Free ECCouncil 312-39 Practice Exam with Questions & Answers | Set: 4

The first step should prioritize immediate containment to stop ongoing exfiltration and prevent further compromise. Isolating the workstation (network isolation or EDR containment) and revoking remote access (terminate sessions, block the suspicious IP, disable the user’s remote access methods) directly reduces the attacker’s ability to continue transferring sensitive data and limits lateral movement risk. In incident response, containment precedes deep forensics when active harm is likely; you preserve evidence while stopping the bleeding. Conducting full forensics first can delay containment and allow continued data theft. Disabling corporate VPN entirely is overly disruptive and does not target the specific compromised endpoint or account; it can also hinder business operations and incident response activity. Informing the department and waiting is inappropriate given the indicators of compromise and policy violation (unauthorized USB). After containment, the SOC should preserve volatile evidence if possible (RAM, active connections), collect relevant logs, assess data accessed, and coordinate with legal/HR due to insider threat implications. But the initial, highest-priority action is targeted containment of the affected workstation and access paths.

After identifying the required event sources in a Security Operations Center (SOC) process, the next stage is to define rules for the use case. This involves specifying the criteria or conditions that will trigger alerts or actions based on the data received from the identified event sources. It is a critical step in ensuring that the SOC can effectively monitor and respond to security events.

Integrating XDR with XSOAR best meets the combined goals of real-time correlation and streamlined response workflows. XDR’s strength is cross-domain detection and correlation (identity, endpoint, email, cloud, network) to produce higher-fidelity incidents from noisy signals—critical in phishing-driven compromises. XSOAR’s strength is orchestrating response: enrichment, case management, approvals, containment actions (disable account, revoke sessions, isolate device), and notifications, all executed consistently through playbooks. When integrated, detections produced by XDR can automatically trigger XSOAR playbooks that standardize triage and containment, reducing response time and analyst workload while improving consistency and auditability. Integrating XDR with SIEM improves centralized visibility and correlation inside the SIEM, but it does not directly address end-to-end automated workflows. EDR integrations (with SIEM or XSOAR) are narrower in scope—useful for endpoint actions but less effective for phishing campaigns that span identity, email, and cloud resources. Since the question explicitly requires both improved correlation and streamlined response automation, XDR-to-XSOAR is the most complete option among those provided.

TheIIS log events indicate a SQL Injection Attack. This is evident from the complex SQL queries present in the log, which include functions like “UNICODE”, “SUBSTRING”, and “MAX”. These functions are being used in a manner that suggests manipulation of strings and extraction of data, which are common tactics in SQL injection attacks. The use of specific characters like CHAR(97) and CHAR(108) within the queries is a technique often employed to bypass security mechanisms during such attacks.

In the context of log storage, a circular buffer is a data structure that uses a single, fixed-size buffer as if it were connected end-to-end. This structure lends itself to bufferingstreams of data, where the data is written to the buffer and read from it in a potentially non-sequential manner. When the buffer is full, new data is written starting at the beginning of the buffer, and thus ‘wraps’ around. This is why the method is referred to as ‘wrapping’. FIFO (First In, First Out) and LIFO (Last In, First Out) are queueing methods, and non-wrapping implies that the buffer does not overwrite existing data when full.

Cloud storage best meets long-term log archival requirements when the priorities are scalability, encryption, durability, and accessibility. From a SOC and compliance standpoint, log volume growth is predictable and often spikes during incidents; cloud storage provides elastic scale without the operational overhead of continuously expanding on-prem capacity. Encryption at rest and in transit is typically standard in cloud storage services, supporting confidentiality requirements for regulated data. Cloud storage also supports lifecycle management (hot to cool/archive tiers), retention policies, and immutability options that help preserve evidentiary integrity for investigations and audits. Local storage is limited by physical capacity, increases risk of single-site failure, and becomes costly to scale and maintain for multi-year retention. “Distributed” and “hybrid” can be viable architectures, but they are broader design patterns rather than a direct fit to the stated requirements; distributed systems still require significant operational management, and hybrid introduces complexity around governance and residency unless explicitly required. Given the need for scalable, encrypted, long-term archival that remains accessible for SOC analytics and audits, cloud storage is the most appropriate option in this question’s context.

Chain of custody is the formal process used to document and preserve evidence integrity by recording who collected the evidence, who accessed it, where it was stored, and when it changed hands. In SOC and forensic operations, chain of custody is essential for maintaining evidentiary reliability, especially in cases with regulatory, legal, or disciplinary implications. It ensures that evidence has not been altered, tampered with, or mishandled, and it supports defensible conclusions about what occurred. Incident documentation is broader and includes timelines, decisions, actions taken, and communications, but it does not specifically track evidence handling transfers. Data imaging is the creation of a forensic copy of storage media (disk image), a separate technical step that may be recorded within chain-of-custody logs. Digital fingerprinting refers to generating hashes or other identifiers to confirm file integrity; again, it is a technique used within evidence handling, but the tracking record of handlers, locations, and transfers is chain of custody. For SOC analysts, correctly maintaining chain of custody is critical when responding to breaches involving sensitive customer records and potential compliance investigations.

Networksniffing is the process of monitoring and capturing all data packets passing through a given network. This is typically done using specialized software or hardware tools designed for this purpose. Here’s a detailed explanation of the process:

Monitoring Traffic: Network sniffing involves using a tool to monitor the data flowing over the network. This can include all types of data packets, regardless of where they come from or where they are going.

Capturing Packets: The tool captures each packet that passes through the network. This includes the packet’s header, which contains information about the packet’s source, destination, and other metadata, as well as the payload, which is the actual data being transmitted.

Analysis: Once captured, the packets can be analyzed for various purposes, such as troubleshooting network issues, monitoring network performance, or detecting security threats.

Tools Used: There are many tools available for network sniffing, with Wireshark being one of the most popular and widely used due to its powerful features and flexibility1.