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NEW QUESTION # 136
You are investigating whether an advanced persistent threat (APT) actor has operated in your organization's environment undetected. You have received threat intelligence that includes:
* A SHA256 hash for a malicious DLL
* A known command and control (C2) domain
* A behavior pattern where rundll32.exe spawns powershell.exe with obfuscated arguments Your Google Security Operations (SecOps) instance includes logs from EDR, DNS, and Windows Sysmon.
However, you have recently discovered that process hashes are not reliably captured across all endpoints due to an inconsistent Sysmon configuration. You need to use Google SecOps to develop a detection mechanism that identifies the associated activities. What should you do?
Answer: B
Explanation:
The core of this problem is the unreliable data quality for the file hash. A robust detection strategy cannot depend on an unreliable data point. Options B and C are weak because they create a dependency on the SHA256 hash, which the prompt states is "not reliably captured." This would lead to missed detections.
Option A is far too broad and would generate massive noise.
The best detection engineering practice is to use the reliable IoCs in a flexible and high-performance manner.
The domain is a reliable IoC (from DNS logs), and the hash is still a valuable IoC, even if it's only intermittently available.
The standard Google SecOps method for this is to create a List (referred to here as a "data table") containing both static IoCs: the hash and the domain. An engineer can then write a single, efficient YARA-L rule that references this list. This rule would trigger if either a PROCESS_LAUNCH event is seen with a hash in the list or a NETWORK_DNS event is seen with a domain in the list (e.g., (event.principal.process.file.sha256 in
%ioc_list) or (event.network.dns.question.name in %ioc_list)). This creates a resilient detection mechanism that provides two opportunities to identify the threat, successfully working around the unreliable data problem.
(Reference: Google Cloud documentation, "YARA-L 2.0 language syntax"; "Using Lists in rules"; "Detection engineering overview")
NEW QUESTION # 137
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?
Answer: D
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
This question is a balance between enabling detection and managing cost. Event Threat Detection (ETD) identifies threats by analyzing logs, and the specific detection for data exfiltration requires Data Access audit logs.
Data Access audit logs are disabled by default because they are high-volume and can be expensive. The key requirement is to "minimize Cloud Logging costs" while still enabling the detection for specific sensitive resources.
Data exfiltration is a "data read" operation. Therefore, to meet the requirements, the organization only needs to enable "data read" audit logs. Enabling "data write" logs (Option B) is unnecessary for this detection and would add needless cost. Enabling logs for all resources (Option C) would be prohibitively expensive and violates the "minimize cost" constraint. While ETD does use VPC Flow Logs (Option D) for many network- based detections, they do not provide the resource-level detail (i.e., which bucket or dataset was accessed) required for this specific data exfiltration finding. Therefore, enabling "data read" logs only for the sensitive resources is the most precise, cost-effective solution.
(Reference: Google Cloud documentation, "Event Threat Detection overview"; "Enable Event Threat Detection"; "Cloud Logging - Data Access audit logs")
NEW QUESTION # 138
Your organization uses Google Security Operations (SecOps) for security analysis and investigation. Your organization has decided that all security cases related to Data Loss Prevention (DLP) events must be categorized with a defined root cause specific to one of five DLP event types when the case is closed in Google SecOps.
How should you achieve this?
Answer: C
Explanation:
Comprehensive and Detailed 150 to 250 words of Explanation From Exact Extract Google Security Operations Engineer documents:
To enforce a specific categorization requirement at the time of case closure, you must customize the Close Case dialog. This feature in Google SecOps SOAR allows administrators to mandate specific fields that analysts must complete before a case can be resolved.
The documentation on Case Management states: "You can customize the Close Case dialog box to require analysts to provide specific information before closing a case... You can add custom fields, such as Root Cause, and define the values that populate the list." By adding the "five DLP event types" as options in the Root Cause dropdown within the Close Case settings, you ensure that analysts cannot close a DLP case without selecting one of these defined types. Options A, B, and C relate to tagging or naming during the active investigation phase and do not enforce the data entry requirement strictly "when the case is closed" as requested.
References: Google Security Operations Documentation > Case Management > Customize the Close Case dialog
NEW QUESTION # 139
You work for an organization that operates an ecommerce platform. You have identified a remote shell on your company's web host. The existing incident response playbook is outdated and lacks specific procedures for handling this attack. You want to create a new, functional playbook that can be deployed as soon as possible by junior analysts. You plan to use available tools in Google Security Operations (SecOps) to streamline the playbook creation process. What should you do?
Answer: B
Explanation:
Comprehensive and Detailed Explanation
The correct solution is Option C. The primary constraints are to "streamline" the process, create a "new, functional playbook," get it "as soon as possible," and "use available tools in Google Security Operations." Google Security Operations integrates Gemini directly into the SOAR platform to accelerate security operations. One of its key capabilities is generative playbook creation. This feature allows an analyst to describe their intended objectives in natural language (e.g., "Create a playbook to investigate and respond to a remote shell alert"). Gemini then generates a complete, logical playbook flow, including investigation, enrichment, containment, and eradication steps.
This generated playbook serves as a high-quality draft. The analyst can then add the necessary customizations (like specific tools, notification endpoints, or contacts for the e-commerce platform) and, most importantly, test the playbook to ensure it is functional and reliable for junior analysts to execute. This workflow directly meets all the prompt's requirements, especially "streamline" and "as soon as possible." Option D (creating a custom playbook from scratch and using a red team) is the exact opposite of streamlined and fast. Option B involves patching an "outdated" playbook, not creating a new one. Option A incorrectly bundles a specific remediation action (filtering traffic) with the playbook creation process.
Exact Extract from Google Security Operations Documents:
Gemini for Security Operations: Gemini in Google SecOps provides generative AI to assist analysts and engineers. Within the SOAR capability, Gemini can generate entire playbooks from natural language prompts.
Playbook Creation with Gemini: Instead of building a playbook manually, an engineer can describe the intended objectives of the response plan. Gemini will generate a new playbook with a logical structure, including relevant actions and conditional branches. This generated playbook serves as a strong foundation, which can then be refined. The engineer can add necessary customizations to tailor the playbook to the organization's specific environment, tools, and processes. Before deploying the playbook for use by the SOC, it is a best practice to test it against simulated alerts to validate its functionality and ensure it runs as expected.
References:
Google Cloud Documentation: Google Security Operations > Documentation > SOAR > Gemini in SOAR > Create playbooks with Gemini
NEW QUESTION # 140
You are conducting a proactive threat hunt in Google Security Operations (SecOps). You observe multiple login events with the same principal.user.userid field that originate from different countries within a short time window. You need to validate whether the account has been compromised. What should you do?
Answer: C
Explanation:
The most direct way to validate if the account shows signs of compromise is to perform a UDM search for login events and group the results by user and country of origin. This allows you to clearly identify impossible travel patterns (same user logging in from different countries in a short time window), which is a strong indicator of account compromise.
NEW QUESTION # 141
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