Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI has removed the skill, personalization, and speed barriers that once limited cyberattacks. Attackers use language models at every stage of the kill chain, from recon to persistence, and underground tools sell pre-jailbroken access to mainstream models for as little as $50 a week. But because every attack still has to change a file, a configuration, or a script on a real system, detecting unplanned change works no matter which model wrote the payload.

Data masking limits unnecessary exposure when teams copy sensitive production values into testing, analytics, and sharing workflows. It replaces those values with realistic substitutes, but weak implementations still permit inference, linkage, or reversal. Effective programs select techniques based on downstream use and test each output against its intended workflow.

As AI agents spread across IT environments, organizations struggle to see what agents they have and what data those agents can access. For Cybersecurity Awareness Month, we wanted to share what Netwrix is doing to help IT and security teams improve agentic AI visibility and governance to keep their sensitive data secure. I recently sat down with Jeff Warren, our chief product officer, who has been working through this problem with customers for a while.

A local password manager stores your credentials in an encrypted vault on your own device or server. You control your data and backups, but you also manage keys and updates yourself. That works for one person. Teams need role-based access, approvals for sensitive accounts, and logs that show who accessed what.

A data risk assessment evaluates where sensitive data lives, who can reach it, and what happens if that access is misused. It creates value only when teams assign and track remediation; without current access data and live verification, organizations can't show that exposure has fallen. 75% of sensitive data exposures begin with compromised identities or misconfigured permissions, according to the Netwrix 2026 Data and Identity Security Report.

Remote code execution (RCE) lets an attacker run commands on a system they don't own, usually through a flaw in a web application, CMS, VPN portal, or API. A successful exploit inherits the permissions of the vulnerable service, and many services run with far more access than they need. AI shortens the time from a disclosed flaw to a working exploit and lets attackers test thousands of exposed systems at once. A remote code execution flaw turns a vulnerable server into someone else's computer.

Proactive security means measuring your posture against clear policies on a steady rhythm and fixing risk before it becomes an alert or an audit finding. Most teams still work reactively: they wait for an auditor or an alert, investigate, and then act. SOC 2, ISO 27001, and NIST CSF already expect ongoing improvement. Getting there takes a shift in mindset and tools that make the rhythm easy to keep.