Is your security team using AI to monitor against threats? Great. But the bad guys are also using AI to target your company - what are you doing about that?

Almost all security teams, SOCs, and MSSPs we work with now are using AI constantly, especially to monitor log files, analyze suspicious events, detect signs of unauthorized access, malware infections, and other security breaches that might have gone unnoticed by manual analysis.

AI-driven incident response platforms can automatically prioritize incidents based on severity and potential impact, allowing security engineers to focus on critical threats first. Additionally, these tools can enrich incident data with contextual information from external threat intelligence sources, empowering engineers to understand the full scope of an attack.

False positives in security alerts are a persistent challenge that can lead to alert fatigue and potentially overlook real threats. Fortunately, AI has emerged as a powerful ally in reducing false positives and enhancing the accuracy of security alerts.

By learning from past incidents and continuously updating their models, AI algorithms can better discern legitimate threats from benign events. Over time, this results in a more refined filtering process, significantly decreasing the number of false alarms and allowing security engineers to focus their efforts on genuine risks.

When handling complex security incidents, AI can assist in identifying attack patterns and tactics used by threat actors, enabling engineers to deploy targeted countermeasures. AI algorithms can also provide guidance on optimal response strategies, suggesting the most effective courses of action based on historical data and best practices.

But cybercriminals are using AI too. In our next post, we will look at ways that cybercriminals are using AI to target your company.