Pass the Cisco Cisco Certified Specialist - Threat Hunting and Defending 300-220 Questions and answers with CertsForce

The correct answer isTransitioning from reactive to proactive threat hunting to identify unknown threats and vulnerabilities. This directly aligns with both theThreat Hunting Maturity Modeland the strategic goals of thePyramid of Pain, which emphasizes increasing the adversary’s cost by detecting behaviors and tactics rather than easily changeable indicators.

Reactive security operations focus on alerts, signatures, and known indicators such as hashes, IP addresses, and domains—the lowest and least painful levels of the Pyramid of Pain. While necessary, these controls are easily bypassed by sophisticated adversaries. Proactive threat hunting represents a higher maturity level, where analysts actively search forunknown, stealthy, or novel attacker behaviorsthat have not yet triggered alerts.

Option D (automating detection of known threats) improves efficiency but does not meaningfully increase adversary pain, as attackers can rapidly change known indicators. Option B provides preparedness benefits but does not directly shift detection capabilities. Option A focuses on compliance, which is necessary for governance but largely irrelevant to adversary behavior.

By transitioning to proactive hunting, organizations focus onTTP-based detection, such as credential misuse patterns, abnormal lateral movement, persistence mechanisms, and command-and-control behaviors. These detections operate higher in the Pyramid of Pain—tactics, techniques, and procedures—forcing attackers to significantly retool and increasing the likelihood of early detection.

From a CISO-level perspective, this shift reflects mature security leadership:compliance keeps you legal, automation keeps you efficient, but proactive threat hunting keeps you resilient against advanced threats.

The correct next action is tosubmit the file for sandboxing. In professional security operations and threat hunting workflows, sandboxing is the most appropriate step when a file originates from an untrusted source and hash-based reputation checks return anunknownresult. An unknown hash means the file has not yet been classified as benign or malicious by threat intelligence databases, which is common with newly created malware or targeted attacks.

Sandboxing allows the security team to performdynamic analysisby executing the file in an isolated, controlled environment. This process observes runtime behaviors such as process creation, registry modification, network communications, command-and-control callbacks, file system changes, and exploit attempts. These behaviors provide high-fidelity indicators that static analysis or hash lookups cannot reveal.

Option B, reviewing the directory path, is useful for contextual awareness but does not determine whether the file is malicious. Option C, running a full malware scan, is premature; modern malware often evades signature-based scans, especially when the file is previously unknown. Option D, investigating the reputation of the website, is a supporting activity but does not assess the actual behavior or payload of the downloaded file.

From a threat hunting and incident response standpoint, sandboxing bridges the gap betweendetection and confirmation. If the sandbox analysis confirms malicious behavior, the team can escalate to containment actions such as isolating the endpoint, blocking hashes and domains, and performing scope analysis to identify other affected systems. Additionally, sandbox results can be used to create new SIEM detections and EDR behavioral rules, strengthening future defenses.

This approach aligns with professional best practices:unknown file + untrusted source = dynamic analysis first. It ensures accurate classification while minimizing unnecessary disruption to the user or environment.

The correct answer islegitimate system processes executing encoded commands. Fileless malware avoids writing binaries to disk and instead abuses trusted processes such as PowerShell, WMI, or rundll32.

Encoded or obfuscated commands executed by legitimate binaries are a strong indicator offileless execution and defense evasion. Cisco Secure Endpoint provides deep visibility into command-line arguments and process behavior, enabling detection of this technique.

Option A is normal behavior. Option B may indicate suspicious execution but still involves files. Option D relies on file presence, which fileless attacks intentionally avoid.

This technique aligns withMITRE ATT&CK – Command and Scripting Interpreter and Defense Evasionand is directly relevant toCBRTHD exam objectivesrelated to endpoint-based threat hunting.

Therefore,Option Cis the correct answer.

The correct answer issmall, periodic outbound connections to a rare destination. Beaconing is a hallmark of command-and-control (C2) communication, particularly in stealthy malware campaigns.

Attackers design C2 channels to:

Minimize bandwidth usage

Blend into normal traffic

Avoid triggering threshold-based alerts

As a result, beaconing traffic often consists oflow-volume, regular intervalsconnecting to the same external destination. Cisco Secure Network Analytics is purpose-built to detect this type ofbehavioral anomalyusing NetFlow and telemetry analysis.

Option A suggests data exfiltration rather than beaconing. Option B is too broad and unspecific. Option D relates to denial-of-service or scanning activity, not C2.

This hunting technique aligns withMITRE ATT&CK – Command and Controland is explicitly covered in theCBRTHD blueprintunder network-based threat hunting. Detecting beaconing behavior forces attackers to significantly alter their communication strategy, increasing their operational cost.

Therefore,Option Cis the correct and Cisco-aligned answer.

The correct answer isdetecting abnormal authentication behavior across VPN and cloud access. This outcome targetsbehavioral detection, which sits significantly higher on the Pyramid of Pain than static indicators.

Options A and C rely on domains and hashes, which attackers can trivially change. Option D is a response action, not a hunting outcome.

Credential misuse is one of themost common initial access vectors, especially in cloud and remote-access environments. Detecting abnormal authentication behavior—such as:

Impossible travel

Unusual login times

Excessive failed logins

Geographic anomalies

forces attackers tochange how they operate, not just what infrastructure they use.

Cisco tools such as:

Secure Network Analytics

Secure Endpoint

Secure Firewall

Identity telemetry via VPN and SSO

enable this higher-fidelity detection approach. This aligns directly withCBRTHD blueprint objectivesfocused onidentity-based threat hunting.

Therefore,Option Bis correct.

The correct answers areB. Processes in nonstandard file pathsandC. Common processes with modified names. These two detection rules are highly effective for identifyingmalicious processes spawned by phishing-delivered malware.

Phishing payloads commonly drop executables intononstandard directoriessuch as AppData, Temp, Downloads, or user profile subfolders. Legitimate Windows binaries rarely execute from these locations. Monitoring for process execution from such paths is a proven technique for detecting malware loaders, credential stealers, and post-exploitation tooling.

Additionally, attackers frequentlymasquerade malware as legitimate processesby using slightly modified names, such as lsasss.exe, svch0st.exe, or expl0rer.exe. These tactics are designed to evade casual inspection and basic allowlisting. Detecting common Windows process names with anomalies—such as incorrect spelling, unexpected parent processes, or abnormal execution paths—is a high-fidelity behavioral signal.

Option A is too broad; nearly all processes are created by users directly or indirectly, making it noisy. Option D (process ownership changes) and Option E (startup time changes) are less relevant to detecting credential-harvesting processes at execution time and may miss the initial malicious activity.

From a threat hunting and detection engineering perspective, optionsB and Calign withMITRE ATT&CK – Defense Evasion and Credential Accesstechniques. These rules focus onbehavioral detection, not static indicators, making them resilient against attacker variation.

In short, detectingwhere a process runs fromandwhat it pretends to beprovides strong coverage against phishing-delivered malware, makingB and Cthe correct and professionally validated choices.

The correct answer isformulating a hypothesis to search for credential misuse without alerts. This activity is the defining characteristic ofthreat hunting.

Threat hunting isproactive and hypothesis-driven, meaning analysts intentionally search for attacker behavior that has not yet triggered alerts. Detection engineering, on the other hand, focuses on building and tuning automated rules that respond to known patterns.

Options A, B, and D all representreactive or preventative security operations. They rely on known indicators or alerts and are foundational but insufficient against stealthy adversaries who abuse valid credentials and native tools.

Cisco’sCBRTHD blueprintexplicitly emphasizes hypothesis-based hunting as a core competency. Hunters ask questions like:

“If credentials were stolen, how would that look in our telemetry?”

“What behavior would indicate lateral movement without malware?”

This approach aligns with detectingIndicators of Attack (IOAs)and operating higher on thePyramid of Pain, forcing adversaries to change tactics instead of infrastructure.

Therefore,Option Cis the correct and Cisco-aligned answer.

The correct answer isStructured threat hunting. In this scenario, the SOC team has alreadyconfirmed malicious activity—a compromised user account, anomalous VPN access, and indicators consistent with data exfiltration. Once an incident has been validated and attributed to adversary behavior, the next professional step is to performstructured threat huntingto uncover additional attacker actions across the environment.

Structured threat hunting ishypothesis-drivenand based on known attacker tactics, techniques, and procedures (TTPs), often mapped to frameworks such asMITRE ATT&CK. Here, the team can form hypotheses like:“If the adversary accessed the file server for exfiltration, they may have also attempted lateral movement, persistence, or privilege escalation.”Analysts then systematically query endpoint, identity, VPN, file server, and network telemetry to confirm or disprove these hypotheses.

Option A (Unstructured) is typically used at the earliest stages when little is known and analysts are exploring weak signals or anomalies without a defined adversary model. That phase has already passed in this case. Option B (AI-driven) refers to tooling or analytics methods rather than a threat hunting methodology. Option C (Proactive) is a general mindset applied to all hunting activities, not a specific hunting type used to investigate known attacker behavior.

From a professional SOC and threat hunting perspective, structured hunting enablesfull attack chain reconstruction. It helps identify secondary objectives such as data staging locations, additional compromised accounts, persistence mechanisms, and command-and-control activity. The outcome is a more complete understanding of the breach, improved containment, and stronger detection logic for future incidents.

This approach reflects mature security operations:once compromise is confirmed, hunt the adversary—not just the alert. Structured threat hunting ensures attackers are fully evicted and prevents repeat compromise through overlooked footholds.

The correct answer isFiles are encrypted. The exhibit shows a collection of API calls and strings that strongly indicatecryptographic operations associated with file encryption, a common behavior in ransomware and data-encrypting malware.

Key indicators in the script include multiple Windows Cryptographic API function calls such as:

CryptAcquireContextW

CryptCreateHash

CryptHashData

CryptDeriveKey

CryptEncrypt

CryptDecrypt

CryptDestroyKey

CryptReleaseContext

These APIs are part of theWindows CryptoAPI, which is explicitly used to generate cryptographic keys, hash data, and encrypt or decrypt content. The presence of ADVAPI32.dll further confirms cryptographic functionality, as this library provides access to Windows security and encryption services.

Additionally, registry-related APIs such as RegSetValueExA, RegOpenKeyExA, and references to:

Software\Microsoft\Windows\CurrentVersion\Run

indicate that the script may also establishpersistence, ensuring the encryption routine executes again after reboot. However, persistence is secondary; the primary functional behavior shown is encryption.

Option A is incorrect because there are no APIs related to disabling networking (such as InternetSetOption or firewall manipulation). Option B is incorrect because retrieving host version information would involve system query APIs like GetVersionEx, which are not present. Option C is incorrect because although the word sleep appears, it is commonly used by malware to delay execution or evade sandboxes—not to place the system into sleep mode.

From a threat hunting and malware analysis perspective, the combination ofCryptoAPI usage, registry modification, and internet-related APIs (InternetReadFile, InternetQueryDataAvailable) is a classic ransomware pattern: retrieve data or keys, encrypt local files, and possibly communicate with command-and-control infrastructure.

Professional defenders recognize these API patterns ashigh-confidence malicious indicators, often mapped toMITRE ATT&CK – Impact: Data Encrypted for Impact (T1486). Detecting such behavior early is critical to prevent widespread data loss and operational disruption.

In summary, the script’s API usage clearly indicates thatits execution results in file encryption, makingOption Dthe correct answer.

The correct answer isreduction in attacker dwell time. Dwell time measures how long an attacker remains undetected in the environment.

As threat hunting maturity increases:

Detection becomes faster

Behavioral coverage improves

Attackers are identified earlier in the kill chain

Metrics such as alert volume or blocked IPs (Options A and D) do not reflect effectiveness and may even indicate excessive noise. Option B measures inputs, not outcomes.

Cisco’sCBRTHD blueprintfocuses onoutcomes, not activity. Reduced dwell time demonstrates:

Effective hunting

Better visibility

Stronger detection engineering

This metric directly correlates with reduced breach impact and improved resilience.

Therefore,Option Cis the correct and Cisco-aligned answer.