Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Recognizing the indicators of insider risk before they turn into threats requires a paradigm shift in the way we operate. It necessitates moving from a reactive mode of operation to proactive. And it requires data that is continuously captured and analyzed to enable security teams to easily see patterns and anomalies and gauge the level of risk of specific behaviors.

Check out the highlights from our most recent update, Platform Release 698. This release contains 449 items including new features, improvements, and bug fixes. See the highlights below. For a full rundown, check out the complete Release Notes here.

You may trust the people you work and partner with, but you never know how they really behave and handle your sensitive data within your organization’s network. Each user in your IT infrastructure brings their own security risks. Tracking user activity helps mitigate those risks and enhance your organization’s security. This article will show you how to set up an efficient user activity monitoring (UAM) process with Ekran System.

Elizabeth Harz, CEO of Veriato, sits down with Chris Hughes from Acceleration Economy for an exclusive interview to discuss the evolving landscape of insider risk management.

External cybersecurity threats are a well-known problem, but organizations should also be aware of managerial insider threats. These threats originate from individuals with privileged access and authority and can cause devastating damage to an organization’s data, reputation, and bottom line. In this guide, we’ll examine managerial insider threats and offer insights and strategies you can use to detect, prevent, and mitigate these risks.

An insider threat occurs when a legitimate user of an organization’s systems intentionally or accidentally puts the organization’s data at risk. These threats can have a devastating impact on a company’s data, reputation, and bottom line. Insider threat hunting has become essential to proactively identify and mitigate these risks before they escalate into full-blown security incidents.

Generative AI (GenAI) tools like ChatGPT have already become indispensable across organizations worldwide. CEOs are particularly enthusiastic about GenAI’s ability to let employees “do more with less”. According to the McKinsey Global Survey on the State of AI in 2024, 65% of organizations already use GenAI tools extensively, and Gartner forecasts that this number will reach 80% by 2026.

A company’s success depends on its employees’ quality, motivation, and honesty. Unmotivated employees who feel neglected and under-appreciated may not hesitate to deceive their employer for their own personal benefit. This type of fraud is known as occupational fraud, and it’s a growing concern for business leaders. So, how can employers detect and prevent this type of fraud from happening?

Is your company grappling with an increasing volume and complexity of information? A strong data governance framework is essential to harness the power of data while lessening risks. This strategic framework ensures data is managed effectively, meets quality standards, and supports informed decision-making, quality standards, and supporting informed decisions. As regulatory compliance burdens intensify, data governance has become critical to organizational success.

In today’s data-driven world, safeguarding sensitive information is paramount. A well-crafted Data Loss Prevention (DLP) strategy acts as a shield, protecting your organization from costly data breaches and reputational damage and ensuring you meet regulatory requirements. Following a step-by-step guide ensures you cover all the essential bases, from selecting a loss prevention policy that aligns with your needs to conducting regular security audits.