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NIST Plans to Build Threat and Mitigation Taxonomy for AI Agents

The U.S. National Institute of Standards and Technology (NIST) is building a taxonomy of attack and mitigations for securing artificial intelligence (AI) agents. Speaking at the AI Summit New York conference, Apostol Vassilev, a research team supervisor for NIST, told attendees that the arm of the U.S. Department of Commerce is working with industry partners..

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Gartner’s AI Browser Ban: Rearranging Deck Chairs on the Titanic

The cybersecurity world loves a simple solution to a complex problem, and Gartner delivered exactly that with its recent advisory: “Block all AI browsers for the foreseeable future.” The esteemed analyst firm warns that agentic browsers—tools like Perplexity’s Comet and OpenAI’s ChatGPT Atlas—pose too much risk for corporate use. While their caution makes sense given..

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Securing MCP: How to Build Trustworthy Agent Integrations

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Model Context Protocol (MCP) is quickly becoming the backbone of how AI agents interact with the outside world. It gives agents a standardized way to discover tools, trigger actions, and pull data. MCP dramatically simplifies integration work. In short, MCP servers act as the adapter that grants access to services, manages credentials and permissions, and..

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Radware Adds Firewall for LLMs to Security Portfolio

Radware has developed a firewall for large language models (LLMs) that ensures governance and security policies are enforced in real time. Provided as an add-on to the company’s Cloud Application Protection Services, Radware LLM Firewall addresses the top 10 risks and mitigations for LLMs and generative artificial intelligence (AI) applications defined by the OWASP GenAI..

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Governing the Unseen Risks of GenAI: Why Bias Mitigation and Human Oversight Matter Most  

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From prompt injection to cascading agent failures, GenAI expands the enterprise attack surface. A governance-first, security-focused approach—rooted in trusted data, guardrails, and ongoing oversight—is now critical for responsible AI adoption.

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When Machines Attack Machines: The New Reality of AI Security

AI

Unlike conventional IT systems—with bounded entry points, predictable patch cycles, and known vulnerabilities—large language models (LLMs) and next-generation AI agents create an attack surface so broad, dynamic, and interconnected that comprehensively mapping or policing it becomes nearly impossible. Every new integration, plugin, RAG pipeline, or deployment scenario multiplies exposure: AI systems undergo constant updates and..

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Commvault Extends AI Ability to Ensure Cyber Resilience

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Commvault today extended the reach and scope of its data protection portfolio as part of an effort to enable IT organizations to achieve and maintain resiliency. Announced at its SHIFT 2025 event, these additions are part of a Commvault Cloud Unity platform that now makes it simpler to backup and recover workloads running in multiple..

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Your Security Team Is About to Get an AI Co-Pilot — Whether You’re Ready or Not: Report

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The days of human analysts manually sorting through endless security alerts are numbered. By 2028, artificial intelligence (AI) agents will handle 80% of that work in most security operations centers worldwide, according to a new IDC report. But while AI promises to revolutionize defense, it’s also supercharging the attackers. IDC predicts that by 2027, 80%..

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Securing the AI-Enabled Enterprise

AI-Driven Security Threats: Moving Beyond the Hype Security does a great job of sensationalizing attacks. This trend was set from a perspective of awareness and edge cases which the industry deals with as attacks and realized perspectives. While this approach leads to discussions around AI-driven cybersecurity threats the risks are hard to comprehend but certain..

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Why API Security Will Drive AppSec in 2026 and Beyond 

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As LLMs, agents and Model Context Protocols (MCPs) reshape software architecture, API sprawl is creating major security blind spots. The 2025 GenAI Application Security Report reveals why continuous API discovery, testing and governance are now critical to protecting AI-driven applications from emerging semantic and prompt-based attacks.

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Survey: Cybersecurity Leaders Much More Concerned About AI Generated Code

A survey of 400 cybersecurity leaders in the U.S. and United Kingdom published today finds all respondents reporting that AI tools are now generating code in their organization’s code base, with just under a third now seeing those tools being used to generate most of the code being created. Commissioned by Cycode, a provider of..

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In an AI World, Every Attack is a Social Engineering Attack    

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AI-driven social engineering is transforming cyberattacks from costly, targeted operations into scalable, automated threats. As generative models enable realistic voice, video, and text impersonation, organizations must abandon stored secrets and move toward cryptographic identity systems to defend against AI-powered deception.

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Securing Agentic AI: Extending Network Security Principles to Serverless Environments

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As enterprise AI rapidly matures, we’re entering a new phase, one powered by agentic AI. These intelligent agents are more autonomous, capable of making decisions, taking actions, and adapting dynamically to new environments. This evolution introduces new complexity in how we build AI systems as well as in how we secure them. Agentic AI doesn’t..

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Veeam Sets Data Graph Course Following Acquisition of Securiti AI

Veeam Software plans to expand the scope of its offerings into the realm of data security posture management (DSPM) following the closing of a $1.725 billion acquisition of Securiti AI. Securiti AI developed a DSPM platform based on a knowledge graph that makes it possible to track the relationships between various data sets and then..

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The Wild West of AI-Driven Fraud

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We are in the middle of an AI gold rush. The technology is advancing, democratizing access to everything from automated content creation to algorithmic decision-making. For businesses, this means opportunity. For fraudsters, it means carte blanche. Deepfakes, synthetic identities and automated scams are no longer fringe tactics. According to Deloitte, GenAI could drive fraud losses..

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The CISO’s Guide to Model Context Protocol (MCP)

As engineering teams race to adopt the Model Context Protocol (MCP) to harness the power of agentic AI, a more cautious conversation dominates security leaders’ mindshare. While the potential for innovation is clear, the primary question for CISOs and CIOs is more fundamental: how are we going to manage the growing risk?  The answer is..

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Check Point Allies with NVIDIA to Secure AI Platforms

Check Point Software Technologies Ltd. today revealed it has developed a cybersecurity platform to secure artificial intelligence (AI) factories in collaboration with NVIDIA. Announced at the NVIDIA GTC conference, the AI Cloud Protect platform enables cybersecurity teams to leverage dynamic objects to enforce policies in real time using NVIDIA BlueField-3 data processing units (DPUs) to..

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When Chatbots Go Rogue: Securing Conversational AI in Cyber Defense 

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As businesses increasingly rely on AI chatbots, securing conversational AI is now mission-critical. Learn about common chatbot vulnerabilities, AI risk management strategies, and best practices — from data encryption and authentication to model protection — to safeguard user trust, privacy, and compliance in the digital era.

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