Insider threats pose a significant risk to organizations, as malicious or negligent insiders can cause substantial damage to sensitive data, intellectual property, and critical systems. Traditional security measures often focus on external threats, leaving organizations vulnerable to internal threats that are difficult to detect and mitigate. Identifying and addressing insider threats is a major challenge for security teams, leading to potential breaches, financial losses, and reputational harm.
MixMode’s dynamical threat detection platform continuously monitors user activity to detect suspicious behavior that may indicate an insider threat.
The MixMode Platform utilizes self-supervised learning to forecast expected behavior and detect potential threats by analyzing network activity and extracting patterns and trends from the underlying time-stamped data without predefined rules or training.
By understanding your network's normal behavior, MixMode can identify and surface known or unknown attacks in real-time, providing unparalleled threat detection capabilities and increasing the efficiency and productivity of the SOC.
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