Over the last year, Model Context Protocol (MCP) servers have transitioned from "cool developer experiments" into critical production infrastructure. Developers love them because they allow AI agents to open tickets, query databases, and update records with almost zero integration backlog. But there is a fundamental truth we must acknowledge before moving forward: The AI revolution is actually an API revolution.

Cyberbullying can happen to anyone at any time, and is especially prevalent among young people (affecting around 1 in 5 young people in the UK). Many young people deal with cyberbullying in silence. They may feel ashamed, fear they’ll lose device privileges, or worry that intervention from loved ones might make things worse. That’s why trying to spot the signs early is so important.

2026, the perfect time to reflect on how far technology has come and what lies ahead. Without a doubt, Artificial intelligence has gone from a niche to an omnipresent force, reshaping how we work, build, and defend. While organisations have speed-ran the adoption of AI and machine learning, cybercriminals have been just as fast to exploit them, and AI now powers business decisions, customer interactions, and – predictably – cyberattacks.

MITRE ATLAS has become a critical resource for cybersecurity leaders navigating the rapidly evolving world of AI-enabled systems.Traditional threat models are built for human-initiated workflows, APIs, and infrastructure, so they are no longer sufficient to describe modern AI attacks..

MITRE ATLAS (Adversarial Threat Landscape for Artificial-Intelligence Systems) is a globally recognized AI security framework that catalogs adversarial techniques targeting artificial intelligence systems. Similar in structure to MITRE ATT&CK but purpose-built for AI, machine learning, and agentic systems, ATLAS translates abstract AI risks into concrete, actionable attack techniques that security teams can monitor and mitigate.

Lack of data has rarely been a challenge that cybersecurity leaders in the enterprise setting have faced. In fact, cyber risk data is usually in abundance. The obstacle, thus, is instead twofold. Teams must first make sense of all of that information, and leadership must then be able to communicate what it means in a language that supports high-level decision-making. That gap between information and deeper understanding is where many cyber risk programs flounder.