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[General] Switch Your Nervousness in Security-Operations-Engineer Exam by Using Google Sec

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【General】 Switch Your Nervousness in Security-Operations-Engineer Exam by Using Google Sec

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Google Cloud Certified - Professional Security Operations Engineer (PSOE) Exam Sample Questions (Q54-Q59):NEW QUESTION # 54
You are responsible for identifying suspicious activity and security events in your organization's environment.
You discover that some detection rules are generating false positives when the principal.ip field contains one or more IP addresses in the 192.168.2.0/24 subnet. You want to improve these detection rules using the principal.ip repeated field. What should you add to the YARA-L detection rules?
  • A. net.ip_in_range_cidr(all $e.principal.ip, "192.168.2.0/24")
  • B. net.ip_in_range_cidr(any $e.principal.ip, "192.168.2.0/24")
  • C. not net.ip_in_range_cidr(all $e.principal.ip, "192.168.2.0/24")
  • D. not net.ip_in_range_cidr(any $e.principal.ip, "192.168.2.0/24")
Answer: D
Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option D. The goal is to exclude events (i.e., stop false positives) when the principal.
ip field contains any IP from the trusted 192.168.2.0/24 subnet.
The principal.ip field in UDM is a repeated field, meaning it can hold an array of values (e.g., ["1.2.3.4",
"192.168.2.5"]). YARA-L provides the any and all quantifiers to handle repeated fields.9
* any $e.principal.ip: This checks if at least one IP in the array meets the condition.
* all $e.principal.ip: This checks if every IP in the array meets the condition.
The function net.ip_in_range_cidr(...) returns true if an IP is in the specified range.
Therefore, the logic we need is: "do not trigger this rule if any of the IPs in the principal.ip field are in the
192.168.2.0/24 range."
This translates directly to the YARA-L syntax: not net.ip_in_range_cidr(any $e.principal.ip, "192.168.2.0/24")
* Option B would only find events from that subnet.
* Option A would only find events where all associated IPs are in that subnet.
* Option C is the logical inverse of A and would incorrectly filter out events that might be malicious (e.
g., ["1.2.3.4", "192.168.2.5"] would not be excluded because all IPs are not in the range).
Exact Extract from Google Security Operations Documents:
YARA-L 2.0 language syntax > Repeated fields and boolean expressions: When a boolean expression, such as a function call, is applied to a repeated field, you can use the any or all keywords to specify how the expression should be evaluated.10
* any <repeated_field>: The expression evaluates to true if it is true for at least one of the values in the repeated field.
* all <repeated_field>: The expression evaluates to true only if it is true for all of the values in the repeated field.
Functions > net.ip_in_range_cidr: The net.ip_in_range_cidr function is useful to bind rules to specific parts of the network.11 To exclude all private netblocks as defined in RFC1918, you can add a not to the start of the criteria:
and not (net.ip_in_range_cidr(any $e.principal.ip, "10.0.0.0/8") or net.ip_in_range_cidr(any $e.principal.ip,
"172.16.0.0/12") or net.ip_in_range_cidr(any $e.principal.ip, "192.168.0.0/16")) References:
Google Cloud Documentation: Google Security Operations > Documentation > Detections > YARA-L 2.0 language syntax Google Cloud Documentation: Google Security Operations > Documentation > Detections > YARA-L 2.0 functions > net.ip_in_range_cidr

NEW QUESTION # 55
Your company is taking a more proactive approach to security. You want to generate an alert when a binary hash first appears in your environment. What should you do?
  • A. Navigate to the Alerts & IOCs page in Google Security Operations (SecOps). Create a filter that targets hashes and specifies a first_seen_time value excluding the current date.
  • B. Write a rule to examine file-related events that join with derived context for hashes in the entity graph. Compare the timestamp of the hash with the first_seen_time field.
  • C. Create a table by using the Google Security Operations (SecOps) statistics in search to examine file-related events for the current day. Verify that the first_seen_time value predates the current day.
  • D. Enable the Applied Threat Intelligence - Curated Prioritization rule set in curated detections.
Answer: B
Explanation:
To generate an alert when a binary hash first appears, you should write a detection rule for file- related events that joins with derived context for hashes in the entity graph and compare against the first_seen_time field. This ensures the rule triggers only when the hash is newly observed in your environment, providing proactive detection of potentially malicious binaries.

NEW QUESTION # 56
You are responsible for managing threat intelligence and IOC lists in your organization. You have compiled a list of IOCs from recent incidents. You want to quickly and efficiently share the IOCs with other teams for collaboration and integration into their operational processes. What should you do?
  • A. Create a list in Google Security Operations (SecOps), and grant the required access to the other teams.
  • B. Create a new threat graph in Google Threat Intelligence, and share the graph with the other teams.
  • C. Export the IOCs from Google Threat Intelligence in CSV or JSON format, and email the file to the other teams.
  • D. Add the IOCs to a collection in Google Threat Intelligence, and share the collection with the other teams.
Answer: A
Explanation:
The most efficient and collaborative approach is to create a reference list in Google SecOps and grant access to the other teams. This allows teams to directly use the IOCs in detection rules, playbooks, and investigations without manual file transfers, ensuring the data is consistently available and up-to-date across operational processes.

NEW QUESTION # 57
You are developing a playbook to respond to phishing reports from users at your company. You configured a UDM query action to identify all users who have connected to a malicious domain. You need to extract the users from the UDM query and add them as entities in an alert so the playbook can reset the password for those users. You want to minimize the effort required by the SOC analyst. What should you do?
  • A. Create a case for each identified user with the user designated as the entity.
  • B. Configure a manual Create Entity action from the Siemplify integration that instructs the analyst to input the Entities Identifier parameter based on the results of the action.
  • C. Use the Create Entity action from the Siemplify integration. Use the Expression Builder to create a placeholder with the usernames in the Entities Identifier parameter.
  • D. Implement an Instruction action from the Flow integration that instructs the analyst to add the entities in the Google SecOps user interface.
Answer: C
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
The key requirement is to *automate* the extraction of data to *minimize analyst effort*. This is a core function of Google Security Operations SOAR (formerly Siemplify). The **Siemplify integration** provides the foundational playbook actions for case management and entity manipulation.
The **`Create Entity`** action is designed to programmatically add new entities (like users, IPs, or domains) to the active case. To make this action automatic, the playbook developer must use the **Expression Builder**. The Expression Builder is the tool used to parse the JSON output from a previous action (the UDM query) and dynamically map the results (the list of usernames) into the parameters of a subsequent action.
By using the Expression Builder to configure the `Entities Identifier` parameter of the `Create Entity` action, the playbook automatically extracts all `principal.user.userid` fields from the UDM query results and adds them to the case. These new entities can then be automatically passed to the next playbook step, such as
"Reset Password."
Options A and C are incorrect because they are **manual** actions. They require an analyst to intervene, which does *not* minimize effort. Option D is incorrect as it creates multiple, unnecessary cases, flooding the queue instead of enriching the single, original phishing case.
*(Reference: Google Cloud documentation, "Google SecOps SOAR Playbooks overview"; "Using the Expression Builder"; "Marketplace and Integrations")*
***

NEW QUESTION # 58
You work for an organization that uses Security Command Center (SCC) with Event Threat Detection (ETD) enabled. You need to enable ETD detections for data exfiltration attempts from designated sensitive Cloud Storage buckets and BigQuery datasets. You want to minimize Cloud Logging costs. What should you do?
  • A. Enable "data read" and "data write" audit logs for all Cloud Storage buckets and BigQuery datasets throughout the organization.
  • B. Enable "data read" and "data write" audit logs only for the designated sensitive Cloud Storage buckets and BigQuery datasets.
  • C. Enable VPC Flow Logs for the VPC networks containing resources that access the sensitive Cloud Storage buckets and BigQuery datasets.
  • D. Enable "data read" audit logs only for the designated sensitive Cloud Storage buckets and BigQuery datasets.
Answer: D
Explanation:
To detect data exfiltration attempts from sensitive Cloud Storage buckets and BigQuery datasets using ETD, you only need "data read" audit logs. These logs capture access and read events (which indicate potential exfiltration). Enabling them only for the designated sensitive resources minimizes Cloud Logging costs while still providing the necessary visibility for detections.

NEW QUESTION # 59
......
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