Hypothesis Driven
| Revised Date | Comment |
|---|---|
| 06.10.2024 | Improved formatting and wording |
Introduction
Hypothesis-driven threat hunting is a structured approach that involves creating and testing specific hypotheses about potential threats based on known attacker behaviors and tactics, techniques, and procedures (TTPs). This method is highly strategic and leverages the knowledge and expertise of threat hunters, as well as detailed frameworks such as MITRE ATT&CK.
Key Concepts
Hypothesis Generation: Formulating specific hypotheses about potential malicious activities. These hypotheses are informed by threat intelligence, recent incidents, and an understanding of the organization’s specific risk profile.
Data Collection: Gathering targeted data that can validate or refute the hypothesis. This might include system logs, network traffic data, endpoint activity logs, and other relevant information.
Analysis and Investigation: Using advanced analysis techniques to investigate the collected data. This involves forensic analysis, correlation with other data sources, and contextual analysis to validate or refute the hypothesis.
Iterative Process: Continuously refining hypotheses based on findings from previous investigations. This iterative approach helps in adapting to new threats and improving the effectiveness of threat hunting over time.
Techniques and Tools
MITRE ATT&CK Framework: Utilizing the MITRE ATT&CK framework to inform and structure hypotheses based on known adversary behaviors and TTPs.
Threat Intelligence: Leveraging threat intelligence to inform hypotheses about potential threats. This includes information on adversaries, their TTPs, and indicators of compromise (IoCs).
Forensic Analysis: Conducting in-depth forensic analysis of collected data to uncover evidence of malicious activities. This can involve examining file system artifacts, memory dumps, and network packet captures.
Correlation and Contextual Analysis: Correlating data from multiple sources to validate hypotheses. This involves looking at the broader context of detected anomalies and linking them to known threat patterns.
Steps in Hypothesis-Driven Threat Hunting
Hypothesis Formulation: Formulate hypotheses about potential threats based on available intelligence and understanding of the organization’s risk profile. For example, a hypothesis might be that an adversary is using PowerShell to execute malicious scripts on endpoints.
Targeted Data Collection: Collect relevant data that can test the hypothesis. This might include logs from endpoints, network traffic data, PowerShell logs, and other pertinent information.
Data Analysis: Apply advanced analysis techniques to investigate the collected data. Use forensic tools, correlation methods, and contextual analysis to uncover evidence supporting or refuting the hypothesis.
Investigation: Conduct a thorough investigation of suspicious findings. Use threat intelligence, additional logs, and forensic analysis to confirm or refute the hypothesis.
Response and Mitigation: If the hypothesis is confirmed, initiate appropriate response actions. This could include isolating affected systems, blocking malicious activities, and remediating any damage.
Feedback and Refinement: Incorporate findings into future hypothesis generation. Refine detection models and update threat intelligence to improve the effectiveness of subsequent threat hunting efforts.
Advantages and Challenges
Advantages:
- Focused Approach: Allows for targeted investigations based on specific hypotheses.
- Expert Knowledge: Leverages the expertise of threat hunters and detailed frameworks like MITRE ATT&CK.
- Adaptability: Can quickly adapt to new threats based on the iterative refinement of hypotheses.
Challenges:
- Complexity: Requires a deep understanding of threat intelligence and attacker behaviors.
- Resource Intensive: Demands significant time and resources to formulate and test hypotheses.
- Data Dependency: Relies on the availability and quality of data to validate hypotheses.
Conclusion
Hypothesis-driven threat hunting is a strategic and focused approach to detecting and mitigating cyber threats. By leveraging detailed threat intelligence and frameworks like MITRE ATT&CK, this method enables targeted investigations based on specific hypotheses. While it involves complexities and requires significant resources, its ability to adapt to new threats and continuously improve makes it a vital component of a comprehensive cybersecurity strategy.