A false positive is a situation where a file or activity is incorrectly identified as malicious by a security tool, when in fact it is benign or harmless. A false positive can cause unnecessary alerts, disruptions, or remediation actions, and reduce the confidence and efficiency of the security system. In this question, a file is identified as malware by the Local Analysis module, whereas WildFire verdict is Benign, assuming WildFire is accurate. This means that the Local Analysis module has made a mistake and flagged a legitimate file as malicious, while WildFire has correctly determined that the file is safe. Therefore, this is an example of a false positive. The Local Analysis module is a feature of the Cortex XDR agent that uses a static set of pattern-matching rules and a statistical model to determine if an unknown file is likely to be malware. The Local Analysis module can provide a fast and offline verdict for files that are not yet analyzed by WildFire, but it is not as accurate or comprehensive as WildFire, which uses dynamic analysis and machine learning to examine the behavior and characteristics of files in a sandbox environment. WildFire verdicts are considered more reliable and authoritative than Local Analysis verdicts, and can override them in case of a discrepancy. Therefore, if a file is identified as malware by the Local Analysis module, but as Benign by WildFire, the WildFire verdict should be trusted and the Local Analysis verdict should be disregarded123

References:

False positive (security) - Wikipedia

Local Analysis

WildFire Overview