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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”

Recent events such as the activities of REvil and Log4j have once again underscored the necessity of Cyber Threat Intelligence, a key component of modern cyber defence. However, effectively integrating CTI can be expensive for SOCs and especially so for less well financially resourced operations that are typical of those

Elemendar's AI-based READ. technology assists cyber analysts in processing cyber threat intelligence (CTI) into machine-readable, structured, defensive code, enabling them to faster defend organisations against new and complex cyber threats. READ. now allows users to apply TLP tagging (Traffic Light Protocol) at the entity level. So what does this mean?

London, UK - January 6th 2022 Elemendar is the world leader in developing AI (Machine Learning) to process human-authored cyber threat intelligence into machine-readable, actionable data to enable cyber analysts to better protect their organisations against cyber threats. Elemendar’s technology is used by Governments, national and international law enforcement agencies,

The last days of 2021 saw PWC publish a report on the attempted extortion of the Health Service Executive (HSE) by the ransomware group Conti. Given that the HSE is the organisation responsible for public health care provision in the Republic of Northern Island and the fact that the attack

Over the past year Elemendar has worked with the US based NC state University Laboratory for Analytic Science (LAS) to examine the prospects of Graph Neural Networks (GNN) for the Cyber Security Industry. Click here to watch our researchers Abdulah Fawaz and Ben Strickson presenting our project findings in their

The cyber threat intelligence landscape is ever-increasing in sophistication as threat intelligence vendors continuously improve their products and user organisations are becoming more mature. To remain at the forefront of this evolution, Elemendar needs to constantly ensure that our CTI processing technology can perform in this changing threat intel landscape. 

At Elemendar we have to keep up to date with as much cyber threat intelligence and machine learning research as we possibly can, so we are constantly reading and exploring. Ben Strickson (our senior data engineer) regards these four papers released this year as especially interesting as their work addresses

As MITRE ATTACK v10 dropped on October 21, we are busy exploring its ramifications for Elemendar and the wider CTI ecosystem. Also, our CTO Syra Marshall has given us her initial thoughts here. 'As a company that focuses on STIX as an output, we're excited to see MITRE create custom objects