Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

The latest News and Information on Data Security including privacy, protection, and encryption.

Securing Your AI Agents: Today's New Data Threat

AI agents are already inside your company - reading files, calling APIs, executing code. Most of them were never approved by security. In this session, Nightfall AI walks through exactly how agents become an attack surface: prompt injection, malicious MCP servers, credential exfiltration, and more.

archTIS and Mattermost Partner to Deliver Secure Collaboration for Defence Operations

archTIS and Mattermost are pleased to announce a collaboration to deliver policy-enforced, data-centric security to secure operational collaboration for Defence Ministries, NATO Allies, and coalition partners worldwide. The collaboration combines Mattermost’s secure, mission-critical command-and-control surface with archTIS Trusted Data Integration (TDI) platform, to enable secure collaboration using dynamic policy orchestration via Attribute-Based Access Control (ABAC).

PII protection: 8-step framework from discovery to security

Most organizations can't answer three basic auditor questions simultaneously: where PII lives, who can access it, and how it's protected. One-off scans and manual classification go stale as data volumes grow. A repeatable, eight-step PII protection program from initial discovery through ongoing governance is what separates a defensible compliance posture from a snapshot that collapses under scrutiny.

Microsoft 365 DLP: what it covers and where it falls short

Microsoft 365 DLP delivers real protection for regulated data in Exchange, SharePoint, Teams, and managed Windows endpoints, but only within that boundary. On-premises file servers, Linux endpoints, unmanaged devices, and non-Microsoft SaaS fall outside enforcement regardless of how policies are configured. Most security teams can't yet clearly distinguish the gaps that configuration fixes can address from those that require supplemental controls.

Why MCP Breaks the Financial Services Security Stack

A relationship manager asks the firm's AI assistant to "summarize my top wealth clients by AUM and flag anyone with a pending transfer over $500K." The agent calls a CRM MCP server, then a core banking MCP server, then a market data MCP server, and returns a clean answer in twelve seconds. Names, balances, account numbers, pending wire details, all rendered in plain text inside the chat window. No file moved. No email left the network. No DLP channel triggered.

Securing Success: Protecting IP While Powering Productivity

To ensure a company can continue to operate and make a profit, its intellectual property must be kept safe. It’s not uncommon, however, for employees to unintentionally put IP in harm’s way – and it’s the job of security to prevent accidental disclosure or loss with the right support. Renasas’ focus on preventing accidental data leaks and protecting IP aligns with Netskope's core data loss prevention (DLP) and security capabilities.

Higher Education Spotlight: Sensitive Data Governance in Decentralized Environments

Higher education faces a unique challenge when it comes to managing sensitive data governance. Unlike a more centralized corporate environment, colleges and universities often operate across many semi-independent schools, departments, research groups, and administrative teams. Each may have its own systems, priorities, workflows, and level of security maturity. That structure is part of what makes higher education work. It supports research, academic flexibility, and departmental independence.

Protegrity + Presidio: Secure Sensitive Data in AI Workflows

See how Protegrity and Presidio help developers secure sensitive data in AI workflows. This demo shows how Protegrity AI Developer Edition helps teams discover, protect, mask, and redact sensitive data before it reaches AI models, applications, or analytics pipelines. You’ll learn how developers can.

DLP for GenAI: How to Prevent Sensitive Data Leaks in AI Tools

Employees are feeding sensitive data into AI tools at a pace most security teams did not anticipate. Source code goes into coding assistants. Customer records get pasted into ChatGPT to draft emails. Confidential contracts land in Gemini for summarization. According to Cyberhaven Labs research, 39.7% of the data employees share with AI tools is sensitive, and the volume is accelerating as AI adoption spreads from individual contributors to entire workflows.

The Best Data Loss Prevention Tools for 2026

The best data loss prevention (DLP) tools in 2026 are those that move beyond rigid, rule-based systems to incorporate AI-driven behavioral analytics. Leading solutions like Teramind (best for AI agent governance), Microsoft Purview (best for M365 ecosystems), and Zscaler (best for cloud-native protection) provide the real-time visibility needed to stop data breaches before they occur.