You are responsible for identifying suspicious activity and security events at your organization. You have been asked to search in Google Security Operations (SecOps) for network traffic associated with an active HTTP backdoor that runs on TCP port 5555. You want to use the most effective approach to identify traffic originating from the server that is running the backdoor. What should you do?
Answer(s): C
The backdoor is running on TCP port 5555 on the server, meaning the server is the source of the traffic. In Google Security Operations (SecOps), the field principal.port represents the source port of the traffic, while target.port represents the destination. Since you want to identify traffic originating from the compromised server, filtering on principal.port = 5555 is the most effective approach.
You are an incident responder at your organization using Google Security Operations (SecOps) for monitonng and investigation. You discover that a critical production server, which handles financial transactions, shows signs of unauthorized file changes and network scanning from a suspicious IP address. You suspect that persistence mechanisms may have been installed. You need to use Google SecOps to immediately contain the threat while ensuring that forensic data remains available for investigation. What should you do first?
The most effective first step in containment while preserving forensic data is to use the EDR integration to quarantine the compromised asset. Quarantine isolates the server from the network, preventing further malicious activity, but it does not wipe or reboot the system, ensuring that evidence such as persistence mechanisms, unauthorized file changes, and indicators of compromise remain intact for forensic investigation.
Your organization uses Google Security Operations (SecOps). You discover frequent file downloads from a shared workspace within a short time window. You need to configure a rule in Google SecOps that identifies these suspicious events and assigns higher risk scores to repeated anomalies. What should you do?
Answer(s): B
The correct approach is to create a frequency-based YARA-L detection rule in Google SecOps. Frequency- based rules allow you to detect repeated suspicious behavior, such as multiple file downloads within a short time window, and assign higher risk outcome scores accordingly. This ensures anomalies are prioritized based on their frequency and severity, rather than flagging isolated single events.
You are implementing Google Security Operations (SecOps) at your organization. You discover that the current detection rules are too noisy. Due to the high volume of alerts, some true positives might be missed. You want to ingest additional context sources to reduce false positives in your security detections and to improve the overall positive ratio of the alerts. What should you do?
Answer(s): A
Ingesting high-value asset (HVA) data from the CMDB allows Google SecOps to prioritize alerts based on the sensitivity and criticality of the affected systems. This reduces noise by helping analysts focus on detections involving critical assets, improving the signal-to-noise ratio and ensuring true positives on important systems are not missed.
You are developing a new detection rule in Google Security Operations (SecOps). You are defining the YARA-L logic that includes complex event, match, and condition sections. You need to develop and test the rule to ensure that the detections are accurate before the rule is migrated to production. You want to minimize impact to production processes. What should you do?
The safest way to minimize production impact is to develop and refine the rule logic in UDM search first. By running searches and reviewing outputs, you can iteratively tune filters and conditions until the detections are accurate. Once validated, you then copy the tested query into the Rules Editor. This approach ensures accuracy without risking false positives or unnecessary load in production.
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