You are evaluating the most appropriate Prevention Policy Machine Learning slider settings for your environment. In your testing phase, you configure the Detection slider as Aggressive. After running the sensor with this configuration for 1 week of testing, which Audit report should you review to determine the best Machine Learning slider settings for your organization?
To determine the best Machine Learning slider settings for your organization after configuring the Detection slider as Aggressive and testing for a week, you should review the Machine-Learning Prevention Monitoring report. This dashboard allows you to view malware that would have been blocked over the selected timeframe based on different Machine Learning Prevention settings (Cautious, Moderate, Aggressive, or Extra Aggressive). It provides insights into ML expected detections and helps in deciding the optimal settings for your environment.
D IS CORRECT
D is the correct answer, tested in console. Audit logs --> Machine-learning prevention monitoring It shows the count of ML expected detections based on the detection levels for a defined time period and the list of files that would be detected on each detection level.
answer should be D here is what it does Machine-Learning Prevention Monitoring Use this dashboard to view malware that would have been blocked in your environment over the selected timeframe based on different Machine Learning Prevention settings (Cautious, Moderate, Aggressive or Extra Aggressive).
D is the correct answer.
D is the only answer. Also checked in the console
Only Machine-Learning Prevention Monitoring.
I asked chatGPT "explain me Prevention Policy Debug dashboard reports on Crowdstrike console" a/ It displays data on events that triggered security policies, such as blocked and allowed events, and the specific policy rule that was applied. This report allows administrators to evaluate the effectiveness of their security policies and make adjustments as necessary to improve the platform's overall security posture.