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AI data security: protecting sensitive information across AI tools

An employee uploads a spreadsheet to find a sales trend. Another pastes a support conversation into a chatbot to draft a reply. Neither intends to expose business information. Even so, both may send sensitive material outside the systems where your business normally controls it. SMB IT decision-makers need to know what employees share and decide which interactions are acceptable, without building a specialist AI security team.

Modern Data Security Should Be Anchored To Your Data's Lineage

New AI tools appear every day. The novelty and utility they bring, along with the constant pressure to be more productive, pull employees toward them to get work done faster. The intent is good but the effect can range from problematic to damaging, because while there are rules in place for sanctioned tools, there are none for the ones that quietly show up in between.

Protect Sensitive Data in LibreChat with Protecto | PII Masking Demo

Most DLP tools can mask a PII value on the way into a model. Almost none of them can make that value usable again when the AI needs to call a tool with it, so the masking breaks the workflow instead of protecting it. This is Protecto Privacy Gateway for AI Chat, live in a self-hosted LibreChat deployment. Watch what happens when a masked account number needs to resolve at a tool boundary — and comes back correct.

Why Network Privacy is Becoming a Critical Layer of Modern Cybersecurity

In 2026, network privacy has become a critical layer of modern cybersecurity. With cyber threats becoming increasingly advanced and businesses embracing hybrid work, cloud platforms, and interconnected systems, network security can protect data moving across networks and reduce exposure to cybercrime. This article will explore why network security is so important in 2026, the risks associated with unsecured connections, and how businesses can strengthen their posture. Read on to find out more.

Where Does Session Replay Cross the Line?

Session replay has quietly become default infrastructure. Product teams want to see where users stall, support wants to stop asking "can you send a screenshot," and engineering wants a reproduction path for the bug that only happens on one customer's machine. The business case writes itself. The security review, in most organisations, never really happened. So when the question finally comes up - where does this stop being lawful? - most teams go looking for the answer in the wrong place.

Best Unified Data Security Platforms for 2026: 7 Compared

Security teams comparing unified data security platforms in 2026 are no longer just choosing between DLP vendors. They're deciding how much of their data security architecture, discovery, classification, enforcement, insider risk, and AI governance should live in one system versus remain assembled and operated from separate tools. That decision has gotten harder. DSPM vendors are adding DLP. DLP vendors are adding posture management. Everyone claims AI coverage.

SACR's New ECP Framework: What It Means for AI and Data Security

A new report from Software Analyst Cyber Research (SACR), The CISO Guide to Endpoint Control and Prevention (ECP): The Next Architecture for Endpoint Security, outlines a new era of endpoint security shaped by AI agents, copilots, SaaS applications, browser-based workflows, and increasingly autonomous activity. The report introduces Endpoint Control and Prevention (ECP) as a framework for understanding this shift and the new security capabilities it requires.