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| Section | Weight | Objectives |
|---|---|---|
| System Hacking | 8% | - Clearing Tracks & Logs - Maintaining Access - Privilege Escalation - Gaining Access: Password Attacks |
| Social Engineering | 6% | - Social Engineering Concepts - Identity Theft - Countermeasures & Awareness - Phishing, Pretexting, Baiting |
| Enumeration | 7% | - Enumeration Concepts - Enumeration Countermeasures - DNS, SMTP, NFS Enumeration - NetBIOS, SNMP, LDAP Enumeration - AI-Driven Enumeration |
| Footprinting and Reconnaissance | 7% | - DNS, WHOIS, Network Mapping - Reconnaissance Concepts - OSINT Techniques - Reconnaissance Countermeasures |
| Sniffing | 5% | - Packet Sniffing Concepts - MITM Attacks - Sniffing Tools & Techniques - Sniffing Countermeasures |
| Denial-of-Service | 4% | - DoS & DDoS Concepts - Defense Mechanisms - DDoS Tools - Attack Techniques & Botnets |
| Session Hijacking | 4% | - Application & Network Level Hijacking - Hijacking Techniques - Session Hijacking Concepts - Countermeasures |
| Wireless Networks | 5% | - Wireless Encryption: WEP, WPA2, WPA3 - Wireless Threats & Attacks - Wireless Hacking Tools - Security Best Practices |
| IoT & OT Security | 4% | - IoT/OT Architecture & Risks - Attacks on IoT & OT Systems - Security Controls |
| Mobile Platforms | 4% | - Android & iOS Vulnerabilities - Mobile Device Security - Mobile Attack Vectors |
| Web Server & Application Attacks | 8% | - Web Server Vulnerabilities - Web Application Attacks: XSS, CSRF - API Security Risks - SQL Injection & Command Injection - Web Security Countermeasures |
| Scanning Networks | 8% | - Network Scanning Basics - Scanning Beyond IDS/Firewall - AI-Assisted Scanning - Host & Port Discovery - Scanning Countermeasures - Service & OS Fingerprinting |
| Cloud Computing | 5% | - AWS, Azure, GCP Attacks - Cloud Security Risks - Cloud Models & Services - Cloud Security Best Practices |
| Evading IDS, Firewalls, and Honeypots | 5% | - Evasion Techniques - IDS, IPS, Firewall Technologies - Honeypot Concepts & Detection |
| Cryptography | 5% | - Encryption Concepts & Algorithms - Cryptanalysis & Attacks - Cryptography in Practice - Public Key Infrastructure |
| Vulnerability Analysis | 8% | - Vulnerability Assessment Lifecycle - Vulnerability Research & Databases - Vulnerability Classification & Scoring - Scanning & Analysis Tools |
| Malware Threats | 7% | - Malware Analysis & Countermeasures - AI-Powered Malware - APT & Fileless Malware - Malware Types: Trojans, Viruses, Worms |
| Introduction to Ethical Hacking | 5% | - Information Security Concepts - Legal and Ethical Compliance - Ethical Hacking Methodology - Cyber Kill Chain & MITRE ATT&CK |
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NEW QUESTION # 108
At a government research lab, cybersecurity officer Nikhil is compiling a vulnerability assessment report after scanning the internal subnet. As part of his documentation, he lists the IP addresses of all scanned hosts and specifies which machines are affected. He includes tables categorizing discovered vulnerabilities by type - such as outdated software, default credentials, and open ports. Which section of the vulnerability assessment report is Nikhil working on?
Answer: A
Explanation:
The section described includes detailed results of the scan, such as affected hosts, identified vulnerabilities, and their categorization. This corresponds to the findings section, where discovered issues and affected assets are documented.
NEW QUESTION # 109
During a targeted intrusion against a cloud infrastructure company in Salt Lake City, Utah, an attacker distributes a modified installation package of a legitimate network diagnostic utility widely used by employees. Before distributing the package, the attacker binds a malicious remote-access payload with the original executable so that both components are installed together.
When users launch the diagnostic tool, it performs its normal troubleshooting functions, while the hidden payload simultaneously executes in the background and establishes communication with a remote command server.
From a malware deployment perspective, what technique best describes this approach?
Answer: B
Explanation:
The correct answer is A. Wrapper.
A wrapper binds a malicious payload to a legitimate executable so that both run when the user opens the file.
The user sees the expected legitimate application, while the hidden malicious payload executes in the background.
CEH Trojan material explains that a wrapper attaches an executable application to a Trojan executable, wraps both programs into a single file, and causes the Trojan to install while the user only sees the legitimate application running . Another CEH reference defines a wrapper as a non-malicious file that binds the malicious file to propagate the Trojan and avoid detection .
Option B. Downloader is incorrect because a downloader retrieves malware from a remote location after execution.
Option C. Packer is incorrect because a packer compresses or obfuscates executable code to make detection harder.
Option D. Dropper is incorrect because a dropper is designed to deliver or install malware onto the victim system, but the key behavior here is binding a malicious payload with a legitimate executable.
Therefore, the best answer is A. Wrapper.
NEW QUESTION # 110
What kind of detection technique is being used in antivirus software that identifies malware by collecting data from multiple protected systems and instead of analyzing files locally it ' s made on the provider ' s environment?
Answer: B
Explanation:
The correct answer is D. Cloud based because the question describes an antivirus architecture where suspicious files, metadata, reputation information, and threat intelligence are collected from multiple protected endpoints and analyzed within the vendor's cloud infrastructure rather than exclusively on the local machine. In CEH malware defense concepts, cloud-based detection leverages centralized analysis engines, reputation services, machine learning models, and global threat intelligence gathered from many endpoints.
This approach enables rapid identification of emerging malware and zero-day threats because intelligence learned from one protected system can immediately benefit all other protected systems.
Heuristic-based detection focuses on identifying suspicious code characteristics and malware-like patterns.
Behavioral-based detection monitors how a program behaves on a system, such as unauthorized registry changes, process injection, or unusual network activity. Honeypot-based solutions use decoy systems to attract and study attackers. None of these specifically describe offloading analysis to the antivirus provider's environment. The key phrase in the question is that malware analysis is performed in the provider's environment using information collected from many protected systems, which is the defining characteristic of cloud-based malware detection. Therefore, option D is the most accurate CEH-aligned answer.
NEW QUESTION # 111
You have successfully comprised a server having an IP address of 10.10.0.5. You would like to enumerate all machines in the same network quickly. What is the best Nmap command you will use?
Answer: D
Explanation:
The -F option performs a fast scan by scanning fewer common ports, allowing quick enumeration of hosts on the 10.10.0.0/24 network.
NEW QUESTION # 112
A Nessus scan reports a CVSS 9.0 SSH vulnerability allowing remote code execution. What should be immediately prioritized?
Answer: C
NEW QUESTION # 113
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