces
7.3 Ransomware leak sites
7.4 Forums and chat platforms
7.5 Cryptocurrency intelligence
7.6 TOR and I2P browsing techniques
7.7 Dark web monitoring tools
7.8 Attribution challenges in dark web
7.9 Ethical/legal considerations
7.10 Case study: Dark web data breach sales
Lesson 8: Adversary Tactics, Techniques, and Procedures (TTPs)
8.1 Defining TTPs in threat intelligence
8.2 MITRE ATT&CK framework overview
8.3 Kill chain methodology
8.4 Campaign analysis and clustering
8.5 Linking indicators to TTPs
8.6 Adversary playbooks
8.7 Behavioral vs. signature-based detection
8.8 Case study: APT28 TTPs
8.9 Evolution of adversary techniques
8.10 Mapping TTPs to detection strategy
Lesson 9: Intelligence Processing
9.1 Data normalization
9.2 De-duplication and filtering
9.3 Enrichment processes
9.4 Correlation across sources
9.5 Handling false positives
9.6 Metadata tagging and categorization
9.7 Automation and orchestration in processing
9.8 Threat intel platforms (TIPs)
9.9 Case management integration
9.10 Scalability in processing pipelines
Lesson 10: Intelligence Analysis – Core Skills
10.1 Critical thinking in CTI
10.2 Structured analytical techniques
10.3 Hypothesis development and testing
10.4 Cognitive biases in analysis
10.5 Source reliability assessment
10.6 Confidence levels in intelligence
10.7 Estimative language usage
10.8 Collaboration between analysts
10.9 Peer review and validation
10.10 Tools for intelligence analysis
Lesson 11: Structured Analytic Techniques
11.1 Analysis of Competing Hypotheses (ACH)
11.2 Key assumptions check
11.3 Red teaming and devil’s advocacy
11.4 Indicators and warnings (I&W)
11.5 SWOT analysis in CTI
11.6 Scenario analysis
11.7 Structured brainstorming
11.8 Chronologies and timelines
11.9 Threat actor profiling
11.10 Lessons learned from SAT in intelligence
Lesson 12: Attribution in Cyber Threat Intelligence
12.1 Definition and challenges of attribution
12.2 Technical evidence for attribution
12.3 Infrastructure overlaps
12.4 Malware code reuse
12.5 Linguistic and cultural indicators
12.6 Geopolitical context
12.7 False flag operations
12.8 Confidence levels in attribution
12.9 Attribution reporting best practices
12.10 Case study: Attribution controversies
Lesson 13: Intelligence Fusion
13.1 Definition of fusion in CTI
13.2 Combining HUMINT, OSINT, SIGINT
13.3 Fusion centers and structures
13.4 Fusion at tactical vs. strategic levels
13.5 Technology platforms for fusion
13.6 Cross-functional collaboration
13.7 Correlation with SIEM/SOAR
13.8 Incident response integration
13.9 Visualization in fusion analysis
13.10 Pitfalls in intelligence fusion
Lesson 14: Intelligence Reporting Fundamentals
14.1 Types of intelligence reports
14.2 Audience analysis
14.3 Writing with clarity and precision
14.4 Confidence and estimative language
14.5 Visual aids and charts
14.6 Executive summaries
14.7 Technical vs. strategic reports
14.8 Report classification and markings
14.9 Review and approval processes
14.10 Common mistakes in CTI reports
Lesson 15: Communicating Threat Intelligence
15.1 Briefing executives vs. analysts
15.2 Storytelling in CTI
15.3 Tailoring intelligence to decision makers
15.4 Oral briefings vs. written reports
15.5 Collaboration with SOC/IR teams
15.6 Presenting uncertainty effectively
15.7 Persuasive intelligence writing
15.8 Communication frameworks
15.9 Using dashboards and portals
15.10 Feedback loops in CTI communication
Lesson 16: Strategic Intelligence Analysis
16.1 Definition and scope of strategic CTI
16.2 Long-term threat actor motivations
16.3 Geopolitical drivers of cyber conflict
16.4 Industry-specific strategic analysis
16.5 Trend forecasting techniques
16.6 Influence of strategic CTI on policy
16.7 Cybersecurity investment decisions
16.8 Threat landscape evolution
16.9 Scenario planning for executives
16.10 Case study: strategic intelligence shaping defense
Lesson 17: Operational Intelligence Analysis
17.1 Definition and scope of operational CTI
17.2 Campaign-level adversary tracking
17.3 Threat infrastructure mapping
17.4 Malware family tracking
17.5 Linking incidents into campaigns
17.6 Actor toolset evolution
17.7 Operational reporting templates
17.8 Collaboration with SOC managers
17.9 Attribution at operational level
17.10 Case study: ransomware operations
Lesson 18: Tactical Intelligence Analysis
18.1 Tactical CTI vs. IOC feeds
18.2 Indicator lifecycle management
18.3 YARA and Snort signatures
18.4 TTP mapping to ATT&CK
18.5 IOC enrichment techniques
18.6 IOC scoring and prioritization
18.7 IOC sharing formats (STIX, MISP)
18.8 Tactical CTI for blue teams
18.9 Limitations of IOC-only approach
18.10 Case study: phishing campaigns
Lesson 19: Cyber Kill Chain in CTI
19.1 Lockheed Martin kill chain model
19.2 Reconnaissance and weaponization
19.3 Delivery and exploitation
19.4 Installation and C2
19.5 Actions on objectives
19.6 Criticisms of kill chain
19.7 Mapping kill chain to ATT&CK
19.8 Threat hunting with kill chain
19.9 Reporting with kill chain framework
19.10 Case study: APT lifecycle analysis
Lesson 20: MITRE ATT&CK for CTI
20.1 Overview of ATT&CK framework
20.2 Tactics vs. techniques
20.3 Data sources mapped to ATT&CK
20.4 ATT&CK navigator usage
20.5 Adversary emulation plans
20.6 Detection engineering with ATT&CK
20.7 Campaign mapping to ATT&CK
20.8 Sharing reports using ATT&CK
20.9 ATT&CK vs. other frameworks
20.10 Case study: threat actor ATT&CK profile
Lesson 21: Threat Hunting with CTI
21.1 Proactive vs. reactive security
21.2 CTI-driven hunting hypotheses
21.3 Building hunting queries
21.4 Tools for hunting (ELK, Splunk, etc.)
21.5 Threat hunting maturity models
21.6 Red vs. blue collaboration
21.7 Hunt team processes
21.8 Integration of CTI into hunts
21.9 Metrics for hunting success
21.10 Case study: insider threat hunting
Lesson 22: Malware Intelligence
22.1 Malware families classification
22.2 Static vs. dynamic malware analysis
22.3 Reverse engineering basics
22.4 Malware sandboxing
22.5 Malware IOC extraction
22.6 Malware naming conventions
22.7 Malware infrastructure overlaps
22.8 Malware reporting best practices
22.9 Malware intelligence feeds
22.10 Case study: Emotet
Lesson 23: Phishing and Social Engineering Intelligence
23.1 Social engineering tactics
23.2 Phishing kit analysis
23.3 Email header forensics
23.4 Brand abuse monitoring
23.5 Business Email Compromise (BEC)
23.6 Spearphishing indicators
23.7 Phishing reporting workflows
23.8 Phishing campaign tracking
23.9 Social media impersonation
23.10 Case study: credential harvesting
Lesson 24: Ransomware Intelligence
24.1 Ransomware evolution
24.2 Ransomware as a service (RaaS)
24.3 Initial access vectors
24.4 Ransomware infrastructure
24.5 Leak sites and extortion tactics
24.6 Cryptocurrency tracing in ransomware
24.7 Decryption keys and negotiation intel
24.8 Ransomware group profiling
24.9 Sharing ransomware intel across industries
24.10 Case study: Conti ransomware
Lesson 25: Insider Threat Intelligence
25.1 Types of insider threats
25.2 Motivation and risk indicators
25.3 Data exfiltration techniques
25.4 Behavioral analytics for insiders
25.5 Internal threat reporting channels
25.6 Balancing privacy and monitoring
25.7 Insider threat use of social engineering
25.8 Legal/ethical considerations
25.9 Intelligence on disgruntled employees
25.10 Case study: insider data theft
Lesson 26: Nation-State Threat Actors
26.1 Characteristics of state-sponsored actors
26.2 Geopolitical motivations
26.3 Notable APT groups (APT1, APT28, etc.)
26.4 Supply chain compromise tactics
26.5 Long-term persistence strategies
26.6 Disinformation operations
26.7 Cyber espionage vs. cyber warfare
26.8 Cross-border attribution challenges
26.9 Case study: SolarWinds attack
26.10 Countering nation-state campaigns
Lesson 27: Cybercrime Ecosystems
27.1 Cybercrime marketplaces
27.2 Carding and financial fraud
27.3 Exploit kits
27.4 Initial Access Brokers (IABs)
27.5 Botnets as services
27.6 Money laundering mechanisms
27.7 Affiliate programs in cybercrime
27.8 International cooperation challenges
27.9 Case study: Evil Corp group
27.10 CTI for law enforcement
Lesson 28: Threat Intelligence Sharing
28.1 Importance of sharing intelligence
28.2 ISACs and CERTs
28.3 STIX/TAXII standards
28.4 MISP platform overview
28.5 Trust groups (TLP)
28.6 Legal barriers to sharing
28.7 Public-private collaboration models
28.8 Sharing across industries
28.9 Pitfalls in sharing initiatives
28.10 Case study: FS-ISAC
Lesson 29: Threat Intelligence Platforms (TIPs)
29.1 Role of TIPs in CTI lifecycle
29.2 Core features of TIPs
29.3 Popular TIPs (ThreatConnect, Anomali, MISP)
29.4 TIP integration with SIEM/SOAR
29.5 IOC ingestion automation
29.6 TIP dashboards and visualizations
29.7 TIP for threat sharing
29.8 TIP scalability challenges
29.9 ROI measurement of TIP deployment
29.10 Future of TIPs
Lesson 30: Automation and Orchestration in CTI
30.1 SOAR platforms overview
30.2 Automation use cases in CTI
30.3 Playbook creation
30.4 Machine learning in CTI
30.5 Natural language processing (NLP) for CTI
30.6 Data enrichment automation
30.7 Automated hunting with CTI
30.8 Challenges in automation
30.9 Human-in-the-loop models
30.10 Future of AI in CTI
Lesson 31: Legal and Ethical Issues in CTI
31.1 International law and cyber operations
31.2 Privacy regulations (GDPR, HIPAA)
31.3 Attribution legal implications
31.4 Ethical OSINT collection
31.5 Dark web monitoring legality
31.6 Corporate liability in CTI operations
31.7 Cross-border intelligence sharing
31.8 Law enforcement collaboration
31.9 Responsible disclosure policies
31.10 Ethical dilemmas in CTI
Lesson 32: CTI Program Development
32.1 CTI program components
32.2 Building a CTI team
32.3 CTI operating models
32.4 CTI maturity assessments
32.5 CTI program KPIs and metrics
32.6 Resourcing and budgeting CTI
32.7 Integration with SOC and IR teams
32.8 CTI vendor management
32.9 Pitfalls in CTI programs
32.10 Roadmap for program growth
Lesson 33: CTI Metrics and Evaluation
33.1 Importance of CTI metrics
33.2 Operational vs. strategic metrics
33.3 Coverage and completeness
33.4 Timeliness and relevance
33.5 Accuracy and reliability
33.6 Business value alignment
33.7 Maturity frameworks
33.8 ROI demonstration in CTI
33.9 Dashboards for CTI metrics
33.10 Case study: CTI program evaluation
Lesson 34: Threat Modeling in CTI
34.1 Threat modeling fundamentals
34.2 STRIDE methodology
34.3 PASTA framework
34.4 DREAD scoring
34.5 Use of CTI in threat models
34.6 Threat modeling for cloud systems
34.7 Threat modeling for IoT
34.8 Automation in threat modeling
34.9 Pitfalls in modeling exercises
34.10 Case study: financial services
Lesson 35: Cyber Threat Intelligence in Incident Response
35.1 Role of CTI in incident response (IR)
35.2 Linking CTI to IR lifecycle
35.3 Using CTI for triage and prioritization
35.4 CTI support for containment
35.5 CTI in forensic investigations
35.6 Post-incident CTI reporting
35.7 Lessons learned process
35.8 CTI-IR collaboration models
35.9 Threat actor re-entry risks
35.10 Case study: breach response with CTI
Lesson 36: CTI in Threat Detection and SIEM
36.1 CTI enrichment of SIEM alerts
36.2 IOC integration into SIEM
36.3 Use cases for CTI in detection
36.4 Threat scoring in SIEM
36.5 CTI-SOC analyst workflows
36.6 False positive reduction
36.7 Correlation rules with CTI
36.8 SOAR automation with SIEM+CTI
36.9 Metrics for CTI-driven detection
36.10 Case study: SOC efficiency boost
Lesson 37: CTI for Threat Hunting Operations
37.1 CTI-driven hunting use cases
37.2 Hypothesis-based hunts with CTI
37.3 Leveraging ATT&CK for hunts
37.4 Endpoint telemetry + CTI correlation
37.5 Hunting malicious infrastructure
37.6 Machine learning aided hunting
37.7 Proactive IOC searching
37.8 Sharing hunting outcomes as CTI
37.9 Hunt to detection pipeline
37.10 Case study: detecting persistence mechanisms
Lesson 38: Intelligence-Led Penetration Testing
38.1 Concept of intelligence-led red teaming
38.2 CBEST/TIBER frameworks
38.3 Adversary emulation plans
38.4 Intelligence collection for red teams
38.5 Threat modeling in pen testing
38.6 CTI-informed target selection
38.7 Reporting findings to stakeholders
38.8 Bridging red and blue with CTI
38.9 Case study: bank sector red team exercise
38.10 Limitations of intelligence-led testing
Lesson 39: CTI for Cloud Security
39.1 Cloud threat landscape
39.2 Cloud-specific attack vectors
39.3 Cloud misconfigurations intelligence
39.4 Monitoring SaaS and IaaS platforms
39.5 Cloud logs as intelligence sources
39.6 Cloud threat actor case studies
39.7 CTI for hybrid and multi-cloud
39.8 Cloud security threat modeling
39.9 Regulatory requirements in cloud CTI
39.10 Case study: Cloud provider breach
Lesson 40: CTI for IoT and OT Security
40.1 IoT threat landscape
40.2 OT vs. IT threats
40.3 ICS threat actors
40.4 Common IoT vulnerabilities
40.5 Intelligence from IoT telemetry
40.6 OT-specific malware (e.g., Stuxnet)
40.7 Threat modeling for OT
40.8 Intelligence sharing in OT sectors
40.9 Case study: Colonial Pipeline
40.10 CTI for critical infrastructure defense
Lesson 41: Emerging Technologies in CTI
41.1 AI and ML in CTI
41.2 Big data analytics
41.3 Blockchain for CTI
41.4 CTI in 5G networks
41.5 Quantum computing implications
41.6 CTI in autonomous vehicles
41.7 Threat intel for edge computing
41.8 Zero trust architectures and CTI
41.9 Integration of CTI with DevSecOps
41.10 Future trends in CTI technology
Lesson 42: Deception and Counterintelligence in CTI
42.1 Cyber deception fundamentals
42.2 Honeypots and honeytokens
42.3 Decoy infrastructure intelligence
42.4 Counter-reconnaissance
42.5 Disinformation as defense
42.6 Legal implications of deception
42.7 Psychological operations in cyberspace
42.8 Counter-intelligence use of CTI
42.9 Case study: adversary deception traps
42.10 Ethical concerns in counterintelligence
Lesson 43: Intelligence Gaps and Biases
43.1 Types of intelligence gaps
43.2 Gap analysis methodologies
43.3 Common analyst biases
43.4 Mitigating confirmation bias
43.5 Anchoring and availability bias
43.6 Overconfidence in attribution
43.7 Source selection biases
43.8 Peer review to reduce bias
43.9 Case study: misattribution errors
43.10 Continuous improvement cycle
Lesson 44: Case Studies in Cyber Threat Intelligence
44.1 Stuxnet campaign analysis
44.2 Sony Pictures breach
44.3 Target 2013 breach
44.4 WannaCry outbreak
44.5 NotPetya campaign
44.6 SolarWinds supply chain attack
44.7 Colonial Pipeline incident
44.8 Ukraine grid cyberattacks
44.9 Hafnium Exchange Server exploit
44.10 Lessons learned from case studies
Lesson 45: Building Adversary Profiles
45.1 Components of adversary profiles
45.2 Adversary objectives and motivations
45.3 Infrastructure analysis
45.4 Toolkits and malware usage
45.5 TTP documentation
45.6 Campaign timelines
45.7 Linking multiple campaigns
45.8 Profile validation techniques
45.9 Presentation formats for profiles
45.10 Case study: Lazarus Group
Lesson 46: CTI for Risk Management
46.1 Risk management frameworks (NIST, ISO)
46.2 CTI integration with risk assessments
46.3 Threat-informed risk decisions
46.4 CTI for third-party risk
46.5 Vulnerability prioritization with CTI
46.6 CTI in supply chain risk
46.7 Metrics for CTI in risk management
46.8 Cyber insurance implications
46.9 CTI for board-level risk reporting
46.10 Case study: risk mitigation via CTI
Lesson 47: CTI in Security Awareness Programs
47.1 CTI role in employee awareness
47.2 Real-world phishing scenarios
47.3 Industry-specific awareness training
47.4 Insider threat awareness campaigns
47.5 Tailored CTI for executives
47.6 Using threat reports in awareness
47.7 Metrics for awareness success
47.8 CTI in tabletop exercises
47.9 Continuous awareness improvement
47.10 Case study: phishing simulation results
Lesson 48: CTI in Law Enforcement and National Defense
48.1 Law enforcement use of CTI
48.2 National CERT roles
48.3 Cyber defense agencies
48.4 Military applications of CTI
48.5 CTI in counter-terrorism
48.6 International collaboration efforts
48.7 Public-private partnerships
48.8 Legal constraints in operations
48.9 Case study: FBI ransomware takedown
48.10 CTI role in national cyber strategy
Lesson 49: CTI Career Development and Skills
49.1 CTI analyst career paths
49.2 Core CTI skills
49.3 Technical vs. analytical CTI roles
49.4 Certification paths (GCTI, etc.)
49.5 Building an analyst portfolio
49.6 CTI internships and training programs
49.7 Networking in CTI community
49.8 Publishing CTI research
49.9 Soft skills for CTI analysts
49.10 Future career trends
Lesson 50: Future of Cyber Threat Intelligence
50.1 Evolution of threat landscapes
50.2 AI vs. AI in cyber conflict
50.3 Global cybercrime cooperation
50.4 Expansion of CTI automation
50.5 Fusion of CTI with physical intel
50.6 Privacy and human rights debates
50.7 Standardization in CTI practices
50.8 CTI for small/medium enterprises
50.9 Predictive intelligence advances
50.10 Final reflections: where CTI is heading