Blogs & Articles

The HP OmniBook Ultra 16 is a beast of a machine. For “pro-formance” users, it represents the apex of portable power today, easily replacing a desktop-bound workstation. It is compact, thin and light, and more importantly, discrete. Laptops like this are at the top end of the premium price bracket, but for good reason. This is a niche market, but one that could grow as the price to performance ratio of AI inferencing reduces, and component costs return to a level that brings

Jev is a “System 1” AI model that can function as a first-layer decision model for fast, high-volume security triage, reducing the number of expensive LLM investigations. At a time of increasing token usage and metered cost, the promise of quick, low-cost triage is very compelling.

The cybersecurity industry has come a long way since threat hunting was considered a new and much more advanced form of threat detection and response. Like any evolution, there have been distinct stages of development - as well as instances where generational “leaps” have potentially been made. The emerging use of agentic AI in automating hunting tasks has the potential to considerably change the game - for defenders as well as attackers.

Management of non-human identities has evolved in response to the rapid adoption of semi-autonomous AI agents. The complex nature of their interactions with both human operators and other agents means that security teams need a more sophisticated approach that uses behavioural context to determine an agent’s permissions. Firms are leveraging an identity management approach mirroring the complexities of human operator requirements, but at a vastly bigger scale.

Autonomous AI agents can bring significant operational efficiencies, but magnify the risk of vulnerabilities if they are given access permissions that are closer to a human identity

By Carolyn Reuss Recently I’ve been talking to a lot of startups and small companies, and the cybersecurity awareness ranges from good...