Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Shadow data is information that exists within an organization's environment but falls outside IT visibility and governance. It accumulates through everyday business activities such as copying files to personal drives, exporting data for testing, and using unapproved cloud apps. This hidden data creates security vulnerabilities, compliance risks, and operational inefficiencies.

NIST CSF 2.0 expands the Cybersecurity Framework into a broader, risk-based model centered on governance, making leadership accountable for cybersecurity as an enterprise risk. It introduces a sixth core function, enhances supply chain and privacy integration, and improves usability for organizations of all sizes. Profiles, tiers, and new implementation resources help align security efforts with business objectives and evolving threat landscapes.

OPSWAT Gold Certification validates that Netwrix Endpoint Protector delivers consistent encryption and data protection across Windows, macOS, and Linux. Linux environments often lack visibility and control, creating gaps in endpoint security. Extending unified policies across all operating systems reduces risk, strengthens compliance, and improves visibility into how sensitive data is accessed and moved across the environment. Many organizations believe their endpoint security is well covered.

NetSuite testing becomes complex due to dependencies between customizations, multiple environments, and frequent updates. Effective testing requires clear scope, accurate environment selection, and version validation. Structuring tests around requirements, prioritization, and version history helps teams improve coverage, reduce inefficiencies, and ensure changes do not negatively impact existing functionality.

DSPM solutions continuously discover and classify sensitive data, map who can access it, and surface misconfigurations across cloud and hybrid environments. Without them, security teams cannot reliably find shadow data, assess real exposure, or demonstrate that sensitive information is protected. Choosing the right platform means matching data coverage, risk prioritization, and remediation workflows to your actual estate.

Most organizations can answer "who can log in" but not "who can access a specific sensitive file, and should they?" Data access governance (DAG) closes that gap. It governs who can reach sensitive data, whether that access is appropriate, and how teams review that access over time, connecting visibility, control, and automation so organizations can govern access continuously rather than scramble before each audit.

AI cybersecurity companies in 2026 fall into two categories: platforms using AI to automate detection, investigation, and response, and platforms built to secure the AI systems organizations are now deploying. With this grouping into ‘AI for Security’ and ‘Security for AI’, this article covers the breadth and depth of AI cyber security companies.

Microsoft just dropped their latest critical infrastructure threat guidance along with their latest Digital Defense Report. And if you read between the lines, there’s a very clear story: Attackers aren’t smashing windows anymore. They’re walking in the front door… quietly… with your credentials. Let me say that again. They’re logging in. Not breaking in.

Compare the top data access governance tools for 2026. Learn what to look for, and which platforms fit mid-market security teams. TL;DR: Data access governance tools map effective permissions to sensitive data, surface overexposed entitlements, and operationalize access reviews across hybrid environments. Without them, organizations cannot answer who can reach regulated data, enforce least privilege, or complete certifications without manual effort.

Identity management is the foundational process of governing every digital identity across your environment: who exists, what they access, and whether that access remains appropriate. Credential abuse is the leading initial attack vector in confirmed breaches. The discipline requires a clean source of truth, automated lifecycle workflows, and continuous governance that scales across hybrid and SaaS environments.