ECCouncil 312-85 Exam Dumps & Practice Test Questions

Question 1:

Daniel is a proficient hacker who targets sensitive data such as social security numbers, personally identifiable information (PII), and credit card details. After successfully stealing this information, he sells it on the black market for profit. 

Based on Daniel’s actions and objectives, what category of threat actor does he belong to?

A. Industrial espionage agents
B. Government-backed hackers
C. Internal threat actors
D. Organized cybercriminals

Answer: D

Explanation:

Daniel’s behavior aligns closely with that of organized cybercriminals. These threat actors are typically part of coordinated groups or individuals who carry out cyber-attacks with the primary aim of financial gain. Their activities usually involve stealing valuable data such as personal identity information, credit card numbers, or confidential business data, which they then sell illegally on the black market.

Unlike other types of hackers motivated by political or ideological reasons—such as government-backed (state-sponsored) hackers who focus on espionage or sabotage—organized cybercriminals are financially motivated. Daniel’s goal of monetizing stolen data highlights this distinction clearly.

Let’s break down the other options:

• Industrial espionage agents (Option A) focus on stealing proprietary business secrets or trade secrets to benefit competitors or foreign companies. Daniel’s focus on personal data rather than corporate intellectual property means this does not fit his profile.

• Government-backed hackers (Option B) usually operate under the direction or support of nation-states for political or strategic advantage. Since Daniel acts for personal financial gain without political motives, this category is incorrect.

• Internal threat actors (Option C) are insiders—employees, contractors, or partners with legitimate access—who misuse their privileges to harm the organization. Daniel is described as an external attacker, so he does not fall into this group.

Organized hackers are often highly skilled and methodical, sometimes working within large cybercriminal networks. They leverage sophisticated hacking tools and techniques to infiltrate systems, steal data, and profit from illicit activities. Daniel’s profile as a motivated, skilled hacker profiting from stolen data fits the organized hacker archetype perfectly.

Question 2:

An attacker is using a network of compromised computers (a botnet) to hide the real locations of phishing websites and malware servers. By frequently changing the IP addresses associated with a single domain name, the attacker makes it challenging for security defenses to block these malicious sites. 

What technique is the attacker employing?

A. DNS Zone Transfer
B. Dynamic DNS
C. DNS Querying
D. Fast-Flux DNS

Answer: D

Explanation:

The technique being described is known as Fast-Flux DNS. This method involves frequently changing the IP addresses linked to a single domain name, sometimes multiple times within minutes or seconds. The goal is to conceal the actual servers hosting phishing pages or malware by rotating through a pool of compromised machines, making it difficult for defenders to block or track the malicious infrastructure.

Fast-Flux exploits the way the Domain Name System (DNS) resolves domain names to IP addresses. Each DNS lookup returns a different IP, often pointing to infected computers that act as proxies or relays, forming a constantly shifting network layer. This dynamic behavior protects the attacker’s real servers from detection, takedown, or blocking by security teams.

Looking at the other choices:

• DNS Zone Transfer (Option A) is a legitimate administrative function used to replicate DNS databases between servers. Attackers may misuse it to gather intelligence on network structure but it does not hide malicious servers or rotate IP addresses.

• Dynamic DNS (Option B) is a service that updates DNS records when an IP address changes, commonly used by legitimate users with changing IPs. While it involves changing IP addresses, it is not designed for malicious obfuscation like Fast-Flux.

• DNS Querying (Option C) simply refers to the process of requesting DNS information and is unrelated to hiding or rotating IP addresses.

In summary, Fast-Flux DNS is a sophisticated evasion tactic that allows attackers to keep their malicious domains alive and harder to block by rapidly changing the IP addresses linked to them, leveraging a botnet of infected hosts as proxies.

Question 3:

Kathy needs to share sensitive threat intelligence securely and wants to control who can access it. 

Using the Traffic Light Protocol (TLP), which color indicates that the information should be shared only within a particular trusted community, restricting its distribution to that specific group?

A. Red
B. White
C. Green
D. Amber

Answer: C

Explanation:

The Traffic Light Protocol (TLP) is a widely adopted classification system in cybersecurity used to manage how sensitive information—especially threat intelligence—is shared among various parties. It assigns colors to information to clearly communicate how widely the information can be disseminated, preventing accidental exposure and ensuring sensitive data reaches only the intended recipients.

Each TLP color carries specific sharing guidelines:

• TLP Red represents the highest sensitivity level. Information marked red is strictly confidential and should only be shared with named individuals who absolutely need to know. It cannot be shared outside this limited group and is not to be disclosed to any third parties.

• TLP Amber indicates that information can be shared within a particular organization or a defined community but should not leave that group. This provides some sharing flexibility while maintaining control over the information’s distribution.

• TLP Green signifies that the information is shareable within a trusted community, such as a specific sector or alliance, but not beyond. It restricts dissemination outside this circle, ensuring the information is accessible to relevant partners while maintaining confidentiality.

• TLP White is the least restrictive classification, meaning the information is suitable for public distribution and can be freely shared without limitation.

In Kathy’s scenario, since the information should only be shared with a specific community (not publicly or across all organizational boundaries), TLP Green is the correct choice. It strikes the right balance by allowing collaboration within trusted groups while preventing widespread exposure. This helps protect sensitive intelligence while enabling effective information sharing among relevant stakeholders.

Question 4:

Moses is investigating the possibility of fraudulent websites using URLs similar to his company’s official domain. 

To help identify such sites using Google’s advanced search features, which search operator would be most effective for finding websites related or similar to the official InfoTec domain?

A. related
B. info
C. link
D. cache

Answer: A

Explanation:

In cybersecurity threat intelligence, detecting fake or phishing websites that impersonate a legitimate company’s domain is crucial for protecting an organization’s reputation and preventing fraud. Google’s advanced search operators are powerful tools that allow analysts to perform targeted searches and uncover related or suspicious domains.

The related: operator helps users find websites that Google deems similar or related to a specified URL. For Moses, using related: www.infothech.org will return websites that share similarities with the official InfoTec domain. These results can reveal spoofed, fraudulent, or phishing sites designed to mimic the company’s legitimate presence, helping Moses identify potential threats quickly.

By contrast, other options are less suited for this goal:

• info: provides metadata about a website, such as cached pages or indexed information, but it doesn’t reveal similar or related domains.

• link: lists web pages that contain hyperlinks pointing to the specified URL, useful for backlink analysis but not for detecting fake or lookalike sites.

• cache: shows the cached snapshot of a website page and is useful for seeing how a page looked at a certain time, but it does not help find related or fraudulent sites.

Therefore, the related: operator is the best tool to discover websites that might be maliciously imitating InfoTec’s official domain. Using it allows Moses to gather intelligence on potential threats posed by fraudulent websites and take necessary actions to mitigate risks.

Question 5:

A group of threat intelligence analysts is examining a malware sample, each formulating different hypotheses supported by their findings on the malware’s behavior. 

To identify the most accurate and well-supported theory among these varying hypotheses, which analytical method should the threat intelligence manager use?

A. Threat modeling
B. Application decomposition and analysis (ADA)
C. Analysis of Competing Hypotheses (ACH)
D. Automated technical analysis

Answer: C

Explanation:

In situations where multiple analysts propose different explanations for a single phenomenon—such as the behavior of malware—having a structured approach to evaluate and compare these hypotheses is vital. The method best suited for this is Analysis of Competing Hypotheses (ACH).

ACH is a rigorous analytical process that helps eliminate cognitive biases and objectively assesses the strength of evidence for and against each hypothesis. Rather than focusing on confirming a favored theory, ACH encourages analysts to consider all hypotheses and evidence impartially, increasing the likelihood of reaching the most reliable conclusion.

The ACH process begins by listing all competing hypotheses—each representing a plausible explanation for the malware’s behavior. Then, all relevant evidence is gathered, organized, and evaluated against each hypothesis. This includes behavioral data, command and control communications, and contextual intelligence such as historical patterns or known threat actors.

Each piece of evidence is analyzed for whether it supports or contradicts the hypotheses, helping analysts systematically weigh the validity of each theory. By doing this, hypotheses that are inconsistent with critical evidence can be discarded or downgraded in plausibility. Ultimately, the hypothesis with the least contradiction and strongest evidentiary support emerges as the most credible explanation.

The other options, while useful in cybersecurity, do not fit this scenario as well:

• Threat modeling is about identifying potential attack paths and vulnerabilities, not comparing hypotheses.

• Application decomposition and analysis (ADA) focuses on dissecting the malware’s components, not evaluating competing theories.

• Automated technical analysis involves using tools to quickly identify malware signatures or behaviors but lacks the critical, hypothesis-driven evaluation ACH provides.

Thus, ACH is the optimal method to reach a consistent, evidence-based conclusion when multiple competing malware theories exist.

Question 6:

Miley is an analyst managing vast amounts of unstructured data. To streamline storage and facilitate sharing, she applies methods to filter, label, and organize the data, extracting relevant structured information from the bulk. 

Which data management technique is Miley employing?

A. Sandboxing
B. Normalization
C. Data visualization
D. Convenience sampling

Answer: B

Explanation:

Miley’s objective is to reduce the volume of unstructured data by organizing and structuring it, making it easier to store, manage, and share. The process she is using—filtering, tagging, and queuing data to isolate relevant information—corresponds to the data management technique known as normalization.

Normalization involves organizing data to reduce redundancy and improve consistency by converting unstructured or poorly structured data into a standardized format. This is essential when handling large datasets because it simplifies analysis, storage, and sharing by ensuring that data adheres to predefined rules and formats.

The filtering step Miley uses removes irrelevant or duplicate information. Tagging helps classify data elements with metadata to facilitate easier searching and sorting. Queuing organizes data into manageable sets or workflows, enabling efficient processing.

Other options are less suitable:

• Sandboxing refers to isolating software or code execution environments to prevent interference or damage, unrelated to data organization.

• Data visualization is about creating graphical representations (charts, graphs) to help interpret data but doesn’t change the data structure itself.

• Convenience sampling is a method in research for selecting easily accessible samples, not for processing or structuring large data volumes.

Therefore, normalization is the best description of Miley’s efforts to refine and organize unstructured data. This technique enhances data quality and usability, allowing analysts to work with streamlined, consistent datasets instead of overwhelming, raw unstructured information.

Question 7:

Bob, a threat analyst at TechTop, is tasked with gathering intelligence to aid the organization’s Red Team, whose goal is to simulate real-world cyberattacks and test security defenses. 

Which type of intelligence would best support the Red Team in planning and conducting effective penetration testing or red teaming exercises?

A. Intelligence focused on increased attacks targeting a specific software or operating system vulnerability
B. Intelligence on the latest vulnerabilities, threat actors, and their tactics, techniques, and procedures (TTPs)
C. Intelligence based on recent attacks against similar organizations, including new threats and TTP details
D. Intelligence highlighting risks linked to strategic business decisions

Answer: B and C

Explanation:

The Red Team’s primary role is to emulate realistic cyberattack scenarios to identify security gaps and test an organization’s defenses. To perform effectively, they require comprehensive and current intelligence that helps them mimic the behavior, tools, and strategies of actual threat actors.

Option B is crucial because understanding the most recent vulnerabilities and the attackers who exploit them—including their Tactics, Techniques, and Procedures (TTPs)—enables the Red Team to design attacks that mirror the latest threats. This knowledge allows the team to focus on the most relevant and dangerous attack methods currently observed in the wild, increasing the realism and impact of their tests.

Option C also plays a significant role because learning from recent incidents targeting similar organizations gives the Red Team valuable context. It reveals industry-specific threat trends and real-world attack methods that adversaries use. This type of intelligence enhances the relevance of the Red Team’s simulations, helping them tailor their activities to the most probable threats the organization might face.

On the other hand, Option A offers narrower intelligence focusing on a single vulnerability or software platform. While useful, it lacks the broader context that the Red Team needs to cover diverse attack vectors and adversary behaviors.

Option D, which centers on risks tied to business strategy, is not directly applicable to the Red Team’s technical mission. Though important for organizational risk management, it does not aid in planning cyberattack simulations.

In summary, to support realistic and effective red teaming, intelligence must be broad, up-to-date, and contextualized—covering both the latest vulnerabilities and threat actors’ behaviors, as well as insights from similar recent attacks. This makes B and C the best choices.

Question 8:

Michael, a threat analyst at TechTop, is conducting cyber-threat intelligence analysis. After gathering initial information about potential threats, he is now analyzing their characteristics and evaluating their possible impact. 

At which stage of the cyber-threat intelligence lifecycle is Michael currently operating?

A. Unknown Unknowns
B. Unknowns Unknown
C. Known Unknowns
D. Known Knowns

Answer: C

Explanation:

The cyber-threat intelligence lifecycle often refers to different levels of awareness regarding threats, framed by the concepts of “known knowns,” “known unknowns,” “unknown unknowns,” and “unknowns unknown.” These stages describe what an organization knows or does not know about potential threats and help structure the intelligence process.

“Known Knowns” (Option D) describe threats that are fully understood and tracked, with clear information about their tactics and implications. These represent the intelligence the organization has already gathered and thoroughly analyzed.

“Known Unknowns” (Option C) apply when the organization knows threats exist but lacks complete details—such as their full scope, how they operate, or the potential impact. This stage involves active investigation and analysis to fill those gaps. Since Michael is analyzing gathered data to better understand the nature of these threats, he is in this phase.

“Unknown Unknowns” (Option A) refer to threats that the organization is completely unaware of until they manifest or are discovered unexpectedly during investigations.

“Unknowns Unknown” (Option B) is a similar concept emphasizing total ignorance about certain threats, often considered the most dangerous because there is no prior warning or recognition.

Because Michael is examining collected threat information to characterize and assess the risks—meaning he knows threats exist but is still working on uncovering critical details—he is clearly operating in the “Known Unknowns” stage.

This stage is vital for advancing threat intelligence from mere detection to actionable insights that inform defense strategies and incident response.

Question 9:

Enrage Tech Company employed Enrique, a security analyst, to conduct threat intelligence analysis. During data collection, Enrique set up a recursive DNS server to implement a counterintelligence measure. This recursive DNS server logs all DNS queries it receives and stores the logs centrally. 

Enrique then uses these logs to identify potential malicious activity targeting the DNS system.Which cyber counterintelligence technique did Enrique use to gather data?

A. Data collection through passive DNS monitoring
B. Data collection through DNS interrogation
C. Data collection through DNS zone transfer
D. Data collection through dynamic DNS (DDNS)

Answer: A

Explanation:

In this situation, Enrique uses a specific method to collect DNS-related data to analyze threats targeting the DNS infrastructure. Understanding the technique requires focusing on how data is gathered. Enrique’s approach involves setting up a recursive DNS server that records all queries and responses it processes without actively interacting with or altering the DNS records themselves. This form of collection is characterized by observing and logging DNS traffic passively.

Option A, passive DNS monitoring, perfectly describes this approach. Passive DNS monitoring entails capturing DNS queries and responses as they happen on the network without sending any active queries or requesting information. The recursive DNS server logs the traffic, which is then stored centrally for analysis. This method is non-intrusive and valuable for detecting malicious patterns or anomalies in DNS traffic without alerting potential attackers or causing DNS disruptions. Enrique’s setup fits this definition exactly since it relies on passive data collection.

Option B, DNS interrogation, involves actively querying DNS servers to extract information, which contrasts with Enrique’s passive listening and logging. Enrique is not sending additional DNS requests but merely recording responses.

Option C describes DNS zone transfers, which replicate full DNS zones between servers, mainly for redundancy or synchronization, and is not about passive monitoring or traffic logging. This process is more intrusive and not used primarily for threat intelligence in this manner.

Option D involves dynamic DNS (DDNS), which dynamically updates DNS records based on device IP changes and is unrelated to passive logging or threat detection techniques.

In summary, Enrique’s method of collecting DNS data by logging recursive DNS queries without altering traffic corresponds to passive DNS monitoring, making Option A the correct answer. This technique allows cybersecurity analysts to observe DNS behavior and detect suspicious activities quietly and effectively.

Question 10:

During a threat intelligence operation, an analyst deploys a recursive DNS server that passively logs all DNS queries and responses it receives. The collected data is stored centrally for later analysis to detect potential DNS-based attacks. 

Which cyber counterintelligence technique is the analyst utilizing in this scenario?

A. Active DNS Interrogation
B. Passive DNS Monitoring
C. DNS Zone Transfer
D. Dynamic DNS (DDNS) Collection

Answer: B

Explanation:

This question relates to techniques used in cyber counterintelligence and threat intelligence, particularly focusing on DNS-based data collection methods, which are essential topics in the EC-Council’s 312-85 Certified Threat Intelligence Analyst (CTIA) exam.

The key to answering this question lies in understanding the nature of the data collection method described. The analyst uses a recursive DNS server that logs DNS queries and responses passively—meaning the server does not initiate DNS queries or interfere with DNS traffic but simply records the traffic it observes.

Passive DNS monitoring (Option B) is a widely used technique where DNS traffic is collected and logged without active querying or manipulation. It provides a historical record of DNS queries and responses that can be analyzed for unusual or malicious patterns, such as DNS tunneling, cache poisoning attempts, or botnet command and control communications. Since this technique involves no active interrogation or disruption of DNS systems, it is stealthy and less likely to alert attackers.

In contrast, active DNS interrogation (Option A) involves actively sending DNS queries to target servers to gather information, which may alert adversaries or affect network performance. This method is more intrusive and generally less covert than passive monitoring.

DNS zone transfers (Option C) are a method for replicating entire DNS databases from primary to secondary DNS servers. While sometimes abused by attackers to gather information, zone transfers are not used for passive monitoring of live DNS traffic but rather for replicating DNS records in bulk.

Dynamic DNS (DDNS) (Option D) is a service that automatically updates DNS records as IP addresses change, especially in networks with frequently changing addresses. DDNS is unrelated to data collection for threat intelligence purposes.

Understanding the distinction between passive and active data collection methods, particularly in DNS monitoring, is vital for threat intelligence professionals. Passive DNS monitoring offers a powerful tool for gathering actionable intelligence with minimal risk of detection, making it a preferred technique in many cyber counterintelligence operations. This knowledge is central to the EC-Council 312-85 exam, which tests candidates’ ability to identify, collect, and analyze threat data using various intelligence-gathering methods.