Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Unlock AI with GPU as a Service in VCF 9

Many IT professionals struggle to integrate artificial intelligence (AI) into their existing environments. You often find expensive hardware trapped in isolated clusters or dedicated hosts. Your infrastructure team manages access through manual ticket queues, which leads to low utilization and frustrating bottlenecks for developers. When you don’t have a standardized way to share and monitor accelerator resources, every hardware change risks downtime for your critical applications.

APIs Are Critical Infrastructure. Why Aren't We Treating Them That Way?

‍In this session, we take an in-depth look at what it truly means to treat APIs as critical infrastructure. Using industry data and real-world examples, we explore the gap between how much businesses rely on APIs and how well they are actually protected. And we talk about why that gap introduces operational and regulatory risks.

Secure Enterprise AI Apps and Agents: Visibility, Governance, Runtime Protection

When you deploy an AI application, do you know what's being sent into it — or what's coming back out? Cato AI Security provides runtime protection for the AI applications your organization builds and deploys, with real-time enforcement, sensitive data anonymization, and a complete audit trail across every interaction. Learn more or request a demo at catonetworks.com.

Rethinking Application Delivery for the AI Era

Rethinking Application Delivery for the AI Era Is your network strategy keeping up with the AI era? Jamison Utter, Field CISO at A10 Networks, challenges IT leaders to move beyond "piecemeal" infrastructure and rethink their approach to application delivery. As organizations face the dual pressure of integrating AI workloads and managing a vast "fleet" of hybrid devices, the old ways of operating are becoming a liability. Jamison discusses the true cost of administrative overhead and the urgent need for a more flexible, simple, and future-proof vendor strategy.

From Intent to Outcome: How Agentic Coding is Transforming the SOC

See how Torq harnesses AI in your SOC to detect, prioritize, and respond to threats faster. Request a Demo Security teams are being asked to move faster and handle more complexity, while the threats they defend against are increasingly AI-assisted. When I wrote about VoidLink in January, my point was simple: you cannot fight machine-speed threats with human-speed defense. Attackers are using AI to code, adapt, and scale attacks while humans are still grinding away doing the heavy lifting in the SOC.

The Unsung AI Hero: Data Normalization

AI agents are only as effective as the data they consume. In this post, we explore the unsung hero of the security stack: data normalization. This process serves as the deterministic guardrail that makes AI grounding possible. Without a structured data foundation, grounding is only as good as the often chaotic data being retrieved, leading to confident but incorrect AI responses.

From Agentic Risk to Agentic Confidence: The JFrog MCP Registry is GA

In an AI-native world where Model Context Protocol (MCP) is the universal standard for AI connectivity, the security and governance stakes have never been higher. AI’s ability to take autonomous action through MCPs means that a single breach of an MCP server can grant attackers control over mission-critical enterprise systems, putting enterprises in an immediate and escalating state of agentic risk that cannot be ignored.

Introducing Agent Privilege Guard: Runtime Privilege Controls for the Agentic Era

The question enterprises are asking is no longer whether to deploy AI agents. It is how to do it without creating security risk they cannot control. In December 2025, Amazon’s own AI coding tool Kiro triggered a 13-hour AWS outage after autonomously deciding to delete and recreate a production environment.