Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

CrowdStrike Accelerates Real-Time Data Classification with On-Device AI

Modern data security depends on understanding sensitive data as it is created, accessed, and moved in real time directly on the endpoint. In addition to identifying predefined patterns such as credit card numbers or Social Security numbers, organizations must protect unstructured information including documents, chat logs, support tickets, AI prompts, medical records, and free-text fields.

When One AI Model Fails Many Companies at Once

Cyber insurance works because losses across a book are mostly independent. One insured suffering ransomware tells you little about the next, so a portfolio of many policies is more predictable than any single one. ‍ Shared AI dependencies break that assumption in a specific way. Where a large share of a book depends on the same foundation model or the same inference infrastructure, a single failure produces simultaneous claims across insureds with no commercial relationship to each other.

From Triage to Full Coverage: The Shift AI Agent Security Took in August

Security teams evaluating an AI agent security platform tend to ask the same question after the first demo: will this keep up? Agentic AI changes shape every few weeks, with new frameworks, new coding agents, and new ways for an agent to reach a tool or a credential. A platform that covers today's stack and stalls on next quarter's isn't much of a bet.

Run LimaCharlie AI Sessions on the model you choose

Co-founder and COO AI Sessions in the LimaCharlie web application now run on OpenAI, Google Gemini, and OpenRouter models in addition to Claude. Connect your own credentials, pick a provider per session profile, and the session behaves the same way regardless of which model is doing the work. Sessions run on Claude by default. Beyond that, you can connect any of the following with your own credentials.

Sumo Logic MCP server: bringing SIEM and log data into Claude and other AI clients

More security and operations work now happens inside an AI client instead of a dedicated console. That shift creates a gap for any platform that isn’t part of the conversation. Every time an analyst needs to triage an insight or check a log, they have to leave the AI client and go open a different tool. Sumo Logic closes that gap with a Model Context Protocol (MCP) server.

The Linux AI blind spot: 7 exfiltration points your DLP can't see

Shadow AI now contributes to one in five data breaches, and Linux endpoints, where most developers work, largely lack DLP enforcement. That means engineers can upload code to AI tools, copy files to USB or Bluetooth devices, sync data to personal cloud storage, and move files through network shares undetected. HIPAA, PCI DSS, GDPR, and CMMC hold organizations accountable regardless of this coverage gap. Netwrix Endpoint Protector extends content-aware inspection and device control to Linux.

Agent Sprawl is the New Shadow IT

As you’re reading this, it’s possible an agent you’ve never heard of is reading your files. But where did it come from? What systems can it access? And who’s responsible for its oversight? Today, employees are using AI and agents to expand what they can accomplish and how work gets done. And the barriers to innovation have never been lower — with natural language and no-code tools, anyone in your organization can build a new agent in the span of an afternoon.

19 Best AI Visibility Tools with MCP Servers in 2026 (Ranked)

AI visibility work now happens in the same conversations where strategy already lives. Analysts draft in Claude, engineers debug in Cursor, and content leads paste ChatGPT screenshots into Slack threads that never become a ticket. Model Context Protocol (MCP) is what turns those screenshots into objects a model can query, filter, and act on. An MCP server exposes visibility scores, citation lists, advertiser intelligence, and even brief generation as tools the model can call mid-sentence, against live data, without a CSV hop. That timing matters because answer engines rewrite outputs daily.

What Marketing Trends Should Businesses Pay Attention to in 2027?

Marketing trends have a habit of arriving with dramatic predictions. Email is dead. Search is dead. Websites are dead. Social media has changed forever. Artificial intelligence will replace every marketing department by Tuesday afternoon. Reality is usually less theatrical. Most major marketing channels do not disappear overnight. Instead, the way people use them changes. Search evolves. Social platforms develop new roles. Video becomes easier to produce. New technology changes expectations. Customers become more selective about what earns their attention.