What is Threat Hunting in cybersecurity?

The process begins with thorough preparation, which involves setting up the necessary tools and defining the scope of the hunt. The specific environment or systems to be monitored are identified, and resources like threat intelligence, logging data, and access to relevant tools (such as SIEM and endpoint detection solutions) are gathered. During this stage, the team establishes clear goals for the threat hunt, ensuring that all team members are trained and aligned with the objectives. Additionally, a hypothesis or scenario is defined that the hunt will focus on, such as detecting lateral movement or identifying signs of malware persistence.

In this step, a hypothesis is generated to guide the threat hunt. This hypothesis is an educated guess based on the organization's threat landscape, past incidents, and knowledge of the environment. For example, the hypothesis might suggest that an attacker could be using compromised credentials to access sensitive data or that malware might have persisted in the network through unauthorized remote access tools. The hypothesis serves as a starting point for the investigation, providing direction while remaining flexible enough to adapt as new information is uncovered during the hunt.

Once the hypothesis is established, the next step is to collect relevant data from various sources across the organization. This includes gathering logs, network traffic data, and endpoint activity. Tools like SIEMs, EDR (Endpoint Detection and Response), and network monitoring systems are used to aggregate and analyze this data. It’s essential that the data collected is comprehensive, covering all potential vectors and areas of interest, such as endpoints, network traffic, and cloud environments. The goal is to have a rich dataset that will allow for thorough analysis in the subsequent steps.

With the data collected, the focus shifts to analyzing it to identify patterns, anomalies, and indicators of compromise (IOCs) that align with the hypothesis. This step involves both automated tools and manual analysis to sift through large volumes of data. The analysis looks for unusual patterns, such as unexpected outbound network connections, abnormal user behavior, or suspicious file modifications. By correlating data across multiple sources, potential threats can be identified that might not be obvious from a single dataset. If needed, the hypothesis may be refined based on the findings, narrowing the focus of the investigation.

After identifying suspicious activities during the analysis, an in-depth investigation is conducted to confirm whether they are legitimate threats or false positives. This involves a deep dive into the suspicious activity to understand its nature, scope, and potential impact. The investigation might involve tracing the origins of the activity, determining if it is part of a broader attack, and assessing the potential damage or data exfiltration. If the threat is confirmed, the threat hunting team may engage with other teams, such as incident response or forensic analysis. The findings are documented, and decisions are made on the next steps based on the outcome of the investigation.

Once a threat is confirmed, the next step is to respond and mitigate it to prevent further damage. This involves collaborating with the incident response team to contain and eradicate the threat from the environment. Mitigation measures might include isolating affected systems, revoking compromised credentials, and applying security patches. The actions taken are communicated to relevant stakeholders within the organization to ensure that everyone is aware of the situation and the steps being taken to resolve it.

The final step is to use the insights gained from the threat hunting process to improve the organization’s security posture. This includes updating threat intelligence feeds, detection rules, and security controls based on the findings. A post-hunt analysis is conducted to identify areas for improvement in the threat hunting process, tools, or techniques. The lessons learned are shared with the broader security team to enhance future threat hunts. Documentation of the hunt is also important for historical reference and compliance purposes.

To enhance efficiency and effectiveness, automation is introduced into the threat hunting process, particularly for repetitive tasks like data collection and initial analysis. A feedback loop is established where insights from completed hunts inform future hunts, refining hypotheses and improving detection capabilities. The process is continuously updated with the latest threat intelligence and observed threats to ensure it remains effective against evolving cyber threats.