Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI Workload Security for Financial Services: What CISOs Need to Know

When your SOC alerts on “suspicious AI activity” in a production trading system, your response team faces a question that didn’t exist two years ago: can you explain to regulators exactly which function processed the malicious prompt, which internal tool it called, and how customer data ended up leaving your environment?

Tackling Third-Party Risks: The Persistent Software Supply Chain Challenge

Modern software development relies on open-source components to accelerate innovation. This efficiency, however, introduces significant risk. Your application’s security is now tied to a vast and complex supply chain of code you did not write. The persistent software supply chain challenge is that this external code is a primary source of critical vulnerabilities and a hard.

1Password Unified Access

Today, we’re introducing 1Password Unified Access, a new identity security platform that enables organizations to: Discover AI agents, tools, and exposed credentials Secure access across humans, machines, and agents Audit every action with clear attribution AI agents are quickly moving from experimentation into real production environments, accessing systems, executing workflows, and acting on behalf of employees.

How to Scale Application Traffic Automatically with A10 FlexPool

How to Scale Application Traffic Automatically with A10 FlexPool Priyanka Mullan, Senior Product Marketing Manager at A10 Networks, explains how FlexPool revolutionizes application delivery by dynamically allocating resources based on real-time user demand. Whether you are managing a sudden traffic surge from a major online event or balancing workloads across a hybrid cloud environment, FlexPool ensures your infrastructure scales automatically, without manual intervention. Learn how to maintain peak application performance while significantly reducing operational costs.

How a Fortune 50 Company Deployed Agentic AI at Scale Without Losing Control of Their Data

In late 2025, a Fortune 50 enterprise decided to deploy autonomous AI agents across core business operations. Customer support that could reason through complex issues. Supply chain systems that could adapt in real time. Product managers with AI assistants pulling insights from dozens of data sources simultaneously. The capabilities that made the agents useful also introduced a problem nobody had a clean answer for. These weren’t chatbots locked inside a single application.

Why Synthetic Data for AI Fails in Production

Synthetic data has been fine for testing software for decades. Traditional apps follow rules. You check inputs, check outputs, file a bug when something breaks. AI is different. AI gets deployed into the situations where the rules aren’t clear and context is everything. The edge cases aren’t exceptions. They’re the whole point. That changes what your test data needs to look like.

Are AI Security Tools the New EDR? Attackers Are Treating Them That Way

AI security tools are no longer just defensive layers. They are high value targets being studied, fingerprinted, and bypassed much like traditional endpoint detection and response (EDR) platforms and antivirus solutions were in their early days. The speed and scale at which these tools are being deployed makes reactive defense increasingly unsustainable.

From Phishing to AI Agents: Can We Design for Digital Mindfulness?

Anyone who knows me knows I’m passionate about mindfulness. Because I genuinely believe it makes us better humans. But also, because I have one of those brains that desperately needs it. I’m easily distracted and I start new ideas before finishing old ones. My attention can scatter in a hundred directions. I wrote before how I clicked on a phishing test because I was multitasking and running on autopilot. And that moment really changed the direction of my career and my research.