ECCouncil 312-50v13 - Certified Ethical Hacker Exam (CEH v13 AI)

The correct answer is A. --spoof-mac 0.

Nmap supports MAC address spoofing as a firewall-evasion and scan-obfuscation option. The available reference material lists Nmap firewall evasion options and identifies --spoof-mac mac as the option used to spoof the MAC address .

The value 0 tells Nmap to generate a random MAC address. Because the question states that the recorded hardware address changes automatically each time, the random MAC option is the correct match.

Option B. --spoof-mac Dell is incorrect because this selects a MAC address associated with a specific vendor prefix, not the fully random behavior described.

Option C. --spoof-mac 00:01:02:25:56:AE is incorrect because it uses a fixed MAC address. Repeated scans would show the same spoofed address, not a new one each time.

Option D. --spoof-mac Dell 10.10.1.11 is incorrect because it is not the correct Nmap option format for this behavior.

Therefore, the best answer is A. --spoof-mac 0.

The correct answer is C. Ping method by sending packets with an incorrect MAC address.

The scenario describes testing whether a network card is processing packets not intended for it. That is exactly what promiscuous mode does. In promiscuous mode, a NIC accepts frames even when they are not addressed to its own MAC address.

CEH sniffing material explains that the Ping Method detects a sniffer by sending a ping request to the suspect IP address with a spoofed MAC address. If the NIC is not in promiscuous mode, it will not respond. If the suspect system is running a sniffer, it may respond to the packet .

Option A. DNS method is incorrect because the scenario does not describe reverse DNS lookup behavior.

Option B. NSE script can be used for promiscuous-mode detection in some cases, but the question specifically describes crafted packets used to test acceptance of traffic not addressed to the host.

Option D. ARP method is another sniffer detection method, but it relies on non-broadcast ARP cache behavior. The scenario’s wording most directly matches the ping method with an incorrect or spoofed MAC address.

Therefore, the best answer is C. Ping method by sending packets with an incorrect MAC address.

CEH v13 identifies ARP spoofing/poisoning as a primary MitM technique in local networks. In such attacks, a single IP address maps to multiple MAC addresses, indicating ARP table manipulation.

This anomaly allows attackers to intercept traffic between victims and gateways. Increased traffic or DNS activity may occur but are not definitive indicators. Thus, IP-to-MAC inconsistencies are the most reliable confirmation of MitM activity.

The correct answer is A, Long dwell time. In CEH security operations and threat-detection concepts, an Advanced Persistent Threat, or APT, is characterized by advanced techniques, persistence, stealth, and a long-term objective. CEH-related material describes an APT as a continuous process of stealing information, often focused on private organizations or political motives, and explains that “persistent” involves continuous monitoring and data fetching from a target. It also lists APT criteria such as timeliness, meaning time spent probing and accessing the target, and risk tolerance, meaning the ability to remain undetected. Long dwell time means the attacker remains inside the environment for an extended period before detection, often performing internal reconnaissance, privilege escalation, lateral movement, credential theft, persistence, and quiet data exfiltration. Malware spam is usually broad and noisy, a one-time exploit lacks persistence, and brute force is only a technique. Therefore, long dwell time best indicates APT behavior.

CEH v13 explains that the Deep Web contains content not indexed by search engines, including exposed databases, misconfigured portals, leaked credentials, and internal documents.

This makes it a critical area to assess unintended data exposure. The Deep Web is not primarily for attacker profiling or insider detection.

Thus, Option D is correct.

The symptoms point to a rogue DHCP scenario, which CEH materials commonly describe as a method attackers use to disrupt networks or perform man-in-the-middle attacks. If an unauthorized device begins answering DHCP requests faster than the legitimate DHCP server, endpoints may receive incorrect IP settings such as a fake default gateway or DNS server. This causes loss of connectivity to internal applications like a CRM system and can silently redirect traffic through an attacker-controlled host. The question explicitly mentions “irregular IP assignment attempts” tied to an unfamiliar device, which aligns strongly with rogue DHCP behavior rather than ARP-only manipulation or simple MAC-limit violations.

DHCP snooping is a Layer 2 security feature on Cisco switches that filters untrusted DHCP messages and allows only authorized DHCP servers on trusted ports. When enabled for the affected VLAN, the switch will drop DHCP offers and acknowledgments arriving on untrusted access ports, stopping the rogue device from leasing addresses. Option A, ip dhcp snooping vlan 10, is the command that applies DHCP snooping protection to the specific VLAN experiencing the issue, which matches the “subnet logs” and the localized impact described.

Option B, Dynamic ARP Inspection, primarily mitigates ARP spoofing and relies on DHCP snooping bindings, but it does not directly stop rogue DHCP leasing. Option D, port security, can limit MAC addresses but does not specifically block DHCP server behavior. Option C enables the feature globally but does not target the VLAN; the VLAN-specific activation in A best matches the scenario and the immediate restoration of correct addressing and connectivity.

Comprehensive Explanation from CEH v13 Courseware:

CEH v13 explains that TOCTOU (Time-of-Check Time-of-Use) vulnerabilities arise when a system checks a condition (such as file permissions) and then later uses the resource based on that assumption. If there is even a tiny gap between the validation and the actual use, attackers can exploit this race condition by replacing or modifying the resource after validation but before execution. This is common in file-handling operations involving temporary files, symbolic links, or shared directories. CEH emphasizes that TOCTOU attacks often lead to privilege escalation, unauthorized execution, or tampering with data because the system trusts the earlier validation step. The attacker swaps the file at precisely the right moment, taking advantage of a race window. The other options—certificate validation, integer overflow, and null pointer dereference—do not involve timing-based race conditions. The scenario exactly matches CEH’s description of TOCTOU exploitation, where attackers manipulate file access in the interval between validation and execution.

The correct answer is B. Launching SQL Injection Attacks because the scenario describes moving beyond merely locating inputs or detecting error behavior and into actively sending injection payloads that successfully alter query logic and change returned results. In a typical CEH-aligned SQL injection workflow, testers begin by identifying where user-controlled input enters the application (forms, URL parameters, cookies, headers), then perform basic tests to detect whether inputs affect backend SQL processing. Once a suspected injection point is found, the next step is to launch SQL injection attempts using crafted inputs designed to manipulate the query and demonstrate impact.

In this case, you “craft and submit multiple malicious inputs,” and one payload “successfully manipulates the backend query,” causing the application to return “additional appointment data that was not intended to be displayed.” That outcome is a clear indicator that exploitation is underway: the injection is not hypothetical—it is functioning and changing the application’s behavior in a way that reveals unauthorized data. This is characteristic of executing an SQL injection attack (in-band exploitation), such as using boolean logic manipulation (e.g., conditions that expand result sets) or other query-altering techniques. The emphasis is on the successful manipulation and unauthorized data exposure, which aligns with the attack execution phase.

Why the other options are less correct: Identifying Data Entry Paths would be earlier, when you locate the patient search field as a candidate parameter. Information Gathering and Vulnerability Detection generally refers to discovering and confirming the presence of weaknesses (often via initial probes, errors, or abnormal responses) rather than a confirmed payload that already returns unauthorized data. Database Enumeration is typically the follow-on step once exploitation is confirmed, where the tester extracts metadata such as database names, tables, columns, users, and versions. Here, you are demonstrating the injection’s ability to retrieve extra records, which is the exploitation/attack-launch stage, not full enumeration yet.

Therefore, the step being performed is Launching SQL Injection Attacks.

In CEH v13 Cloud Computing, serverless architectures introduce unique security challenges, particularly around Function-as-a-Service (FaaS) permissions. When a serverless function is compromised through an insecure third-party API, the damage depends largely on what the function is allowed to do.

Implementing function-level permission models and enforcing the principle of least privilege ensures that even if a function is exploited, its ability to execute malicious actions is strictly limited. CEH v13 strongly emphasizes granular IAM controls in serverless environments.

While cloud-native security platforms (Option A) and CASBs (Option C) provide visibility and governance, they do not directly prevent excessive permissions. Regular patching (Option D) is important but does not mitigate permission abuse.

CEH v13 identifies least privilege as the single most critical control in preventing serverless abuse and privilege escalation. Therefore, Option B is the correct answer.

The CEH IDS/IPS Evasion module describes packet fragmentation as a common evasion technique used to bypass signature-based detection.

Option B is correct.

Other options represent different attack categories.

CEH highlights reassembly normalization as a countermeasure.

According to the CEH Cryptography module, strong symmetric encryption algorithms are essential for protecting data confidentiality and obscuring traffic content.

AES (Advanced Encryption Standard) is the industry-standard symmetric encryption algorithm approved by NIST and recommended by CEH for encrypting data in transit and at rest. AES provides strong resistance against cryptanalysis and prevents attackers from deriving meaningful information from encrypted traffic.

Option D is correct because AES is efficient, secure, and widely implemented.

Option A (HMAC) provides integrity and authentication, not encryption.

Option B (RSA) is computationally expensive and not suitable for bulk traffic encryption.

Option C (DES) is deprecated due to weak key length.

CEH materials clearly recommend AES over legacy algorithms.

Fingerprinting the running service is the most appropriate technique because the strongest indicator in the scenario is inconsistent protocol behavior and error responses that do not match a legitimate production database service. In CEH reconnaissance guidance, honeypots and decoy systems often emulate common services but may implement only partial protocol stacks or simplified responses. This can lead to anomalies such as incorrect banner strings, malformed or generic error messages, unsupported command handling, unusual protocol negotiation, or responses that do not align with the claimed software version. By fingerprinting, Mia compares observed behavior against expected behavior for the genuine service, including version-specific quirks, command sets, response codes, and timing patterns for particular requests.

In practice, service fingerprinting involves interacting with the service using legitimate and edge-case requests, validating banners and headers, and correlating results with known signatures from real implementations. If the server claims to be a specific database or application service but reacts in ways that real deployments would not, it suggests emulation, instrumentation, or deception typical of honeypots designed to log attacker activity.

Analyzing response time can help, because some honeypots respond too quickly or with uniform timing, but timing alone is less definitive than protocol inconsistencies. MAC address analysis is not reliable for identifying honeypots and is often not visible beyond the local segment. Analyzing system configuration and metadata usually requires deeper access than reconnaissance and is not the primary method when the clue is protocol-level mismatch. Therefore, fingerprinting the running service best fits the observed symptoms.

QUBB ESTION NO: 25 [Mobile Platform and IoT Hacking]

Javier Ruiz from CyberFortress Solutions is tasked with auditing the mobile security practices of Apex Financial Services, a financial firm in Houston, Texas. During a covert penetration test, Javier targets employees ' personal smartphones used to access corporate financial systems. He exploits a vulnerability by installing a malicious app that bypasses access controls, granting him unauthorized entry to sensitive financial data because the devices lack a specific security measure to restrict app access. Based on this vulnerability, which BYOD security guideline is most likely missing in Apex Financial Services ' policy?

A. Review permissions requested by apps before installing them

B. Set passwords for apps to restrict others from accessing them

C. Enforce automatic device locking or implement biometric authentication

D. Use encryption mechanisms to store data

Answer: A

The most likely missing BYOD guideline is reviewing application permissions before installation. In CEH mobile security guidance, a major risk in BYOD environments is the introduction of untrusted or malicious applications that abuse the mobile permission model to access corporate data, intercept authentication tokens, read storage, capture keystrokes via accessibility services, or communicate externally. When users install apps without scrutinizing requested permissions, they may unknowingly grant excessive privileges that enable data theft or access-control bypass, especially if the app leverages OS weaknesses or misconfigurations.

The scenario states Javier “installs a malicious app that bypasses access controls” and gains access to sensitive financial data because devices “lack a specific security measure to restrict app access.” This maps directly to a policy gap around controlling and validating apps and their permission requests. CEH emphasizes that organizations should reduce attack surface by limiting app privileges, avoiding sideloading from untrusted sources, and enforcing least privilege through user awareness and enterprise controls such as MDM application allowlisting and permission governance. Reviewing permissions is the user-facing guideline that prevents employees from granting dangerous access (for example, SMS, storage, contacts, accessibility, device admin, or VPN configuration permissions) that can enable credential theft or unauthorized data access.

Option B adds an extra layer for local access but does not stop a malicious app with granted permissions from accessing corporate data. Option C helps if a device is physically stolen, but it does not prevent malicious apps already running under the user context. Option D protects data at rest, yet a malicious app can still exfiltrate data once it is decrypted and accessed by the user session. Therefore, permission review is the most directly relevant missing BYOD guideline.

The weakness described is a classic online password-guessing condition: the application permits unlimited authentication attempts without any throttling, lockout, or challenge mechanism. In CEH guidance, this exposure enables brute-force attacks and automated credential stuffing, where attackers rapidly test many passwords or reused credential pairs until successful. A practical and commonly recommended control at the web application layer is adding CAPTCHA challenges to the login workflow, especially after a small number of failed attempts or when anomalous behavior is detected. CAPTCHA increases the cost of automation by forcing human interaction, directly disrupting high-speed scripted guessing against the admin portal.

While implementing MFA is an excellent additional safeguard and is strongly encouraged for privileged access, the question asks for the best countermeasure to address the specific issue of unlimited rapid attempts. CAPTCHA is a direct mitigation for automated login abuse, and CEH commonly pairs it with rate limiting, progressive delays, and account lockout policies. Periodic password changes do not prevent an attacker from guessing a password today, and CEH materials note that forced rotation can even reduce security if it drives predictable password patterns. Strong password hashing such as bcrypt, scrypt, or Argon2 is critical for protecting stored passwords if a database is compromised, but it does not stop online guessing against the login form itself. Therefore, the most fitting countermeasure for the identified vulnerability is using CAPTCHA challenges on login and registration pages, ideally combined with throttling and lockout for stronger defense in depth

CEH methodology stresses prioritization based on risk, exploitability, and business impact. High-severity vulnerabilities—especially those related to outdated or unsupported server software—are frequently associated with known, publicly documented exploits. The proper next step after identifying such vulnerabilities is to confirm exploitability safely, typically by researching available exploit code, validating version-specific weaknesses, and determining whether the vulnerability can be successfully leveraged under the defined scope of engagement. CEH highlights that exploitation attempts must be evidence-driven, not arbitrary, and focusing on high-risk vulnerabilities allows testers to demonstrate meaningful security impacts. Brute-forcing (Option A) is unnecessary and high-noise. Ignoring or deprioritizing the high-risk finding (Options B and C) contradicts CEH risk-based assessment principles. Therefore, verifying exploitability of the high-risk vulnerability is the correct step.