Creating proper cyber range content to conduct realistic exercises can be challenging at times.
That’s why our team at CybExer always seeks to come up with new, innovative solutions that are useful for organizations to create meaningful cyber range content and give their teams the opportunity to improve their cyber resilience.
In this article, we will tell you about the AI analysis that our team conducted to help organizations streamline their content creation process and give you exciting product updates on AI implementation in our platform.
Applying AI to Create Cyber Range Content
Creating content for the cyber range to successfully conduct cyber exercises is oftentimes a challenging and time-consuming process for organizations – this process generally requires a considerable amount of coding of different auxiliary components.
For example, when it comes to conducting a training session about IoT security, the main focus could be on protecting central controllers and management systems. For that, you need specific sensors and actuators that have to be part of a setup.
Deploying physical components for such use cases might be a complex and lengthy process, which is an unnecessary burden that has a negative effect on scalability among other limitations – a simulator itself could be sufficient, but the availability of suitable products is limited in this case.
Creating a simulation of a simple IoT device may involve a lot of tedious coding of interfaces and functionalities that are mandatory only for the successful integration of the simulator into the overall system.
How Can Organizations Use AI to Automate the Content Creation Process on Cyber Range?
In order to make the whole process more efficient, we decided to automate this work with the help of AI by giving the information and specifications of the real product to it.
However, the typical restrictions on context size can make this task challenging, in case the product specifications have to be split into smaller parts or rewritten in a more compact form.
Having the option to use a larger context might allow training conductors to feed a human-readable specification directly to the AI model and ask it to generate a simulation that would be compatible with the given requirements.
Successfully executing this integration gives us the opportunity to use different advanced AI Large Language Models to autonomously develop cyber range content by combining prompts and executing code in a secure testing environment.
This specific analysis was carried out by Google Gemini AI infrastructure, which allowed us to execute our ideas with the advanced approach, pushing Google’s latest AI infrastructure to a breaking point.
What Are the Outcomes and Benefits of This Integration?
Generally, these types of tasks would take many hours of expert developer work just to have a moderate effect on the overall product or service.
However, automating this work using LLM-powered AI infrastructure would allow organizations to streamline their content creation process and make it more efficient. Not to mention the major cut in costs for companies that are in need of low-stakes development efforts.
With the future advancements and developments of this approach, the solution can be developed further to cover more cyber range content development use cases and create larger opportunities to cut down costs for organizations worldwide.
Improving Efficiency and Accuracy of Cyber Exercise Evaluation Process: AI-Assisted Situational Reports
Another application where our team has found the usage of Artificial Intelligence tools incredibly useful is making the exercise evaluation process more efficient and accurate.
Every time our team organizes a Live-Fire or Threat Hunting cybersecurity exercise, Blue Team members create a Situational Report (Sitrep), which aims to capture the goals of a specific exercise and tell about the updates in non-technical terms.
The idea is to communicate the state of a particular exercise with the exercise organizers and give them information about the larger context and state of this activity.
However, the problem is that these Sitrep documents are usually quite lengthy, making it difficult to digest the information in an effective manner. Especially when the exercise is large, and there are many of those documents coming in. Sitreps must follow a specific format and structure as well.
In order to solve this problem, our team has created an AI tool that helps organizations give the main context of a Sitrep and evaluate its accuracy in an effective manner.
The main idea is that whenever an organization is conducting a large cybersecurity exercise with many teams involved, this AI tool, within our cyber range platform, will help them efficiently give an insightful summary and assessment of a Situational Report created by the Blue Teams.
This makes the process faster, more efficient, and more accurate for everyone involved. At the same time, it helps organizers concentrate on other aspects of successfully conducting a cybersecurity exercise.
CybExer Technologies – Leading the Way to Cyber Preparedness
At CybExer Technologies, we have been at the forefront of shaping the cybersecurity industry since 2016. We are committed to providing advanced technologies to help our customers improve their overall cyber preparedness.
If you’d like to learn more about our product and its newest updates, feel free to schedule a call with our cyber range experts to discuss your organization’s needs.
