User Behavior based Threat Intel


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Publish Date :

September 4, 2022

User Behavior based Threat Intel 

Security automation has outperformed human psychology. Yes, you got it! I’m talking about bots that were created by humans, built to think like humans, for the humans, but the best part is they are not humans. That sounds fascinating, isn’t it? But ever wondered how on earth can machines learn to think like humans and even behave like humans? That’s not it. Like every superhero film where there’s a superhero and a villain, the bot here can be a superhero and a villain at the same time. Okay, this does not sound fascinating to me at all. Moreover, a lot of such bots can change their nature based on how the user behaves. Therefore, user and entity behavior plays a vital role in understanding what activity of theirs can be a threat to the business. This is where Threat Intelligence must be developed and adopted by organizations. 

Threat Intelligence Definition 

“Threat intelligence” is a modernized term for an analysis that can read an adversary’s intent, opportunity, or rather capability to harm the system. However, it cannot be achieved magically by any tool. The information must be fed into the tool by actual users that classify as organizational gaps. However, this is not something that a user must feed into the tool like a data entry sort of activity. Instead, the tool must be capable enough to learn regular user behaviour activity and classify if there are gaps in the ways of their working. Cyber threat intelligence thus highlights a high multiplier for enterprises looking to institutionalize their threat detection and response, especially when the threats arise from their very own users. Human threats are considered the most common ones that large organizations usually ignore because they tend to forget the very cause of the vulnerabilities that arose. Threat intelligence focuses on anticipating those indefatigable human threats with revolutionized technology to defend them. 

Importance of Threat Intelligence 

Threat intelligence enterprise solutions are designed to learn and collect raw data from multiple sources that could eventually materialize threat actors or, instead, potential threat activities. Threat intelligence tools can help companies attain valuable user behaviour information that could be potential threats that otherwise go unnoticed. Therefore, this data can be used against building a threat intelligence matrix that will lead to well-defined defence mechanisms to mitigate floating risks capable enough to damage an organization’s business as a whole. In a nutshell, all targeted threats require targeted defence which can be proactively delivered by threat intelligence. The primary purpose of this type of security defence mechanism is to keep enterprises aware of user behaviour activities and to protect against zero-day malware attacks and advanced threats and exploits. A few salient features of having a threat intelligence mechanism in place are: - To learn, mitigate, and provide future security against insider or human threats. - Curb persistent threats and exploits. - Identify the attack surface and advance your security posture. - By far the obvious one - to keep all stakeholders updated with user integrated reporting. 

How to build an effective Threat Intelligence Program?

Companies across the globe are rapidly growing their business but so are the threats constantly advancing, probably with speed two times greater. As a result, it becomes an increasing two-fold pressure on businesses to identify and manage emerging vulnerabilities across the threat landscape. However, a sought-after threat intelligence program design can benefit the organization in the real world. This can be designed by following a few essential security elements such as: 

  •  Identifying common indicators of compromise (IOC) 
  •  Recommend mitigation steps once all the IOCs have been accumulated 
  •  Hypothesis generation 
  •  Comprehend organizational user information and knowledge gaps 
  •  Learning and unlearning false positives 
  •  Integrating user behavior analytics, applications in use to build a threat, intelligent interactive model 
  •  Learning adversary intentions 
  •  Building a data collection framework 
  •  Analyze threat intelligent produced reports 

This general threat intelligence framework can be easily tailored to fit organizational elements to drive practical intelligence within the system. The goal of every organization is always to protect its system and infrastructure. But little do they know that it is vital for them to define the specifics around it to achieve that goal. Let’s take a contingent approach and look at the above categories that define the very foundation of a cyber threat intelligence framework. 


First and foremost, organizations must take a step back and start gathering critical requirements such as a list of Prioritized Intelligence elements. Defining an outline is a crucial step that can easily be achieved by asking questions like what we’re looking for? How will the specific data help us achieve threat intelligence? What can be done with the data? Etc. 


Once organizations have a clearly defined Prioritized intelligence list of elements, the next step would be to plan how to collect the required amount of data. To implement this data collection proposal, it is now time to figure out all the user entities that can hold enough raw data to be used as threat intelligence—for instance, endpoints. Endpoints can be surprisingly a great way to start collecting raw logs, especially because user endpoints are most likely the most vulnerable targets for cybercriminals. 


Data logs can be useless unless we can make sense of them. This brings us to our next step in the framework, i.e., Analysis. Unbeknownst, this is the most crucial step out of all. Businesses can ideally analyze large chunks of data logs in mainly two different ways: Manually and Automatically. In 2021, most likely automation is the key to driving effective and speedy Analysis of enormous data volumes. In the age of artificial intelligence and machine learning, Analysis can be done just with a button click. However, everything comes with a price tag. 


 Once we have collected all data sources from where the data will be ejected and analyzed, it is at this level that organizations must think about how to integrate this framework with multiple tools or possible third-party vendors too. Multiple vendors may have their policies and processes to integrate. These also include specific limitations. But this is where the flexibility of cutting-edge tools comes to play. This is why selecting your tools right can get you where you want to be in the hardest of times. 


Ultimately, the final step to implement a practical cyber threat intelligence framework is a sophisticated dissemination plan. Of course, this must include well-defined alerts. Alerts to limit detection of false positives, which can be remediated as soon as possible. However, the idea is not just to define alerts and remediate them manually. The essential element is to automatically remediate the intelligent alerts that are thrown at the system. Keeping this in mind, it is pivotal to execute a design to predict potential attacks on the system. 

So how will a Cyber Threat Intelligence (CTI) solution help one’s organization? By building a threat intelligence framework, security architects and analysts will regain immense amounts of confidence in narrowing down real-time attacks in much less time. In addition, they will become more proficient in predicting plausible cyber threats even before it strikes. As organizations grow, the amount of data inflow grows exponentially. Imagine controlling this data with an effective cyber threat intelligence program in place. Sounds good, right? Yes, it does. Internal teams will be well-equipped with enough data to protect your business. After all, what better than knowing the adversary’s malicious intent well in advance.

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