# About the connection between threat intelligence, analysis and modeling ### šŸ”„ Interplay Overview |Concept|Role in Cybersecurity|How It Connects to the Others| |---|---|---| |**Threat Intelligence**|Collects and delivers data on threats|Feeds raw data into analysis and modelling| |**Threat Analysis**|Interprets and assesses threat data|Uses intelligence to evaluate risks and impact| |**Threat Modelling**|Maps out potential attack paths and scenarios|Uses analysis to simulate and prioritize threats| --- ### šŸ§  Threat Intelligence ā†’ šŸ” Threat Analysis - Threat intelligence providesĀ **real-time data**Ā on threat actors, malware, vulnerabilities, and attack trends. - Analysts use this data toĀ **identify patterns**,Ā **assess relevance**, andĀ **prioritize risks**Ā based on the organization's context. ### šŸ” Threat Analysis ā†’ šŸ§© Threat Modelling - Analysis helps determineĀ **which threats are most likely and impactful**. - This guides threat modelling to focus onĀ **realistic attack scenarios**, not just theoretical ones. ### šŸ§© Threat Modelling ā†’ šŸ§  Threat Intelligence - Threat modelling revealsĀ **gaps in visibility**Ā orĀ **missing threat data**. - These insights can refine intelligence collection efforts, ensuring more targeted and useful data. --- ### šŸ›”ļø Real-World Example Imagine a financial institution: 1. **Threat Intelligence**Ā detects a surge in phishing campaigns targeting banking apps. 2. **Threat Analysis**Ā reveals that attackers are exploiting MFA fatigue and targeting mobile users. 3. **Threat Modelling**Ā simulates how these attacks could bypass defenses and identifies weak points in mobile app authentication. This leads to: - Updating detection rules. - Strengthening MFA protocols. - Training users on phishing awareness. --- Together, these disciplines create aĀ **feedback loop**Ā that strengthens an organization's ability toĀ **predict, prevent, and respond**Ā to cyber threats. Would you like a visual diagram or a case study to illustrate this further?