Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Cybersecurity Awareness Training for AI: Key Focus Areas

As employees increasingly rely on AI tools and AI agents in daily workflows, organizations are facing a new workforce security challenge: how to reduce risk without slowing productivity. Security leaders are no longer just protecting systems and identities. They also need to manage how employees interact with AI-generated content, automation, and decision support tools.

How to Use AI for Vulnerability Management

With over 48,000 CVEs published in 2025 and attackers weaponizing vulnerabilities in as little as 20 hours, traditional vulnerability management is no longer enough. This post breaks down the key findings from the SANS whitepaper The Exposure Gap: From Vulnerability Management to AI-Driven Control, and what it means for security teams trying to get ahead of risk. In 2025, over 48,000 CVEs were published. That’s roughly 130 new vulnerabilities every single day.

How to Setup AI Rules, Skills, Hooks and MCPs

In this video, we break down how to properly set up and use AI extension points - specifically MCP (Model Context Protocol) servers, Rules, Skills, and Hooks - to supercharge your development workflow. Using practical, security-flavored examples with Claude Code and Snyk, you'll learn how to configure a local project environment that automatically catches vulnerabilities before they ever hit your codebase. Whether you use the Claude CLI, VS Code extensions, or alternate AI ecosystems like Cursor or Gemini, you can use these exact steps as a blueprint to automate any workflow in your project.

5 Agentic AI Security Use Cases Every Security Leader Must Know in 2026

A human employee who wants to delete a customer record, issue a refund, or push a config change has to ask, click, and confirm. An AI agent doing the same thing can plan, decide, and execute the action in one pass, often through a tool it picked itself, in a sequence no one explicitly approved. That shift, from systems that respond to systems that act, is why most application security stacks fall short the moment agentic AI enters the picture.

AI changed what you ship. It also changed what you have to secure.

Two years ago, your teams shipped software. Today they ship two different things. They ship software that AI mostly wrote. And they ship AI systems they built themselves: models, agents, features that reason and act. Most security programs are still scoped for the first and blind to the second. That gap is not a tooling problem. It is a category problem. And the way the industry is drawing the categories is making it worse.

Decoding the Copilot Ecosystem

Microsoft’s approach of generative artificial intelligence has fundamentally redefined corporate productivity. The "Copilot" brand has become synonymous with workplace efficiency, promising to accelerate everything from writing software to summarizing executive board meetings. For a security analyst, however, this widespread integration introduces significant challenges to the attack surface they manage.

The 2026 Enterprise AI Security Index

The writing is on the wall: artificial intelligence has moved past the experimental phase and has cemented its place as a core component of the modern enterprise stack. For CISOs, the playbook of flat firewall blocking is ineffective—bans don’t halt adoption, they simply drive usage underground into unmanaged shadow streams. To protect corporate assets without stalling business velocity, security leaders are seeing the need to shift from blind obstruction to active, structured guidance.

The Architecture of an AI-Powered Breach: The Shadow Supply Chain

CISOs and security analysts understand that the narrative surrounding artificial intelligence risk has changed. The old assumption that AI risk begins and ends with an employee copying and pasting a sensitive paragraph into a public ChatGPT prompt has dissipated, and we now see that AI has rapidly transitioned from an occasional consumer novelty into a deeply embedded, departmental infrastructure.

How to layer fraud checks on top of Anthropic's KYC Screener agent

Anthropic released a pre-built KYC Screener agent last month. It runs a four-step workflow on onboarding records to extract structured data from KYC documents, evaluate that data against a firm's KYC rules, screen named parties, and escalate exceptions to a compliance file for human review. The Anthropic template is purpose-built for meeting basic KYC compliance requirements during onboarding, and it lowers the cost of getting it right.