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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Enumeration | 7% | - AI-Driven Enumeration - Enumeration Countermeasures - NetBIOS, SNMP, LDAP Enumeration - DNS, SMTP, NFS Enumeration - Enumeration Concepts |
| Topic 2: Footprinting and Reconnaissance | 7% | - DNS, WHOIS, Network Mapping - OSINT Techniques - Reconnaissance Countermeasures - Reconnaissance Concepts |
| Topic 3: Sniffing | 5% | - Sniffing Countermeasures - MITM Attacks - Packet Sniffing Concepts - Sniffing Tools & Techniques |
| Topic 4: Social Engineering | 6% | - Social Engineering Concepts - Identity Theft - Phishing, Pretexting, Baiting - Countermeasures & Awareness |
| Topic 5: Scanning Networks | 8% | - Scanning Countermeasures - AI-Assisted Scanning - Scanning Beyond IDS/Firewall - Host & Port Discovery - Service & OS Fingerprinting - Network Scanning Basics |
| Topic 6: Session Hijacking | 4% | - Session Hijacking Concepts - Application & Network Level Hijacking - Countermeasures - Hijacking Techniques |
| Topic 7: Web Server & Application Attacks | 8% | - Web Server Vulnerabilities - API Security Risks - SQL Injection & Command Injection - Web Security Countermeasures - Web Application Attacks: XSS, CSRF |
| Topic 8: Cryptography | 5% | - Encryption Concepts & Algorithms - Cryptanalysis & Attacks - Public Key Infrastructure - Cryptography in Practice |
| Topic 9: Wireless Networks | 5% | - Security Best Practices - Wireless Encryption: WEP, WPA2, WPA3 - Wireless Threats & Attacks - Wireless Hacking Tools |
| Topic 10: Denial-of-Service | 4% | - Attack Techniques & Botnets - DDoS Tools - Defense Mechanisms - DoS & DDoS Concepts |
| Topic 11: IoT & OT Security | 4% | - Attacks on IoT & OT Systems - IoT/OT Architecture & Risks - Security Controls |
| Topic 12: Introduction to Ethical Hacking | 5% | - Legal and Ethical Compliance - Cyber Kill Chain & MITRE ATT&CK - Ethical Hacking Methodology - Information Security Concepts |
| Topic 13: Cloud Computing | 5% | - Cloud Security Best Practices - Cloud Security Risks - AWS, Azure, GCP Attacks - Cloud Models & Services |
| Topic 14: Evading IDS, Firewalls, and Honeypots | 5% | - Evasion Techniques - Honeypot Concepts & Detection - IDS, IPS, Firewall Technologies |
| Topic 15: Mobile Platforms | 4% | - Android & iOS Vulnerabilities - Mobile Device Security - Mobile Attack Vectors |
| Topic 16: System Hacking | 8% | - Maintaining Access - Privilege Escalation - Gaining Access: Password Attacks - Clearing Tracks & Logs |
| Topic 17: Malware Threats | 7% | - APT & Fileless Malware - Malware Types: Trojans, Viruses, Worms - AI-Powered Malware - Malware Analysis & Countermeasures |
| Topic 18: Vulnerability Analysis | 8% | - Vulnerability Research & Databases - Vulnerability Classification & Scoring - Scanning & Analysis Tools - Vulnerability Assessment Lifecycle |
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NEW QUESTION # 659
MidWest BioAnalytics, a pharmaceutical research firm in Columbus, Ohio, authorizes a controlled adversarial simulation to assess the resilience of its internal web-based inventory management platform.
During the exercise, administrators observe that several active client connections briefly lose synchronization, and unexpected command patterns appear within system transaction logs.
The irregularities are subtle and become apparent only after reviewing stored network captures. Executive leadership requests a solution that can maintain ongoing visibility into network exchanges and highlight activity that diverges from typical communication behavior across the organization's infrastructure.
Which approach best satisfies this requirement?
Answer: A,B,C,D,E
NEW QUESTION # 660
As a cybersecurity professional in a growing organization, you are tasked with conducting comprehensive reconnaissance of your own company's digital presence. In addition to using tools like WHOIS, DNS analysis, and search engines, you are also considering investigating the Deep Web. Which of the following justifications best supports your idea to explore the Deep Web for potential risks related to your organization's information?
Answer: D
Explanation:
The Deep Web consists of content not indexed by standard search engines, making it a potential location for exposed or forgotten organizational data that would not be discovered through conventional reconnaissance methods.
NEW QUESTION # 661
You are part of a red team hired to assess the cybersecurity posture of a large retail chain headquartered in New York. The client wants to know whether their defenses can anticipate future attack patterns before they occur. To meet this objective, your team deploys an AI-enabled platform that analyzes previous breaches and anomaly data to forecast potential attack vectors. Which benefit of AI-driven ethical hacking is most critical in this case?
Answer: D
Explanation:
The correct answer is B. Predictive analysis because the client's primary objective is to anticipate future attack patterns before they occur, and the described AI-enabled platform is explicitly being used to forecast potential attack vectors based on historical breaches and anomaly data. In CEH-aligned coverage of modern security capabilities, AI-driven approaches add value by learning from large datasets (logs, alerts, incidents, threat intelligence, and observed attacker behaviors) to identify trends, detect weak signals, and predict the most likely next steps an adversary may take. This directly supports proactive defense planning rather than purely reactive response.
In this scenario, the platform ingests "previous breaches and anomaly data" and produces forward-looking insights. That is the essence of predictive analysis: applying machine learning/analytics to estimate where attacks may emerge (for example, which assets are most at risk, which tactics are trending, what misconfigurations correlate with compromise, or which sequences of events often precede an intrusion). This helps defenders prioritize controls, patching, monitoring, and hardening to disrupt the projected attack paths ahead of time. It also aligns with the retail client's desire to know whether their defenses can "anticipate" attacks, not merely document them after the fact.
Why the other options are less correct: Scalability is a benefit of AI (automating large-scale analysis), but it does not specifically address forecasting future attack vectors. Enhanced reporting improves how findings are communicated, but it is not the key capability described. Simulation and testing refers to running scenarios or automated testing in environments to measure resilience; that can be AI-assisted, but the prompt focuses on analyzing historical and anomaly data to predict likely attacks, which maps most directly to predictive analysis.
Therefore, the most critical benefit of AI-driven ethical hacking in this case is predictive analysis.
NEW QUESTION # 662
During an internal audit at a financial services firm in Mumbai, ethical hacker Meera was tasked with assessing lateral movement risks within the Windows-based domain environment. While monitoring internal network traffic, she noticed a strange broadcast from a workstation trying to resolve a non-existent host. Suspecting protocol-level weakness, she responded swiftly using a pre-configured system. A few minutes later, she captured NTLMv2 hashes from several authenticated sessions across multiple departments. Later, her team successfully cracked one of the hashes offline and used the credentials to gain access to a sensitive internal reporting server.
Which type of attack did Meera most likely execute?
Answer: A
Explanation:
The attack involves responding to broadcast name resolution requests for non-existent hosts and capturing NTLMv2 hashes from authentication attempts. This behavior is characteristic of LLMNR/NBT-NS poisoning, where an attacker exploits name resolution protocols to intercept and capture credentials.
NEW QUESTION # 663
A competing technology firm begins releasing products that closely mirror the design, pricing strategy, and feature roadmap of ApexDynamics Inc. An internal review reveals that detailed information about ApexDynamics's upcoming initiatives had been gradually collected through publicly available sources and external disclosures before product launch. Which footprinting- related threat does this scenario best represent?
Answer: C
Explanation:
The organization suffers competitive disadvantage and revenue impact because publicly exposed information about its plans allowed a competitor to replicate its strategy. This outcome represents business loss resulting from footprinting activities.
NEW QUESTION # 664
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