How to Automate Threat Hunting

Threat hunting involves proactively searching for threats that may be sitting undetected in the network. For organizations looking to gain the upper hand against cybersecurity threats threat hunting is an essential component of their security toolkit. 

Take advanced persistent threat (APT) as an example. In these cases, a stealthy attacker can cause a lot of damage to your business without you ever knowing it, hiding in your system for months or even years at a time. Once an attacker has gained access, they can move laterally throughout your network, compromising further areas and stealing credential information.

To combat these sophisticated threats implementing threat hunting measures gives you the ability to respond quickly unlike traditional measures such as firewalls and antivirus that are often not enough. Manual threat hunting can be very labor-intensive and time-consuming and there is a severe skills shortage in the industry. To help cover the gap, many security organizations are automating easily replicable tasks that will perform some of the threat hunting tasks or make them easier. 

Automation is one of the strongest assets you can leverage in the race against cybersecurity threats. It frees up your human analysts to focus only on critical threats and helps reduce human error. Automation is also key to enabling a DevSecOps work process, which in turn enables faster and more efficient production cycles.

Automating threat hunting can help you accelerate your network security process, reduce operating costs and improve your capacity to mitigate advanced cybersecurity threats in time.

Software Automation for Simple Tasks

All cybersecurity measures, including threat hunting tasks, involve predictable processes that can be replicated by software. You can train software to search for anomalous events, prioritize events with higher risk, and even respond to lower-level threats. Automation allows you to scale these processes up, with each task taking just a fraction of the time it would take a human analyst to perform. The software mimics the actions of security analysts and requires humans to configure it to work effectively.

The following are critical threat hunting tasks that lend themselves to automation:

Event Analysis

It can be a challenge to manage the large number and variety of security events and its associated features. A single application can have thousands of events and the nature of those events may change with each new update. 

Automating event analysis will classify security events quickly and significantly increase the scope of events you can examine. An automation platform can analyze millions or even billions of events in a very short space of time.

Factor identification

Separating the wheat from the chaff is one of the most time-consuming aspects of threat hunting. Some factors are more relevant for threat detection than others, and it is important to focus your analysis on those factors that matter. What these factors are will depend on the specific organization and its patterns of user behavior and resource usage.

You can automate factor identification with machine learning that will follow the instructions of an analyst. Advanced machine learning models can over time learn to discover relevant factors by themselves, building on the initial categories set out by the security team.

Data enrichment

Enriching the data collected from monitoring tools will make it more useful for predictive analytics. Data enrichment involves combining, correcting or adding to data, and it requires special expertise to understand what data needs to be enriched and how. To automate this process, you can use data enrichment tools that automatically group similar events and perform an analysis of root causes.

Advanced Investigation with Artificial Intelligence

By combining powerful data analysis and machine learning you can make your investigation more efficient and accurate. Machine learning applications can sift through the mass of security data and convert it into actionable information. Machine learning is an efficient way to detect irregular activities that may indicate malicious behavior and can help you detect threats at scale. 

This approach does not replace the human element altogether but rather accelerates the intelligence-gathering process, so that security analysts and engineers can respond to prioritized threats without wasting time and energy on the tedium of filtering irrelevant data for insights. When the AI detects behavioral anomalies, these are treated as hunting leads, which analysts can then investigate to identify threats that may suggest potential malicious behavior. 

Conclusion

Threat hunting automation is not a replacement for human analysts. Automation tools assist analysts in their decisionmaking and cover the execution of threat hunting tasks that would otherwise take a long time to perform. The machines can run 24/7 on a large scale and allow the SOC to focus on specific threats that are a high priority. 

Without automation, threat hunting is impractical for a majority of organizations. With it, security teams may have the advantage and the necessary capabilities to stay ahead of the growing array of sophisticated security threats and help secure the network from cyberattackers. To learn more about automating your processes, read our blog post, “How to Start Security Automation with Exabeam.”