CrowdStrike Advances the Use of AI to Predict Adversary Behavior and Significantly Improve Protection

CrowdStrike is advancing its use of artificial intelligence (AI) and machine learning (ML) to enhance cybersecurity by introducing AI-powered indicators of attack (IoA) models. These models aim to detect and predict malicious behavior patterns in real-time, regardless of the tools or malware used, by using machine intelligence to stop breaches more effectively. The company has pioneered AI applications in cybersecurity to tackle sophisticated attacks, address hyperscale data challenges, and automate repetitive security tasks, effectively closing the cybersecurity skills gap. Innovations include multi-process atomic behavior analysis in Windows, detection of malicious command lines and living-off-the-land binaries (LOLBins), and AI-powered coverage for malicious Linux scripts and fileless .NET assemblies. These developments enhance proactive detection and prevention capabilities across diverse operating systems and attack vectors, offering increased visibility and protection against evolving adversarial techniques. CrowdStrike continues to leverage deep learning and cloud-native machine intelligence to improve the speed and precision of detecting new behavioral patterns, thereby maintaining a robust defense against emerging cyber threats.