Pass the ECCouncil CEH v13 312-50v13 Questions and answers with CertsForce

Just like any other service that accepts usernames and passwords for logging in, AWS users are vulnerable to social engineering attacks from attackers. fake emails, calls, or any other method of social engineering, may find yourself with an AWS users’ credentials within the hands of an attacker.

If a user only uses API keys for accessing AWS, general phishing techniques could still use to gain access to other accounts or their pc itself, where the attacker may then pull the API keys for aforementioned AWS user.

With basic opensource intelligence (OSINT), it’s usually simple to collect a list of workers of an organization that use AWS on a regular basis. This list will then be targeted with spear phishing to do and gather credentials. an easy technique may include an email that says your bill has spiked 500th within the past 24 hours, “click here for additional information”, and when they click the link, they’re forwarded to a malicious copy of the AWS login page designed to steal their credentials.

An example of such an email will be seen within the screenshot below. it’s exactly like an email that AWS would send to you if you were to exceed the free tier limits, except for a few little changes. If you clicked on any of the highlighted regions within the screenshot, you’d not be taken to the official AWS web site and you’d instead be forwarded to a pretend login page setup to steal your credentials.

These emails will get even more specific by playing a touch bit additional OSINT before causing them out. If an attacker was ready to discover your AWS account ID on-line somewhere, they could use methods we at rhino have free previously to enumerate what users and roles exist in your account with none logs contact on your side. they could use this list to more refine their target list, further as their emails to reference services they will know that you often use.

For reference, the journal post for using AWS account IDs for role enumeration will be found here and the journal post for using AWS account IDs for user enumeration will be found here.

During engagements at rhino, we find that phishing is one in all the fastest ways for us to achieve access to an AWS environment.

The Common Vulnerability Scoring System (CVSS) is a method used to supply a qualitative measure of severity for a vulnerability. CVSS consists of three metric groups: Base, Temporal, and Environmental. The Base metrics produce a score ranging from 0 to 10, which can then be modified by scoring the Temporal and Environmental metrics. A vector string represents the values of all the metrics as a block of text1

The Base metrics measure the intrinsic characteristics of a vulnerability, such as the attack vector, the attack complexity, the required privileges, the user interaction, the scope, and the impact on confidentiality, integrity, and availability. The Base score reflects the severity of a vulnerability assuming that there is no temporal information or context available1

The Temporal metrics measure the characteristics of a vulnerability that change over time, such as the exploit code maturity, the remediation level, and the report confidence. The Temporal score reflects the current state of a vulnerability and its likelihood of being exploited1

The Environmental metrics measure the characteristics of a vulnerability that depend on a specific implementation or environment, such as the security requirements, the modified base metrics, and the collateral damage potential. The Environmental score reflects the impact of a vulnerability on a particular organization or system1

In this scenario, the vulnerability has a Base score of 7, a Temporal score of 8, and an Environmental score of 5. This means that:

The vulnerability has a high severity based on its intrinsic characteristics, such as the attack vector, the attack complexity, the required privileges, the user interaction, the scope, and the impact on confidentiality, integrity, and availability. A Base score of 7 corresponds to a high severity rating according to the CVSS v3.0 specification1

The vulnerability has an increasing likelihood of exploitability over time based on its current state, such as the exploit code maturity, the remediation level, and the report confidence. A Temporal score of 8 is higher than the Base score of 7, which indicates that the vulnerability is more likely to be exploited as time passes1

The vulnerability has a medium impact on the specific environment or implementation based on the security requirements, the modified base metrics, and the collateral damage potential. An Environmental score of 5 is lower than the Base score of 7, which indicates that the vulnerability is less impactful in the particular context of the organization or system1

Therefore, the statement that best describes this scenario is: The vulnerability has an overall high severity, the likelihood of exploitability is increasing over time, and it has a medium impact in their specific environment.

The TPM is a chip that's part of your computer's motherboard — if you bought an off-the-shelf PC, it's soldered onto the motherboard. If you built your own computer, you can buy one as an add-on module if your motherboard supports it. The TPM generates encryption keys, keeping part of the key to itself

Comprehensive Explanation from CEH v13 Courseware:

CEH v13 underscores that modern multi-vector DDoS attacks—particularly SYN floods combined with Layer 7 HTTP floods—cannot be effectively mitigated by traditional firewalls, IPS devices, or local traffic filters. These systems become overwhelmed or risk blocking legitimate clients. CEH emphasizes the use of cloud-based DDoS mitigation platforms that provide traffic scrubbing, distributed filtering, rate shaping, and automatic scaling to absorb massive volumes of malicious traffic. Such services differentiate legitimate versus malicious traffic using global intelligence, behavioral analysis, and multi-layer protection strategies. Increasing bandwidth or blocking broad traffic categories is ineffective and harmful to users. An IPS cannot scale to handle volumetric attacks. Only cloud scrubbing solutions (e.g., Cloudflare, Akamai, AWS Shield Advanced) meet CEH’s recommended defenses for high-volume distributed attacks. These services ensure continuous availability and minimize collateral damage by filtering traffic upstream before it reaches the organization's infrastructure.

Key observations in the packet capture:

Repeated 0x90 values indicate a NOP sled (No Operation instructions), commonly used in buffer overflow payloads to guide execution to the malicious shellcode.

The presence of "/bin/sh" in ASCII indicates that the attacker intends to launch a shell (command-line access) on the victim’s system once the overflow is successful.

The payload likely contains shellcode that spawns a shell, giving the attacker command-line access.

From CEH v13 Official Courseware:

Module 6: Malware Threats

Module 9: Denial-of-Service

Module 5: Vulnerability Analysis

CEH v13 Study Guide states:

“A buffer overflow exploit typically involves injecting a NOP sled followed by shellcode. The string '/bin/sh' is a tell-tale sign of shell-spawning code that aims to give the attacker command access.”

Incorrect Options:

A: There's no evidence the IDS blocked the attack—only that it logged it.

B: Creating a directory would not involve a NOP sled or spawn a shell.

C: We cannot confirm success; only the intent and method are clear.

18 U.S.C. §1030, also known as the Computer Fraud and Abuse Act (CFAA), is a broad federal statute that criminalizes unauthorized access to computers and related fraudulent activities—including phishing and email scams.

From CEH v13 Official Courseware:

Module 1: Introduction to Ethical Hacking

Topic: U.S. Laws Related to Cybercrime

CEH v13 Study Guide states:

“Email-based frauds such as phishing, spoofing, and other social engineering attacks fall under the Computer Fraud and Abuse Act (18 U.S.C. §1030), which criminalizes unauthorized access and fraudulent behavior in computing systems.”

Incorrect Options:

B: Relates to credit cards and access devices.

C: Covers interference with government communication systems.

D: Covers illegal wiretapping and eavesdropping.

Comprehensive and Detailed Explanation:

The OpenSSL command-line utility s_client is used to test SSL/TLS connections.

Correct syntax:

openssl s_client -connect www.website.com:443

This command will initiate a TLS connection to port 443 on the given domain and allow you to inspect certificates, cipher suites, and server responses.

From CEH v13 Courseware:

Module 12: Cryptography → SSL/TLS Testing Tools

Patch management is that the method that helps acquire, test and install multiple patches (code changes) on existing applications and software tools on a pc, enabling systems to remain updated on existing patches and determining that patches are the suitable ones. Managing patches so becomes simple and simple.

Patch Management is usually done by software system firms as a part of their internal efforts to mend problems with the various versions of software system programs and also to assist analyze existing software system programs and discover any potential lack of security features or different upgrades.

Software patches help fix those problems that exist and are detected solely once the software’s initial unharness. Patches mostly concern security while there are some patches that concern the particular practicality of programs as well.

https://en.wikipedia.org/wiki/Subnetwork

As we can see, we have an IP address of 10.1.4.0 with a subnet mask of /23. According to the question, we need to determine which IP address will be included in the range of the last 100 IP addresses.

The available addresses for hosts start with 10.1.4.1 and end with 10.1.5.254. Now you can clearly see that the last 100 addresses include the address 10.1.5.200.

The given rule syntax is consistent with Snort, a popular open-source Intrusion Detection System (IDS). This rule alerts when any TCP traffic from any source IP and port is sent to IPs within the 192.168.100.0/24 subnet on port 21 (FTP), triggering the alert message: “FTP on the network!”

The Snort rule format is:

alert protocol source_IP source_port -> destination_IP destination_port (rule_options)

CEH v13 course materials teach this rule format under IDS/IPS configuration.

From CEH v13 Guide:

“Snort rules are used in IDS/IPS to define suspicious traffic patterns. An example rule: alert tcp any any -> 192.168.1.0/24 21 (msg: 'FTP detected') triggers an alert on FTP traffic within a subnet.”

Incorrect Options:

A/C. IP tables are used in firewalls and routers but follow a completely different syntax.

B. FTP servers do not use such alerting rules.

Reference – CEH v13 Study Guide:

Module 12: Evading IDS, Firewalls, and Honeypots

Section: Snort IDS Configuration

===========

Comprehensive and Detailed Explanation:

In Windows SID structure:

RID 500 = Default Administrator

RID 501 = Guest Account

Therefore, “-501” at the end indicates Matthew is operating as the Guest user, which has very limited privileges. To gain full administrative control, he must escalate his privileges.

From CEH v13 Courseware:

Module 6: System Hacking → Privilege Escalation Techniques

https://en.wikipedia.org/wiki/Sniffing_attack

To prevent networks from sniffing attacks, organizations and individual users should keep away from applications using insecure protocols, like basic HTTP authentication, File Transfer Protocol (FTP), and Telnet. Instead, secure protocols such as HTTPS, Secure File Transfer Protocol (SFTP), and Secure Shell (SSH) should be preferred. In case there is a necessity for using any insecure protocol in any application, all the data transmission should be encrypted. If required, VPN (Virtual Private Networks) can be used to provide secure access to users.

NOTE: I want to note that the wording "best option" is valid only for the EC-Council's exam since the other options will not help against sniffing or will only help from some specific attack vectors.

The sniffing attack surface is huge. To protect against it, you will need to implement a complex of measures at all levels of abstraction and apply controls at the physical, administrative, and technical levels. However, encryption is indeed the best option of all, even if your data is intercepted - an attacker cannot understand it.

Once initial access is obtained—especially through weak or default credentials—the CEH system hacking methodology directs the tester to proceed to privilege escalation. The objective is to elevate user-level access to administrative or system-level privileges so the attacker can perform unrestricted actions such as installing tools, modifying configurations, accessing protected files, and pivoting laterally. CEH materials emphasize using privilege escalation vulnerabilities, such as misconfigured services, kernel exploits, unpatched local privilege escalation flaws, weak file permissions, and token impersonation. A denial-of-service attack is counterproductive and does not support post-exploitation goals. XSS is a web application attack vector and unrelated to operating system privilege manipulation. Brute-forcing the root password is noisy, slow, and unnecessary when authenticated access is already established. Therefore, exploiting a known local privilege escalation vulnerability is the appropriate CEH-aligned next step.

Implementing regular firmware updates for all IoT devices is the primary recommendation to prevent DDoS attacks on the smart city project. Firmware updates can fix security vulnerabilities, patch bugs, and improve performance of the IoT devices, making them less susceptible to malware infections and botnet recruitment12. Firmware updates can also enable new security features, such as encryption, authentication, and firewall, that can protect the IoT devices from unauthorized access and data theft3. Firmware updates should be done automatically or remotely, without requiring user intervention, to ensure timely and consistent security across the IoT network4.

The other options are not as effective or feasible as firmware updates for the following reasons:

B. Deploying network intrusion detection systems (IDS) across the IoT network can help detect and alert DDoS attacks, but not prevent them. IDS can monitor network traffic and identify malicious patterns, such as high volume, spoofed IP addresses, or unusual protocols, that indicate a DDoS attack5. However, IDS cannot block or mitigate the attack, and may even be overwhelmed by the flood of traffic, resulting in false positives or missed alerts. Moreover, deploying IDS across a vast network of IoT devices can be costly, complex, and resource-intensive, as it requires dedicated hardware, software, and personnel.

C. Establishing strong, unique passwords for each IoT device can prevent unauthorized access and brute-force attacks, but not DDoS attacks. Passwords can protect the IoT devices from being compromised by hackers who try to guess or crack the default or weak credentials. However, passwords cannot prevent DDoS attacks that exploit known or unknown vulnerabilities in the IoT devices, such as buffer overflows, command injections, or protocol flaws. Moreover, establishing and managing strong, unique passwords for each IoT device can be challenging and impractical, as it requires user awareness, memory, and effort.

D. Implementing IP address whitelisting for all IoT devices can restrict network access and communication to trusted sources, but not DDoS attacks. IP address whitelisting can filter out unwanted or malicious traffic by allowing only the predefined IP addresses to connect to the IoT devices. However, IP address whitelisting cannot prevent DDoS attacks that use spoofed or legitimate IP addresses, such as reflection or amplification attacks, that bypass the whitelisting rules. Moreover, implementing IP address whitelisting for all IoT devices can be difficult and risky, as it requires constant updating, testing, and monitoring of the whitelist, and may block legitimate or emergency traffic by mistake.

Social engineering is the term used for a broad range of malicious activities accomplished through human interactions. It uses psychological manipulation to trick users into making security mistakes or giving away sensitive information.

Social engineering attacks typically involve some form of psychological manipulation, fooling otherwise unsuspecting users or employees into handing over confidential or sensitive data. Commonly, social engineering involves email or other communication that invokes urgency, fear, or similar emotions in the victim, leading the victim to promptly reveal sensitive information, click a malicious link, or open a malicious file. Because social engineering involves a human element, preventing these attacks can be tricky for enterprises.