Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Securing the agentic future: Where MCP fits and where it doesn't

AI agents are rapidly transforming how software is accessed, operated, and integrated, such as automating workflows, calling APIs, and interacting with tools and SaaS platforms on behalf of users. This paradigm unlocks powerful new capabilities, but it also raises urgent questions about how sensitive data, especially credentials and secrets, should be managed.

When AI Agents Go Rogue: What You're Missing in Your MCP Security

We’re at a major inflection point in how software operates. And I don’t say that lightly. For the past decade, we’ve seen a steady evolution toward microservices, APIs, and cloud-native architectures. But Agentic AI is something different. We’re no longer talking about static services. We’re now dealing with autonomous agents that reason, remember, and act in real-time across live environments.

From unknowns to known risks: Mapping your app's privacy surface

Mobile apps are everywhere. From the moment we wake up and check the weather to staying connected with friends and family, our lives are woven together by apps. They manage our money, track our workouts, store our memories, and even help us find love. But with this convenience comes a hidden cost: our privacy. Every tap, every swipe, every “allow” permission is a potential gateway for data to flow, sometimes to places we never intended.

Understanding AI compliance and its importance for organizations

As AI capabilities grow, organizations are adopting it for compliance monitoring, risk analysis, and data processing. However, increased use also introduces new risks, making strict regulation essential, especially in sectors where sensitive data is involved—like finance, insurance, and healthcare. Mishandling this information can lead to reputational damage, legal action, or hefty fines.

Best AI Red Teaming Tools: Top 7 Solutions in 2025

There was a time when “AI red teaming” sounded like a novelty. Now, it’s fast becoming table stakes. If your organization is shipping machine learning or LLM-powered systems into the real world (especially in sensitive domains), you need to know how those systems behave under pressure. That’s where AI red teaming tools come in. These tools help teams stress-test AI the way it will actually be used (and misused).

GitGuardian Launches MCP Server to Bring Secrets Security into Developer Workflows

GitGuardian, the leader in automated secrets detection and remediation, today announced the launch of its Model Context Protocol (MCP) Server, a powerful new infrastructure designed to bring AI-assisted secrets security directly into developer environments. As intelligent agents begin to reshape the software development landscape, GitGuardian's MCP server marks a pivotal shift in aligning security practices with an environment where code is shipped faster than ever.

Developing Security Leaders

Most security leaders don't suddenly become "strategic" the moment they get a new title. It's a skill developed through failures, feedback, and learning how to align your work with the business's goals. On this episode of The Connectivity Cloud Podcast, Olivier Busolini opens up about his own missteps, trying to contribute from inside the tech silo, then outside of it, and still feeling ineffective?