Best Practices for managing Kubernetes environment in Web-DDoS attacked environments – Part1 In today’s cloud‑native era, distinguishing between genuine user growth and malicious Web DDoS surges is critical. When Auto-Scaling Lies: Diagnosing False Demand in Kubernetes During Web DDoS would be a disaster. Nithin Rudraswamy |March 04, 2026
Runtime Security in an AI-Accelerated World The release of Claude Code Security triggered headlines about disruption across the cybersecurity market. Analysts questioned whether traditional security categories were at risk, and public markets reacted quickly. Gabi Malka |February 25, 2026
How Effective Is Radware’s AI Agent Protection Against Indirect Prompt Injection? As autonomous AI agents rapidly enter business workflows, security teams face a new and often overlooked threat: indirect prompt injection (IPI). Dror Zelber |February 18, 2026
Why AI Crawler Management Matters: Balancing Visibility and Control In my previous blog, we explored what AI crawlers are, how it differs from traditional search engine crawlers, the different types of AI crawlers, and the impact on businesses. Dhanesh Ramachandran |February 17, 2026
Bringing Cloud-Grade Web DDoS Protection to On-Prem Applications Imagine this: it’s a perfectly normal Thursday morning. The coffee is hot, dashboards are green, and your application is quietly doing its job. No alerts. No calls. No one blaming the network. Everything is perfect and you even start planning your weekend. Dalit Bar |February 04, 2026
When Good AI Agents Go Bad: A Cautionary Tale for Modern Organizations In 2025, retail chain BrightMart was riding a wave of optimism. Like many organizations across industries—law firms, insurance companies, logistics providers and customer-facing service companies—it had begun deploying AI agents to accelerate employee productivity, automate repetitive tasks, streamline customer interactions and push overall efficiency to new levels. Dror Zelber |February 03, 2026
Radware’s New API Security Service: Unified, End-to-End Protection Built for Real-World APIs APIs are at the core of modern digital experiences, and they’re expanding faster than traditional security approaches can keep up. To address this challenge, Radware’s new API Security Service delivers a unified, end-to-end solution that protects APIs across their entire lifecycle, from discovery and posture management to real-time runtime protection. Uri Dorot |January 19, 2026
When Help Turns Harmful: How Attacking a Healthcare LLM Prompt Can Put Patients at Risk Healthcare institutions around the world are adopting AI-driven virtual assistants to improve patient services. Instead of waiting on hold, patients can ask a Large Language Model (LLM) for help with booking appointments, checking lab results, understanding treatment options, managing chronic conditions, or even getting reminders about medication or follow-ups. Dror Zelber |January 14, 2026
Unlimited Resources, Unlimited Damage: The Real Cost of Ignoring Unrestricted Resource Consumption vulnerability Imagine your application is an all-you-can-eat restaurant… Most customers take a reasonable amount of food, but one person decides to empty every single tray. David Netanel Mashiah |January 09, 2026
Radware AI SOC Xpert: Elevating Security Operations — A Deep Dive into Its Bot Defense Capabilities In the rapidly evolving world of cybersecurity, automation and data intelligence have become indispensable for defending digital infrastructure. Modern Security Operations Centres (SOCs) process massive volumes of data — including alerts, logs, network telemetry, and user behaviour. Managing and interpreting this information manually is time-consuming and prone to human error. Netravati Hegadi |January 07, 2026
Fighting AI-Driven Bots Across the Full Attack Lifecycle The bot threat landscape has fundamentally changed, with a new reality that is far more sophisticated than the simple, scripted bots of the past: AI-enhanced bots. Dhanesh Ramachandran |December 23, 2025
From Cutting-Edge to Critical Risk: Unpacking the Cybersecurity Dangers of LLM Integration - Part 2: Defending at the Inline Edge In Part 1, we explored how integrating large language models (LLMs) into business applications creates new and often misunderstood security exposures - from prompt injection and data leakage to brand impersonation and compliance risks. Rotem Elharar |December 16, 2025