AI Agent Classification: Helping Security Teams See AI Agents Clearly When we set out to design AI Agent Classification, the first question was not only what the system should identify, but how to help security teams understand a type of traffic they were not used to seeing. Marom Duani Pe’er |July 08, 2026
AI Agents Are Everywhere. Can You Govern and Secure Them All? AI agents are rapidly becoming part of everyday business operations. They automate workflows, assist employees, interact with enterprise systems, and increasingly make decisions and take actions on behalf of users. Dror Zelber |July 07, 2026
APIs in the Age of AI: When "Legitimate" Traffic Becomes the Threat Most API security is built around a simple assumption: the threat looks like an attack. Bad payload, stolen token, known bot, malicious IP. Find it, block it, done. Tzvika Shneider |July 06, 2026
When AI Acts on Its Own: The New Threat Landscape of Agentic AI The arrival of Agentic AI marks a profound shift in how organizations must think about cybersecurity. Unlike traditional LLMs, which generate text and recommendations, Agentic AI systems can act — executing workflows, calling APIs, modifying configurations, analyzing systems, and making autonomous decisions. Dror Zelber |July 01, 2026
Radware & Dataiku: Securing and Governing Enterprise AI at Scale Enterprises are rapidly moving beyond GenAI into a new phase of agentic AI adoption, where autonomous AI agents, analytical pipelines, and generative systems actively participate in decision-making, operations, and customer engagement. Dror Zelber |June 25, 2026
A World Cup Playbook for Cyber Resilience: Defending Your Applications in the AI Era Every four years, the world unites around one of the most electrifying global events—the World Cup. Teams prepare for years, analyzing opponents, anticipating plays and building strategies designed not just to react, but to win. Radware |June 18, 2026
Protect First, Patch Safely: Closing the AI-Driven Exploit Window AI is changing the economics of cyber offense, especially across the vulnerability lifecycle. Security teams have always had to identify, prioritize, and remediate vulnerabilities, but AI tools are changing the speed and scale of discovery, analysis, and weaponization. Dan Schnour |June 17, 2026
AI Agent Visibility and the New Traffic Blind Spot The mix of traffic reaching enterprise applications is changing, and a growing share of it no longer fits the assumptions on which security solutions were built on. Up until a few years ago, bot management solutions operated on a straightforward premise: every incoming request was either from a human user or an automated bot. Dhanesh Ramachandran |June 16, 2026
The Invisible Supply Chain: How AI Agents Create New Third- Party Risk Without Human Awareness AI agents don’t just analyze information - they act. They browse the web, pull documents, call APIs, trigger workflows, and plug into marketplaces of connectors and plugins. Dror Zelber |June 10, 2026
From Prompt Injection to Mission Drift: The Emerging Attack Vectors Targeting AI Agents As organizations adopt Agentic AI at scale, attackers are already adapting their tactics. The shift from passive, text only AI to autonomous, tool enabled agents introduces a wide range of new attack surfaces. Dror Zelber |May 27, 2026
Radware & MaiAgent: Partnering to Secure and Accelerate Agentic AI at Enterprise Scale Across industries, organizations are rapidly embracing Agentic AI — autonomous, goal driven AI agents capable of reasoning, taking actions, and orchestrating complex workflows across enterprise systems. Travis Volk |May 21, 2026
Why AI Guardrails Are Not Enough for Autonomous Agents For the last two years, organizations have relied heavily on LLM guardrails to secure their AI deployments. Prompt filtering, output moderation, jailbreak detection, and policy enforcement - many of them aligned with the OWASP Top 10 for LLM applications - have become standard practice. Dror Zelber |May 20, 2026