Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI adoption is rapidly increasing, and with that comes a steady influx of useful but potentially vulnerable tools and services still maturing in the AI space. The Model Context Protocol (MCP) is one example of new AI tooling, providing a framework for how applications integrate with and supply context to large language models (LLMs). MCP servers are central to developing AI assistants and workflows that are deeply integrated with your environment.

We’ve all heard the myth: goldfish have a memory span of just a few seconds. While that’s debatable in marine biology circles, it’s useful as a metaphor in tech, especially when talking about memory, risk, and AI. The problem is, large language models (LLMs) are not goldfish. In fact, they have incredible memory. And increasingly, that memory isn’t just session-based. It’s persistent, long-term, and system-connected. That changes everything.

Enterprise security teams commonly focus on controlling AI agent conversations through prompt filters and testing edge cases to prevent unauthorized information access. While these measures matter, they miss the bigger picture: the real challenge is granting AI agents necessary permissions while minimizing risk exposure. This isn’t a new problem—it’s the same fundamental challenge we’ve faced with human users for years.

This week marks a milestone in the evolution of mobile endpoint security. At a time when attackers are moving faster and targeting smarter, Lookout is proud to unveil a breakthrough initiative: AI-powered social engineering protection—the first solution of its kind built to detect and disrupt human-targeted attacks at the mobile edge.

Explore enhanced secrets security across code, collaboration tools, & public repos. Discover new Agentic AI protection, NHI lifecycle automation, and smarter incident management.

Global Artificial Intelligence (AI) infrastructure spending is projected to surpass $200 billion by 2028, according to research from the International Data Corporation (IDC). As organizations rapidly deploy more complex AI systems, the demand for high-performance infrastructure, like Graphics Processing Units (GPUs) and AI accelerators, is surging. This growth exponentially increases computing power, energy consumption and data exchange across hybrid and cloud environments.