What capability allows Zscaler to identify and block various types of cyber threats?

AI-powered detection capabilities enable Zscaler to effectively identify and block a wide range of cyber threats by leveraging advanced algorithms and machine learning techniques. This capability allows Zscaler to analyze vast amounts of data in real time, learn from patterns, and identify anomalies that may indicate malicious activity or potential threats.

By utilizing artificial intelligence, Zscaler can enhance its detection accuracy beyond traditional methods, adapting to new types of threats as they evolve. This proactive approach helps in recognizing previously unknown threats based on their behavior and characteristics, providing a robust layer of security.

While signature-based detection relies on known threats and requires constant updates, and user behavior analytics focuses on behavioral patterns of users to detect anomalies, AI-powered detection offers a more dynamic and comprehensive solution. Static code analysis, on the other hand, is typically used in the context of application security during the development phase to detect vulnerabilities, which is not the primary function in the context of real-time threat detection.