Stewart Bertram

Elemendar’s READ. platform uses proprietary Machine Learning (ML) technology to extract entities in STIX and MITRE ATT&CK formats from unstructured text (check out this blog for more details). In plain terms, we teach machines to replicate a very specific human task: mapping text strings to more abstract categories such as

Here at Elemendar we spend a lot of time talking to the global Cyber Threat Intelligence (CTI) analyst community. While we are well versed in all aspects of CTI, the main topic of conversation is typically Artificial Intelligence (AI) and the role of Machine Learning (ML) within structuring unstructured data.

Pictured (from left to right) Stewart Bertram, Giorgos Georgopoulos and Ben Strickson The RSA Conference hosted in San Francisco burst back onto the cyber security scene after a two year COVID enforced hiatus – and some of the Elemendar team were there to see it!  So, what were the main

Elemendar’s READ. uses machine learning techniques to add structure to unstructured data in a STIX format. Given how much of the world’s Cyber Threat Intelligence (CTI) data is stored in an unstructured format, the strategic design rationale behind the READ. tool is obvious; however, we have found that some of

The MITRE ATT&CK framework has, quite rightly become one of the cornerstones of modern cyber threat intelligence. For those not aware of the framework, the core of the system is the ATT&CK Navigator, shown below: Figure 1: MITRE ATT&CK framework (X and Y axis) The X Axis in Figure 1

Cyber analysts using Elemendar’s READ. AI for CTI application can now analyse multiple cyber threat intelligence (CTI) reports together! This is the ability for a user to combine the analysis from multiple documents into a single view for further analysis. Read on to see this illustrated using READ.’s inbuilt graph

STIX (Structured Threat Information eXpression™) and TAXII (Trusted Automated Exchange of Intelligence Information™) have become the de facto standards for the exchange of Cyber Threat Intelligence between Threat Intelligence Platforms. Developed since 2015 under the sponsorship of the US Department of Homeland Security, STIX and TAXII have become so influential

Some of Elemendar’s core clients for our flagship product READ. are cyber threat intelligence vendors looking to enrich their text-based reports with our software. CTI vendors may be some of our core customers however, the CTI market is a big place full of a multitude of service offerings and business

One of the many unique challenges of CTI that differentiates it from other forms of threat intelligence, is the need to integrate significantly more pieces of component into CTI assessment as opposed to say a ‘bomb and bullet’ based assessment.  With CTI, the devil really does lie in the details

Every now and then in the world of cyber threat intelligence, a report is released that changes the game and reshapes our view on the Threat Landscape. Shadows in the Clouds and APT 1 are two of these reports that immediately spring to mind when one applies the “strategically significant”