purple-ai

SentinelOne threat investigation uses natural language processing to analyze security telemetry across endpoints, cloud workloads, and identities. You ask plain English questions about threats or anomalies, and the system returns an analysis with ready-to-execute PowerQuery strings for deeper data inspection.

Yes, PowerQuery generation translates natural language questions into ready-to-execute query strings for in-depth security telemetry analysis. By asking about specific behaviors like PowerShell processes connecting to external IPs, the system automatically builds the corresponding query logic to hunt for malicious activity.

MITRE ATT&CK mapping provides context by linking detected threats and behavioral anomalies to known adversary tactics, techniques, and procedures. This contextual mapping helps cybersecurity analysts understand the broader attack framework and threat lifecycle during investigations.

Behavioral anomaly analysis across endpoints, cloud workloads, and identities is best handled by querying security telemetry with natural language to find suspicious activities. This approach leverages AI to rapidly identify malicious behavior and generate PowerQueries for targeted threat hunting.

Yes, executing PowerQuery for cybersecurity threat analysis requires the dedicated purple_ai tool for query execution and analysis. This tool processes the natural language input, generates the query strings, and returns the behavioral anomaly findings across your telemetry.