In the previous blog, we covered the basics, what threat hunting is, why it matters and the key frameworks behind it, With that foundation in place, you’re ready to go deeper
In this part, we’ll walk through the actual threat hunting process, step by step. We will talk about how hunts are planned, executed, and refined. We’ll also cover how to measure the success of a hunt, so you can continually improve and show real impact of your hunts
Threat Hunting Process
Before you start hunting, it’s important to understand the ingredients that make a successful hunt possible. It all starts with data, lots of it. Your ability to spot threats heavily depends on how well you’re watching your environment. If there are blind spots, attackers could slip through unnoticed. But collecting data is not enough on its own. You also need to know what “normal” looks like, a solid baseline. That way, unusual behavior stands out more easily.
Now, if you are an MSSP working with multiple clients, that gets trickier because “normal” is different for everyone.That’s where machine learning can be a powerful tool to help spot anomalies
And finally, there is threat intel. Hunters live off it. Whether it’s IOCs, IOAs, or fresh threat reports, this intel helps you know what to look for and where to dig
With these key pieces in place, you are ready to move through the hunting process.
Threat hunting is not guesswork, it’s a structured loop that allows security teams to proactively identify threats and improve overall detection. Here's a breakdown of the key part of the process.
The first step is to ask the right questions. A good hypothesis gives your hunt a clear direction. Start by focusing on three main questions:
Getting clear answers to these questions helps you focus and hunt smarter.
To build your hypotheses you can use threat intel, recent threat reports, or by mapping potential attacker behavior with frameworks like MITRE ATT&CK. This way, you’re hunting with purpose
Once you have your hypothesis. The next step is to put it to the test using the right tools and techniques.
Once a hypothesis is tested, it can either be confirmed or disproved. If it is confirmed, you now need to evaluate the threat: Is this a major incident? Has the attack just started? Could this be a false positive? These are important questions to answer before deciding on next steps.
A confirmed hypothesis can also uncover new TTPs, which should be documented and shared for future detection and defense.
On the other hand, a disproved hypothesis does not mean it was a bad one. Sometimes, it simply means you did not have the full picture, maybe there was not enough data or visibility to confirm anything yet. In that case, you can refine the hypothesis, adjust your approach, and try again.
“Every hunt, whether it leads to a discovery or not, helps you learn more about your environment and makes the next hunt even sharper.”
Successful hunts don’t just stop at finding a threat, it helps you get better at catching the next one, and the insights gained can be used to fine-tune detection rules, this way, analysts are not stuck repeating the same tasks, they can focus on spotting new, unknown threats instead.
Also to save time you can automate parts of the process by setting up scheduled searches or using machine learning.
“The more you hunt, the more you understand your environment, and the stronger your defenses become.”
How to Measure Hunt Success?
At the end of the day, you need to know if your threat hunting efforts are actually making a difference and your work is helping catch threats earlier. So it's important to track the impact of your hunts. Here are some key ways to measure that success:
Keep track of how often you uncover real threats, especially the serious ones. This gives you a good sense of how effective your hunts are at catching what matters
Track how many hosts are found to be compromised over time. This helps you understand trends and sheds light on the state of your endpoint security.
Dwell time refers to how long a threat has been sitting in your network before being detected. Measuring this can tell you if certain attack stages are being missed for too long.
If threats are sitting unnoticed for too long, it might be a sign that you are focusing too much on certain parts of the kill chain and missing others.
One of the biggest goals of hunting is to uncover blind spots. When a hunt results in new detection rules or logic that closes a gap, that’s a big success, you have just made your defenses stronger.
Sometimes a hunt doesn’t lead to an incident, but it still teaches you more about your environment.
Maybe it reveals misconfigurations or areas where logs were missing. That’s still a win
If you turn a hunting discovery into a detection rule, it’s worth tracking how accurate it is.
Too many false positives waste analyst time, so keep fine-tuning your rules as needed.
“Threat hunting is not just about finding the bad stuff, it is about improving your overall security posture.”
Conclusion
Threat hunting is all about digging deeper to find what others might miss. Every successful hunt not only uncovers hidden threats but also strengthens your defenses by closing detection gaps. By continuously learning and improving, you make your environment safer and more resilient against attackers.
In the next blog, we’ll explore how large language models (LLMs) are reshaping threat hunting and helping security teams work smarter and faster. Stay tuned!
References:
https://www.threathunting.net/files/hunt-evil-practical-guide-threat-hunting.pdf
