Staying ahead of malicious actors is a continuous challenge for governments and organizations worldwide. Cybersecurity can no longer be reactive. And with the shift to a more proactive approach, threat hunting continues to gain in popularity and sophistication. Instead of waiting for alerts or incidents to occur, organizations now actively search for signs of compromise, anomalies, or potential threats within their systems. The use of security automation has become pivotal in expediting threat hunting by leveraging technology to streamline processes, analyze data at scale, and respond rapidly to potential threats.

The Role of Security Automation in Threat Hunting

Security automation, including the use of security automation, orchestration, and response (SOAR) solutions, increases the efficiency and precision of threat hunting activities. Automation empowers cybersecurity teams to streamline their processes, enhance their detection capabilities, and respond more rapidly to potential threats. Here’s an in depth look into the ways automation improves the threat hunting process:

Rapid Data Collection: The sheer volume of data generated by systems and networks can overwhelm manual analysis. Automation tools can collect and analyze logs, many times with the help of machine learning algorithms and AI-driven tools, from various sources to identify anomalies or known suspicious patterns that might escape human observation. These systems can also continuously monitor network traffic and behavior and instantly flag common methodologies used by actors to exploit systems and networks.

Threat Intelligence Aggregation: Using security automation, it is much easier to aggregate and correlate threat intelligence from various sources. By integrating threat feeds, vulnerability databases, and historical attack data, these systems consolidate the external and internal data about known threats, attack vectors, and vulnerabilities, enabling analysts to identify potential threats and their scope and their impact more effectively.

Behavioral Analysis: Using more sophisticated automations, organizations can use behavioral analysis to establish baselines for normal system behavior. Specific deviations trigger alerts, indicating potential threats or unusual behavior. These tools continuously monitor activities, allowing for real-time detection of anomalies, configuration changes, threat behaviors, and threat indicators. With the addition of AI and machine learning, these tools may even recognize patterns and anomalies that might evade traditional rule-based detection.

Incident Response Orchestration: Using automation in the threat hunting process facilitates a quicker and more coordinated response. Threat hunters study and pattern out adversary behaviors, quantify the tradecraft observed, and then test the techniques to build detection content and determine the most effective response actions. They build high-fidelity detections that are both actionable and universal to ensure alerts can detect the techniques used by adversaries of all skill levels. When orchestrating incident response, it’s important for threat hunters to leverage past investigations, research, and testing to provide key artifacts, useful content, and the most effective response actions to the analysts working the incident. This threat-based approach improves the quality of the tools and knowledge provided while enabling swift, effective responses that have been tested and tuned for the specific environment. This ensures that when a detection occurs there’s high confidence it is a true positive, and it also contains the context necessary for reporting and response.

Continuous Improvement: In threat hunting, speed and accuracy are king. By using automation, threat hunters increase the speed of remediation by already having research, scripts, queries, and response actions staged and ready to provide to the analysts working an incident. Accuracy is improved significantly when pairing together threat hunting and automation by ensuring that the queries, scripts, and response actions have already been tested and verified—over days and weeks rather than as an incident unfolds—as the most effective methods for remediation. Accuracy is enhanced because of the consistency that automation brings to a SOC. Each analyst is provided the same resources and context with all technical documentation and open-source intelligence (OSINT) sources carefully selected based on their value to an incident responder. The analyst gets a clearer picture of the incident and is equipped with the most effective actions to take immediately to reduce its overall impact.

The Future of Automated Threat Hunting

The impact of a security incident to an organization largely depends on how fast an incident response team can transition from detection to containment. Incident response triage begins with a detection from monitoring and threat hunting and ends with a clear picture of the incident, the systems involved, and a plan to stop the progress of the attack. This process includes initial assessment, information gathering, analysis, and then the reporting of findings. Using automation and SOAR platforms makes this entire process flow more smoothly and efficiently by providing analysts with a “decision advantage.” By utilizing security automation with threat hunting, organizations can bolster their defenses against sophisticated cyber threats and enable a more proactive security posture.