Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

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.

Organizations are increasingly reliant on complex systems and vast amounts of sensitive data, which makes them attractive targets for cybercriminals. However, while external threats are often in the spotlight, insider risks posed by privileged users who have elevated access to critical systems and sensitive information often goes unnoticed.

According to the 2023 Insider Threat Report by Cybersecurity Insiders, 74% of organizations are at least moderately vulnerable to insider threats. This statistic underscores a critical issue: Insider threats are notoriously difficult to detect because they originate from individuals with authorized access and intimate knowledge of your systems. While traditional security measures focus on external threats, they often fall short when it comes to spotting insider threats.

Access to data comes with significant responsibility, and misuse of this access can negatively affect organizations. When employees misuse data for personal gain or other unauthorized purposes, it can jeopardize data security and lead to costly breaches. Indeed, 68% of data breaches involve a human element, according to the 2024 Data Breach Investigations Report by Verizon.