Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Testing MiniMax M2.1 for AI Coding: The Results Might Surprise You

Can "lesser-known" AI models actually keep up with the giants like Google, OpenAI, and Anthropic? In today’s video, we put MiniMax M2.1 to the ultimate test: building a production-ready, secure Node.js note-taking application from a single prompt. We’ll explore how to access MiniMax natively in the Windsurf IDE, walk through the debugging process for common errors (like environment variables and OS-specific dependencies), and perform a deep-dive security audit using Snyk. Stick around until the end to learn how to integrate MiniMax M2.1 into VS Code using OpenRouter.

Top 3 Skills for AI Security in 2026 #shorts

Are your cybersecurity skills ready for the AI era? In this clip, we reveal which traditional security frameworks still work and the one new mental shift you need to survive. It’s not just about code anymore—it’s about "Socio-Technical" thinking. Raji (Microsoft AI Security) breaks down exactly how to future-proof your career.

Why Vulnerability Management Falls Short - And How Exposure Management Fixes It

Vulnerability management identifies weaknesses. Exposure management helps prioritize them based on real-world risk and context. Ed and Garrett unpack why traditional vulnerability programs struggle to drive real risk reduction. The challenge isn’t discovery. It’s prioritization and follow-through. Too often, vulnerabilities are treated as isolated IT tasks—handed off, tracked by SLAs, and stripped of the context that explains why they matter in the first place.

The Asymmetric Threat: Why AI API Traffic is Hard to Predict

The Asymmetric Threat: Why AI API Traffic is Hard to Predict As AI becomes more integrated into business operations, the way data moves through APIs is changing. In this clip from the A10 Networks webinar, "APIs are the Language of AI: Protecting Them is Critical," experts Jamison Utter and Carlo Alpuerto break down the concept of data asymmetry in AI.

How CEOs are turning AI investment into a competitive advantage

Artificial intelligence has moved quickly from experimentation to expectation. In many organisations, the question is no longer whether to invest, but how to turn investment into advantage that is durable, measurable, and defensible. The early wave of AI activity produced a familiar pattern: plenty of pilots, proofs of concept, and internal demos, but fewer examples of sustained value at scale. In 2025, that gap is narrowing. More leadership teams are treating AI as a core capability rather than a side project, and they are building the structures needed to capture value repeatedly, not just once.

10 AI Trends Reshaping Digital Marketing Strategies

Modern marketing is basically a result of technology, innovation, and human insight coming together. The brands that are the leaders in their industries are the ones that use the new tools extensively and, at the same time, build real relationships with their audiences. Artificial intelligence is the use that has become the main factor of this change very soon.

AI vs. Legacy Systems: Why Your Old Documentation Isn't Safe

AI vs. Legacy Systems: Why Your Old Documentation Isn’t Safe In this A10 Networks discussion, "APIs are the Language of AI: Protecting Them is Critical," security experts Jamison Utter and Carlo Alpuerto tackle one of the most overlooked threats in modern IT: the "specter in the shadow." For years, many organizations relied on "security through obscurity"—the idea that if a system is old or undocumented, it's safe from attackers. However, AI has changed the rules. These systems can now decipher legacy documentation and communicate with obscure systems faster than a human ever could.

The Architecture of Agentic Defense: Inside the Falcon Platform

The architectural divide in cybersecurity is no longer theoretical. It's operational. Adversaries are deploying AI-accelerated attacks and moving laterally across domains faster than human analysts can correlate evidence. Meanwhile, defenders are adopting AI tools that accelerate individual tasks but still operate on fragmented data and require manual correlation across disconnected systems.

What's shaping the AI agent security market in 2026

For the past two years, AI agents have dominated boardroom conversations, product roadmaps, and investor decks. Companies made bold promises, tested early prototypes, and poured resources into innovation, with analysts projecting an economic impact of $2.6 trillion to $4.4 trillion. As 2026 begins, the experimentation phase ends and the production era starts as organizations roll out AI agents at scale across their enterprises.