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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Vulnerability Management | 30% | - Vulnerability assessment processes
|
| Topic 2: Reporting and Communication | 17% | - Security awareness and training
|
| Topic 3: Incident Response Management | 20% | - Incident response lifecycle
|
| Topic 4: Security Operations | 33% | - Automation and orchestration
|
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NEW QUESTION # 419
A security analyst wants to implement new monitoring controls in order to find abnormal account activity for traveling employees. Which of the following techniques would deliver the expected results?
Answer: C
Explanation:
User behavior analysis (UBA) is the most effective method for detecting abnormal account activity. UBA uses machine learning and behavioral analytics to identify patterns in how users interact with systems. If an employee suddenly logs in from an unusual location or accesses resources outside of their normal behavior, it raises an alert .
NEW QUESTION # 420
A company recently removed administrator rights from all of its end user workstations. An analyst uses CVSSv3.1 exploitability metrics to prioritize the vulnerabilities for the workstations and produces the following information:
Which of the following vulnerabilities should be prioritized for remediation?
Answer: B
Explanation:
nessie.explosion should be prioritized for remediation, as it has the highest CVSSv3.1 exploitability score of
8.6. The exploitability score is a sub-score of the CVSSv3.1 base score, which reflects the ease and technical means by which the vulnerability can be exploited. The exploitability score is calculated based on four metrics: Attack Vector, Attack Complexity, Privileges Required, and User Interaction. The higher the exploitability score, the more likely and feasible the vulnerability is to be exploited by an attacker12.
nessie.explosion has the highest exploitability score because it has the lowest values for all four metrics:
Network (AV:N), Low (AC:L), None (PR:N), and None (UI:N). This means that the vulnerability can be exploited remotely over the network, without requiring any user interaction or privileges, and with low complexity. Therefore, nessie.explosion poses the greatest threat to the end user workstations, and should be remediated first. vote.4p, sweet.bike, and great.skills have lower exploitability scores because they have higher values for some of the metrics, such as Adjacent Network (AV:A), High (AC:H), Low (PR:L), or Required (UI:R). This means that the vulnerabilities are more difficult or less likely to be exploited, as they require physical proximity, user involvement, or some privileges34. References: CVSS v3.1 Specification Document - FIRST, NVD - CVSS v3 Calculator, CVSS v3.1 User Guide - FIRST, CVSS v3.1 Examples - FIRST
NEW QUESTION # 421
An analyst has discovered the following suspicious command:
Which of the following would best describe the outcome of the command?
Answer: A
Explanation:
ThePHP script allows remote users to execute system commands via the system() function, meaning an attacker can send arbitrary commands to the server.
* Option A (Cross-site scripting - XSS)is incorrect because this script does not inject JavaScript into a webpage.
* Option B (Reverse shell)is possible if an attacker sends a crafted command, but the script itself is more of a general backdoor than a dedicated reverse shell.
* Option D (Logic bomb)is incorrect because a logic bomb is typicallytriggered by a specific event or daterather than executing arbitrary commands on demand.
Thus,C (Backdoor attempt) is the best answer, as this scriptgrants unauthorized remote command execution.
NEW QUESTION # 422
During an incident in which a user machine was compromised, an analyst recovered a binary file that potentially caused the exploitation. Which of the following techniques could be used for further analysis?
Answer: D
NEW QUESTION # 423
The management team requests monthly KPI reports on the company's cybersecurity program. Which of the following KPIs would identify how long a security threat goes unnoticed in the environment?
Answer: A
Explanation:
Mean time to detect (MTTD) is a metric that measures the average time it takes for an organization to discover or detect an incident. It is a key performance indicator in incident management and a measure of incident response capabilities. A low MTTD indicates that the organization can quickly identify security threats and minimize their impact12.
NEW QUESTION # 424
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