During the exfiltration stage, attackers move the pilfered data outside the compromised network. This can involve using various methods such as unauthorized file transfers, covert channels, or disguising data within legitimate network traffic to avoid detection.
Analyzing network traffic for suspicious activities such as unauthorized file access, unusual application behavior, or unusual patterns like unexpected data transfers, or large volumes of outbound traffic can indicate potential data exfiltration.
Vectra AI utilizes behavioral analysis to detect abnormal patterns in network and user behavior that may indicate data exfiltration. Leveraging artificial intelligence and machine learning algorithms, Vectra AI identifies deviations from normal behavior, enabling it to detect subtle and sophisticated exfiltration techniques.
Vectra AI focuses on identifying anomalous communication patterns, such as unusual data flows or connections to external entities, which may signify data exfiltration. The platform performs contextual analysis, considering various factors such as user behavior, network topology, and data access patterns to enhance the accuracy of exfiltration detection.