Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Why AI Projects Stall and How CIOs Can Respond

Across enterprises, a familiar pattern is emerging. A business unit identifies an AI tool with a clear upside in productivity or revenue. Their proposal moves into procurement. Security raises concerns, and the legal team asks new questions about the tool. Compliance starts hesitating and the momentum slows. Finally, the project stalls. This friction is not due to resistance to innovation. It reflects a deeper structural issue: Most enterprise governance models were not designed for AI.

Agentic AI Visibility and Risk Scoring: What Cyberhaven Sees That Others Miss | (Part 3 of 4)

Knowing an AI tool exists is not the same as knowing what it did with your data. This is Part 3 of Cyberhaven's 4-part AI Security product launch series, covering Agentic AI Visibility and AI Risk IQ, Cyberhaven's evidence-based risk scoring system for every AI app and agent in your environment.

Real-Time AI Enforcement Powered by Data Lineage | Cyberhaven (Part 4 of 4)

Visibility without enforcement is just an alert backlog. This is Part 4 of Cyberhaven's four-part AI Security product launch series, covering how Cyberhaven enforces risk-based controls at the data level, not the tool level, using Data Lineage as the foundation.

Shadow AI Discovery: How to Find Every AI Agent in Your Environment | Cyberhaven (Part 2 of 4)

Security teams cannot govern what they cannot see. This is Part 2 of Cyberhaven's four-part AI Security product launch series, focused on Shadow AI Discovery and how Cyberhaven automatically inventories every AI app and agent running across your organization.

AI Security for Autonomous Agents | Cyberhaven Product Launch (Part 1 of 4)

Autonomous AI agents are running on enterprise endpoints right now, accessing files, processing sensitive data, and executing actions outside the visibility of most security programs. This is Part 1 of Cyberhaven's four-part AI Security product launch series. What this video covers: Most AI security tools were built for browsers and SaaS apps. They cannot see agents operating at the OS level, coding assistants running in IDEs and CLIs, or MCP servers executing in the background. Cyberhaven's AI Security platform was built to close that gap.

Do You Know How Many MCP Servers Are Running in Your Environment Right Now?

Most organizations have no idea how many MCP servers are running in their environment—and attackers are counting on that. In this clip, Adrian Culley breaks down the exact steps security teams need to take now: run the network scan, apply stringent code review to every MCP server project you find, and mandate authentication. Authorization may be optional in the MCP spec—but it doesn't have to be optional in your deployment.

AI-assisted SOC training with Carlo Anez

Join us for this week's Defender Fridays as Carlo Anez, Founder & Lead Instructor at IgniteCyber Academy and DEFCON Training Instructor, breaks down how to build practical blue team skills using open-source labs, MITRE ATTACK, and real-world defender workflows, and where AI fits into the picture without replacing the analyst.

Claude's Agents Are Already Running Across Your Enterprise. Now Security Teams Can Catch Up.

We are excited to share that Zenity now integrates with Claude's Compliance API to bring Claude activity into the same AI security and governance platform enterprises already use to govern agents across the business. By combining Claude's Compliance API telemetry with Zenity's native agent security capabilities, security teams gain the visibility, posture controls, and real-time enforcement needed to secure Claude across the full agent lifecycle.

Nightfall's integration with Claude's Compliance API is now live

What this milestone means for enterprise AI security - and why we built it. AI adoption inside the enterprise didn't slow down and wait for security to catch up. It accelerated. And nowhere is that more visible than in the rapid deployment of large language models like Claude across enterprise workflows. Customer support teams use it to summarize tickets. Legal teams use it to review contracts. Engineers use it to write and review code. Finance teams use it to draft reports.

Cloud Security Monitoring: A Complete Guide for 2026

Your cloud footprint probably grew faster than your monitoring program did. That's the normal path. A team starts with one cloud account, one logging service, and a few dashboards. Then come managed databases, containers, serverless functions, SaaS integrations, new identities, and temporary workloads that appear and disappear before anyone documents them. Security ends up with a pile of logs, a backlog of alerts, and a nagging suspicion that the dangerous activity isn't the stuff already visible.