What technologies does Cloud Sandbox utilize to detect malicious files?

The Cloud Sandbox employs advanced AI and machine learning (ML) techniques, along with behavioral analysis, to identify and detect malicious files. This approach enables the system to analyze file characteristics and behaviors in a dynamic environment, which helps uncover sophisticated threats that may not be identifiable through traditional methods.

By leveraging AI and ML, Cloud Sandbox can continuously learn from new data and adapt its detection capabilities, improving its ability to identify harmful patterns and anomalies. Behavioral analysis augments this process by observing how files act in a simulated environment, which is crucial for recognizing malicious behavior that might be masked when the files are static.

In contrast, manual reviews by security analysts, while useful, rely on human expertise and can be time-consuming, and often cannot keep pace with the volume of threats. Regular expressions and pattern matching function well for known threats, but they may not effectively detect new or evolutionarily modified malware. Basic keyword detection often lacks the sophistication needed for identifying complex threats and can easily result in false positives. Thus, the combination of AI, ML, and behavioral analysis provides a robust solution for detecting malicious files in the Cloud Sandbox environment.