Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Short correlation windows miss insider risk because misuse develops gradually, often over longer periods than detection models track. Short correlation windows miss insider risk because misuse often spans longer periods than detection models track. When context resets at fixed intervals, small behavioral changes fail to accumulate into visible risk. When context resets at fixed intervals, behavior is evaluated in disconnected segments.

User and entity behavior analytics (UEBA) tools are essential cybersecurity solutions, helping organizations to detect anomalous activities and hidden threats. In this article, we explore the top 10 UEBA tools on the market today. You’ll learn about their key features, use cases, pricing, and customer experiences.

Insider threats often don’t trigger alerts because the activity relies on valid credentials, approved tools, and authorized workflows. When viewed as individual events, this behavior looks normal and stays below traditional rule thresholds. Risk accumulates across otherwise valid actions without producing a signal that meets alert thresholds.

Generative AI has revolutionized productivity — but it has also introduced a massive, often invisible new vulnerability: AI data exfiltration. Whether it’s a well-meaning engineer pasting source code into an LLM for debugging, or a marketer feeding sensitive customer data into a prompt for analysis, your organization’s most valuable intellectual property is likely walking out the virtual front door.

The rapid adoption of generative AI has transformed enterprise productivity, but it’s also quietly introduced a new, sophisticated vulnerability: the AI insider threat. For years, securing the internal perimeter meant watching for data exfiltration via USB sticks or unauthorized emails. Today, the risk looks entirely different.

Most insider risk programs stall at the same place: they can see what data exists, but not what users are doing with it. Data security posture management (DSPM) tools catalog sensitive files, flag misconfigured permissions, and surface overexposed repositories. What they often cannot communicate is whether that overexposed file was accessed, copied, renamed, and uploaded to a personal cloud account by an employee who put in their resignation last week.

Artificial intelligence tools have completely revolutionized the way we work, boosting productivity to heights we couldn’t have imagined just a few years ago. But the upside comes with a high-stakes catch: every time an employee pastes proprietary code, financial records, or sensitive customer data into a public AI prompt, your company is at risk. As Shadow AI adoption skyrockets, implementing robust data leakage prevention is no longer an IT checklist item — it’s a business imperative.