Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Invitation Is All You Need: Invoking Gemini for Workspace Agents with a Simple Google Calendar Invite

Over the last two years, various systems and applications have been integrated with generative artificial intelligence (gen AI) capabilities, turning regular applications into gen-AI powered applications. In addition, retrieval augmented generation (RAG)-which is the process of connecting gen-AI and large language models (LLMs) to external knowledge sources-and other agents have been incorporated into such systems, making them more effective, accurate, and updated.

CrowdStrike Signal: Detect the Undetectable

Modern adversaries hide in plain sight by blending malicious activity with normal system behavior, making it difficult for traditional detection tools to identify threats early. CrowdStrike Signal uses self-learning AI to turn scattered signals into high-confidence Automated Leads that help analysts stop breaches before they escalate.

Designing the Future of Agentic AI: Cato Engineering Details a New Practical, Secure, and Scalable MCP Server Framework

Some of you may remember the early days of security, when setting up a firewall or antivirus felt like enough. It was simple and gave us a sense of control. But over time, we learned that security is a moving target. What once felt sufficient quickly became just the starting point. In today’s agentic AI era, many treat their Model Context Protocol (MCP) setups the same way. If it’s running and returning results, it feels good enough. But the AI landscape is evolving rapidly.

From Ideas to Impact: How the Bay Area Is Shaping the Future of Secure AI

Generative AI is reshaping how software is made, secured, and scaled. At Snyk’s Lighthouse event in Silicon Valley, leaders from engineering, security, and platform teams gathered to explore one big question: How do we build AI-powered systems that move fast, without breaking trust? For many, that future is already here — 60% of organizations at the Summit reported building agentic apps internally. The answers weren’t just technical. They were cultural. Organizational. Strategic.

CrowdStrike Launches New AI Security Services to Strengthen AI Security and SOC Readiness

AI is transforming business processes and the threat landscape. CrowdStrike is expanding our AI Security Services portfolio to help organizations meet the dual challenges of securing their AI systems and effectively integrating AI into security operations.

AI Is Not the Destination-It's the Catalyst: Inside Bitsight's Vision for Third-Party Risk Management

A new era in third-party cyber risk and exposure management is underway, one that operates in real time, informed by intelligence and scaled by automation. This shift wasn’t feasible even a few years ago. The scale, speed, and complexity of today’s threat landscape—spanning thousands of vendors, assets, and attack vectors—demand more than human capacity can manage. Artificial Intelligence is the catalyst making this new model possible.

From Clipboard to Cloud: Upgrading Dental Reception Security with AI

Dental reception areas have come a long way. Not too long ago, check-ins involved clipboards, paper forms, and the occasional misplaced file. It was all a bit clunky. While it got the job done, it wasn't exactly secure, and it definitely wasn't efficient. Now, clinics are realising that the front desk is more than just a place to schedule appointments. It's also where patient data starts its journey, which means it has to be secure from the very beginning. That's where artificial intelligence comes in, offering smarter, safer ways to handle sensitive information.

Introducing Netskope One Copilot for Private Access

Any organization that’s undergone a security transformation knows the promise of zero trust network access (ZTNA): secure, least-privilege access to private applications, anywhere, on any device. But turning that promise into operational reality is often far from simple. Between fragmented tools, complex configurations, and sprawling environments, implementing ZTNA can quickly become a manual, time-consuming, and error-prone process.