64. Advanced Threat Intelligence Analysis

Introduction

Threat Intelligence Analysis is an indispensable part of effective cybersecurity. Without understanding the nature and evolution of threats, companies and organisation are incapable of effectively mitigating risk and defending against attacks. Organisations regularly face Advanced Persistent Threats (APTs) which require advanced analysis techniques to detect and neutralise. This lesson explores such techniques.

Understanding Advanced Persistent Threats (APTs)

Advanced Persistent Threats (APTs) are sophisticated, organised and continuous cyber threat attacks that target specific organisations for a specified period (source). APTs take time to plan and execute, often by well-funded criminal or state-sponsored groups.

Phases of APTs

1. Reconnaissance: Cybercriminals research, identify, and select targets.
2. Initial Exploitation: Intrusion into the network via phishing, network vulnerabilities, or social engineering.
3. Establish Foothold: The hacker installs malware to create a backdoor in the network.
4. Privilege Escalation: The threat actor gains higher-level privileges on the network.
5. Internal Reconnaissance: The attacker maps the internal network and profiles assets and servers.
6. Lateral Movement: The attacker infiltrates other network areas.
7. Maintain Foothold: Additional security measures are established to secure ongoing control.
8. Complete Mission: Actions directed by the objective are executed – data theft, corruption, or exfiltration, for instance.

Threat Intelligence Analysis

Threat Intelligence Analysis makes it possible to understand and combat APTs more effectively, by conducting in-depth research, correlation and analysis of cyber threat data and intelligence.

Techniques for Advanced Threat Intelligence Analysis

1. Information gathering: Using open source intelligence (OSINT), threat analyst collects data from various sources like logs, network traffic, security devices etc. (source).
2. Data analysis: The information collected is analysed to identify patterns, anomalies, activities or behaviours that signify cyber threats.
3. Threat intelligence feed: Threat intelligence feeds offer real-time information about potential threats from various providers such as OTX, Recorded Future, etc. (source).
4. Machine Learning (ML) and Artificial Intelligence (AI): ML and AI models are used to advanced threat analysis by speeding up data analysis and helping to predict new threat patterns.

Best Practices

1. Threat intelligence analysis should aim towards proactive instead of reactive responses, i.e., prevention rather than mitigation.
2. Threat intelligence should align with organisational requirements and capacity. Overstretched resources may reduce effectiveness.
3. Sharing threat intelligence within the community can often lead to collective better defence.
4. Performing regular risk assessments based on your threat intelligence can keep your cybersecurity strategy aligned with current threats.

Conclusion

The critical point of Advanced Threat Intelligence Analysis is anticipation. Organisations must be prepared for emerging threats and able to respond promptly and effectively to incidents. A detailed threat intelligence analysis provides a dynamic and robust cybersecurity posture that evolves with the changing threat landscape.

Recommended Readings

1. Learning from the Enemy: Advanced Threat Intelligence
2. 10 threat intelligence tools to keep you ahead of emerging threats