Use Cases:
AI-Generated Attack Detection

As artificial intelligence (AI) continues to advance, there is a growing concern about the emergence of AI-generated attacks. Threat actors are harnessing the power of artificial intelligence to develop sophisticated attack techniques that can evade traditional security measures, making them highly elusive and difficult to detect using conventional methods. These AI-generated attacks can potentially cause substantial damage to organizations, compromising sensitive data, disrupting operations, and undermining trust.

MixMode’s  patented self-learning AI platform identifies patterns and trends  without predefined rules or training, customizing to the specific  dynamics of individual networks, rather than relying on more generic  machine learning models typically found among competitors.

MixMode AI was designed to identify and mitigate advanced attacks,  including adversarial AI. An adversary would need to have a deep  understanding of MixMode’s algorithms and processes to evade detection.  However, in attempting to learn and replicate MixMode's AI, the  adversary's behavior would likely be detected as anomalous by the  platform, triggering an alert and preventing any further damage.