Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Defending at Machine Speed in the Autonomous Age

Frontier AI models are accelerating the discovery of new vulnerabilities combined with the ability to exploit those weaknesses at speed and scale. This alone isn’t the problem. Trust in AI‑driven security outcomes is. With AI dominating headlines, security leaders are asking what models like Mythos or GPT‑5.4‑Cyber mean for their business. The real issue runs deeper. Teams need to be able to trust tools and technology that move at machine speed.

Building a Governed AI Model Supply Chain: Integrating AWS SageMaker and the JFrog Platform

Amazon SageMaker accelerates the process of training and deploying machine learning models. However, as AI adoption scales from individual experiments to enterprise-wide production, the focus of leading Fortune 500 software development operations and security teams must shift from pure velocity to governance.

Phishing Campaigns Abuse AI Workflow Automation Platforms

Threat actors are abusing agentic AI automation platforms to deliver malware and send phishing emails, according to researchers at Cisco Talos. The researchers observed attackers using n8n, a legitimate platform that automates workflows in web apps and services like Slack, GitHub, Google Sheets, and others.

Millions of AI agents are running without oversight. Is yours one of them?

Accelerating security solutions for small businesses‍ Tagore offers strategic services to small businesses. A partnership that can scale‍ Tagore prioritized finding a managed compliance partner with an established product, dedicated support team, and rapid release rate. Standing out from competitors‍ Tagore's partnership with Vanta enhances its strategic focus and deepens client value, creating differentiation in a competitive market.

Acronis GenAI Protection is now live: Secure the AI era

Generative AI is no longer emerging. It is already embedded in how businesses work. From content creation and research to customer support and internal productivity, AI tools are rapidly becoming part of everyday workflows across SMBs and the MSPs that serve them. But this shift comes with a hard reality: As GenAI adoption accelerates, so do the risks.

Implementing AI Agent Security on Azure AKS: A Practical Guide

Your platform team deployed eBPF-based runtime sensors on AKS last week. Defender for Containers is enabled. Azure Policy is enforcing pod security standards across your AI workload namespaces. And your Observe pillar is still blind — because nobody enabled the Diagnostic Setting that routes kube-audit logs to the Log Analytics workspace where your tooling can actually consume them.

What Is AI Agent Security? Threats, Risks, and What Actually Stops Them (2026)

Over two-thirds of enterprises are already running agentic AI in production, according to a 2025 industry survey on the state of agentic AI security. Fewer than one in four have the visibility to know what those agents are actually doing. That gap is live right now, in systems handling customer data, financial records, and protected health information.

AI Workload Discovery: How to Find Every AI Agent Running in Your Clusters

A CISO at a mid-sized SaaS company pulls her platform lead aside after a board meeting. One question: “Do we have AI agents running in production?” The lead pauses. He knows the data science team has been experimenting with LangChain. He remembers a conversation about a customer-support pilot. He thinks there might be an inference server in staging that got promoted last quarter.

AI Workload Security for Healthcare: What CISOs Need to Prove Under HIPAA

A patient calls your privacy office and requests an accounting of every disclosure of her PHI made outside treatment, payment, and healthcare operations over the past six years. This is her right under HIPAA. Your privacy officer pulls the EHR disclosure log. It is complete through the day your organization deployed its first production AI agent.