Quiz 2026 CS0-004: CompTIA Cybersecurity Analyst (CySA+) Certification Exam High Hit-Rate PDF

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CompTIA CS0-004 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Incident Response and Management	24%	- Incident Investigation 1. Digital evidence and forensic considerations 2. Post-incident activities and lessons learned - Incident Response Processes 1. Incident detection, containment, eradication, and recovery 2. Incident response tools and techniques
Topic 2: Security Operations	34%	- Security Operations and Architecture 1. Logging, monitoring, and network architecture 2. Indicators of malicious activity and analysis - Threat Intelligence and Hunting 1. Threat intelligence concepts and sources 2. Threat hunting, detection, and response tools
Topic 3: Vulnerability Management	26%	- Vulnerability Response 1. Security controls and mitigation 2. Risk prioritization and remediation - Vulnerability Assessment 1. Scanning methods and vulnerability identification 2. Vulnerability analysis and validation
Topic 4: Reporting and Communication	16%	- Reporting 1. Metrics, trends, and recommendations 2. Vulnerability and incident reports - Communication 1. Technical and executive-level communication 2. Stakeholder communication and escalation

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CompTIA Cybersecurity Analyst (CySA+) Certification Exam Sample Questions (Q84-Q89):

NEW QUESTION # 84
A Chief Information Security Officer (CISO) evaluates a threat heat map and notices a substantial increase in custom scanning and enumeration activities. The CISO wants to gather as much information as possible about the activities targeting the company to help prioritize mitigations.
Which of the following solutions is the best way to accomplish this goal?

A. Subscribing to information-sharing and threat intelligence reports for the industry
B. Implementing a web application firewall in front of all applications and having it log attacks
C. Leveraging canary tokens on all production systems to detect valid intrusion attempts
D. Configuring a honeypot in a separate environment to gather attacker techniques

Answer: D

Explanation:
A honeypot safely attracts attackers and records detailed, organization-specific scanning, enumeration, and exploitation behavior without exposing production systems.

NEW QUESTION # 85
Due to some incidents involving non-authorized devices, a company wants to implement a solution that only allows access to its LAN and Wi-Fi if certain policies are matched. Which of the following is the best solution to implement?

A. NAC
B. NGFW
C. IPS
D. SDN

Answer: A

Explanation:
Network Access Control (NAC) enforces security policies before allowing devices to connect to wired or wireless networks. It can verify device compliance, authentication status, and other security requirements, ensuring that only authorized and compliant devices are granted access to the LAN and Wi-Fi network.

NEW QUESTION # 86
A Chief Information Security Officer (CISO) is notified of an ongoing incident. Which of the following explains why the CISO instructs the Chief Executive Officer not to discuss the incident over email?

A. The security team discovered a vulnerability in the Short Message Service email gateway.
B. The email system may be compromised.
C. The CISO has not notified the public relations team of the incident.
D. Emails are not encrypted in transit.

Answer: B

Explanation:
During an active incident, attackers may be monitoring a compromised email system. Incident communications should therefore use a secure, out-of-band channel.

NEW QUESTION # 87
A security analyst uses a full pcap solution to extract all traffic from the last two days associated with the 10.213.4.27 file server. This file server is under investigation due to concerns about potential data exfiltration using Domain Name System (DNS) traffic. Which of the following commands should the analyst use to extract any potentially leaked data from the suspicious.pcap file?

A. tcpdump -r suspicious.pcap port 53 and host 10.213.4.27
B. zeek -r suspicious.pcap ; grep 10.213.4.27 file.log
C. strings suspicious.pcap | grep 10.213.4.27
D. snort -r suspicious.pcap ; grep eve.log 10.213.4.27

Answer: A

Explanation:
This command reads the packet capture and filters traffic involving the file server on DNS port 53, allowing the analyst to inspect potential DNS-based data exfiltration.

NEW QUESTION # 88
An analyst uses an AI platform to help correlate events. The AI output contains events that did not happen.
This results in inaccurate correlations.
Which of the following best describes what has occurred?

A. Model poisoning
B. Malicious prompts
C. Hallucinations
D. Data exposure

Answer: C

Explanation:
The scenario describes an AI hallucination , commonly termed confabulation in formal AI risk-management literature. The defining characteristic is that the model produces information that appears plausible but is factually incorrect or unsupported. Here, the AI system introduces events that never occurred, contaminating the event-correlation process and potentially causing analysts to reach incorrect conclusions.
NIST's Generative AI Profile identifies confabulation as the production of confidently stated but erroneous or false content and treats it as an AI risk that requires verification and monitoring. NIST cybersecurity guidance also recognizes hallucination and confabulation as risks to information accuracy when AI is incorporated into cybersecurity workflows.
Data exposure would involve unauthorized disclosure of confidential or sensitive information. A malicious prompt involves intentionally crafted input designed to influence model behavior or bypass restrictions.
Model poisoning occurs when an adversary manipulates training or model-related data to corrupt the system's behavior. None of these conditions is required in the scenario; the critical evidence is fabrication of nonexistent events.
Security analysts therefore must treat AI-generated correlation as analytical assistance rather than unquestioned evidence and validate important conclusions against authoritative logs and telemetry.
Study Guide Reference: Security Operations # Artificial Intelligence # AI Risks # Hallucinations # Data Exposure # Malicious Prompts # Model Poisoning # Human Validation.

NEW QUESTION # 89
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