212-89 Exam Dumps - ECCouncil ECIH Questions and Answers

User Behavior Analytics (UBA) is a cybersecurity process or tool that utilizes machine learning, algorithms, and statistical analyses to detect potentially harmful activities within an organization ' s network by comparing them against established patterns of users ' behavior. It is particularly effective in identifying malicious internal actors or compromised users who may be conducting activities that deviate from their normal behavior patterns, such as accessing unauthorized data or systems, excessive file downloads, or unusual login times. UBA tools can flag these activities for further investigation, often before traditional security tools detect a breach. In contrast, SOC2 compliance reports, log forwarding, and syslog configuration are important for maintaining and auditing security standards and for infrastructure monitoring, but they are not primarily focused on detecting malicious behavior based on deviations from established user behavior patterns.

This scenario reflects misuse of system resources, a category defined in ECIH network and endpoint incident classification.

Option C is correct because unauthorized software caused excessive CPU usage and system strain, violating acceptable use policies.

Options A, B, and D do not match the behavior described.

ECIH classifies such activity as a security incident because it impacts availability, performance, and risk exposure.

A rogue-access point attack occurs when attackers or insiders install an unsecured access point within a trusted network, typically behind a firewall, to create a backdoor. This allows them to bypass network security measures and perform various malicious activities undetected. The use of any software or hardware access point to gain unauthorized access and conduct an attack characterizes a rogue-access point attack. This contrasts with password-based attacks, malware attacks, and email infections, which involve different methodologies and objectives, such as stealing credentials, distributing malicious software, or propagating through email systems, respectively.

When you receive a screenshot from Nervous Nat and go through a list of questions, check resources for information to determine the nature of the screenshot, and assess the condition of your network, you are engaging in the Detection and Analysis (or Identification) phase of Incident Response (IR). This phase is about identifying potential security incidents based on reported concerns, anomalies detected by security tools, or through the analysis of security alerts. In this scenario, despite the historical context of false positives, each report is treated seriously, requiring you to collect and analyze information to determine whether a real attack is happening. This involves verifying the validity of the incident, assessing its nature, scope, and impact, and deciding on the appropriate next steps. The detection and analysis phase is critical for determining the course of the IR process, including whether escalation is needed and what response measures should be initiated.

In the ECIH Incident Handling lifecycle, once a breach is detected, the IH & R team must focus on analysis and scoping to understand how the attack occurred, what systems were affected, and whether the attacker still has access.

Option D is correct because analyzing logs with Incident Response Automation and Orchestration (IRAO) tools allows rapid correlation of events, identification of attacker entry points, and determination of breach scope. ECIH stresses that zero-day incidents require deep forensic and timeline analysis to ensure complete containment and prevent recurrence.

Options A and C are important but depend on accurate breach understanding. Option B is premature without full incident context.

Therefore, log analysis and origin tracing is the correct primary focus.

Incident triage is the phase in the incident handling and response process where identified security incidents are analyzed, validated, categorized, and prioritized. This step is critical for determining the severity of incidents and deciding on the allocation of resources for effective response. It involves initial analysis to understand the nature of the incident, its impact, and urgency, which guides the subsequent response actions.

BinText is a lightweight text extraction tool that can be used to perform string search analysis within binary files. This functionality is crucial for incident handlers like Jason, who are tasked with analyzing memory dumps for malicious activity or indicators of compromise. By searching for specific strings or patterns that are known to be associated with malware, BinText helps in identifying potentially harmful actions that a program could perform, thus aiding in the investigation of malware incidents.

Anti-forensics techniques are designed to prevent, mislead, or interfere with the incident handling process, affecting the collection, preservation, and identification phases of the forensic investigation process. These techniques include methods to erase, encrypt, or alter information, make data recovery difficult, hide data (e.g., steganography), or otherwise obstruct forensic analysis and investigation efforts. Anti-forensics can significantly challenge the efforts of incident responders and forensic investigators in establishing the facts of a security incident or crime.

The ECIH Forensic Readiness module defines chain of custody as a documented trail showing who collected, handled, transferred, and stored evidence. Maintaining this record is essential for legal admissibility.

Option C is correct because Liam’s actions—labeling, logging, photographing, and documenting custody transfers—directly establish and maintain chain of custody. ECIH stresses that without proper chain-of-custody documentation, evidence may be challenged or dismissed in legal proceedings.

Options A, B, and D are unrelated to evidence tracking.

Thus, Liam is demonstrating proper chain-of-custody management.