Intelscale – Threat intelligence at scale

The evolution and the complexity of the Cybersecurity Landscape nowadays is triggered by the continuous development of the computing environment that is integrating new devices, new software and new technologies everyday. In this rapidly evolving environment, responding properly to threats, the investigation and the mitigation of the vulnerabilities becomes a challenge that has to be handled with tools that offer the desired flexibility and scalability.

Intelscale is a scalable and open threat intelligence solution with analytics and machine learning capabilities built together with a team of cybersecurity professionals. Based on open source technology, Intelscale was built to ingest data from any source and in any format, as the core of any reliable threat intelligence solution is to have enough data to provide useful insights for the threats  we are facing.

Intelscale centralizes and curates data sets from heterogeneous systems which are coupled with very powerful, advanced search capabilities for finding and retrieving the required information. Furthermore, Intelscale is capable of doing correlation between the different sources of ingested intel feeds. From a security perspective, having data on cyber attacks is great, but being able to see the possible ramifications of the attacks with other attacks or threats enables you to approach the problem from multiple angles. This leads to faster remediation of the problem and speeds up the mitigation process.

Intelscale was built with scalability and usability in mind. By its nature Intelscale is horizontally scalable, meaning that it can grow dynamically just as your database of threat intelligence grows. Additionally, it provides high availability of the data, having several mechanisms in place which prevent data loss. In terms of usability, Intelscale is built around APIs and therefore is easily integrated with other 3rd party tools. At the same time the solution can also support other data related use cases besides threat intelligence. By integrating machine learning capabilities we enable Intelscale to be able to do two very important things in terms of gathering insights: anomaly detection and predictions. Anomaly detection comes in the form of detecting unusual activity compared to past behavior of either hackers or attacks. This can mean a change in the time of day or the countries in which an attack takes place or the type of attack a hacker uses. This is useful in order to become aware that the pattern of attacks has changed and therefore previous solutions might not apply anymore.When it comes to security a reactive approach is the norm. However, with hackers becoming smarter and more dedicated in their activity, this is no longer enough. A hacker needs to be successful only once to have a negative impact on your organization. With predictive threat intelligence you can determine when and where an attack will take place and prepare accordingly, thus switching to a proactive approach to security.If you would like to find out more about Intelscale, please write to us at: