Cisco 300-220 Dumps

The correct answer ismonitoring NetFlow records for abnormal beaconing patterns. Cisco Secure Network Analytics is fundamentally abehavioral analytics platform, not a signature-based detection tool.

Advanced adversaries deliberately avoid known malicious infrastructure to bypass traditional IOC-based defenses. As a result, IP addresses, domains, and threat intelligence feeds (Options A and D) provide limited long-term value and sit at thelowest levels of the Pyramid of Pain.

Stealthwatch excels at detectingbehavioral anomalies in network traffic, particularly:

Regular, low-volume outbound connections

Consistent timing intervals (beaconing)

Rare destination communication

Protocol misuse over common ports (80/443)

These patterns are characteristic ofC2 traffic, even when encryption and legitimate cloud services are used. By analyzingNetFlow telemetry, analysts can detect C2 behavior without needing to know the destination in advance.

Firewall logs (Option C) are reactive and lack behavioral context. They also miss allowed traffic, which is where most stealthy C2 operates.

This hunting technique aligns directly withCBRTHD blueprint objectivesrelated to:

Network-based threat hunting

Detecting command-and-control communications

Moving detection higher on the Pyramid of Pain

Therefore,Option Bis the most effective and Cisco-aligned answer.

The correct answer isendpoint process execution and memory access events. During thedata collection and processing phase, the goal is to gatherhigh-fidelity telemetrythat supports hypothesis validation.

Credential harvesting often occurswithout dropping malwareand instead relies on:

Memory scraping

LSASS access

Credential dumping tools

In-memory execution

Cisco Secure Endpoint provides deep visibility into:

Process creation and parent-child relationships

Memory access attempts

Privilege abuse

Fileless execution

Option A provides enrichment but not raw behavioral evidence. Option C supports context but does not replace endpoint telemetry. Option D is reactive and unreliable for structured hunts.

Within theCBRTHD threat hunting lifecycle, this phase emphasizesevidence over indicators. Without endpoint execution and memory telemetry, hunters cannot reliably confirm credential access techniques.

This aligns withMITRE ATT&CK Credential Accesstactics and Cisco’s emphasis onendpoint behavioral analytics.

Thus,Option Bis the correct answer.

The correct answer isdocument findings and create permanent detections. While containment actions are necessary, they areincident response tasks, not threat hunting outcomes.

Cisco’s threat hunting lifecycle emphasizes that once malicious behavior is confirmed, teams must:

Document attacker techniques

Identify detection gaps

Convert findings into automated detections

Options A and B are tactical responses that address the current incident but do not prevent recurrence. Option D delays improvement and increases risk.

Operationalizing hunt findings ensures:

Repeated attacker behavior is detected automatically

Future dwell time is reduced

SOC maturity increases

This step directly aligns with theCBRTHD blueprint’s focus on continuous improvement and feedback loopsbetween hunting and monitoring.

Therefore,Option Cis the correct answer.

The correct answer isanalyzing abnormal behavior patterns across identity, endpoint, and network telemetry. This approach represents the foundation of modern threat hunting and directly addresses adversaries who deliberately avoid traditional detections.

Advanced attackers increasingly rely onliving-off-the-land techniques, stolen credentials, and legitimate administrative tools such as PowerShell, WMI, RDP, and cloud APIs. These activities rarely generate malware signatures or known IOCs, making alert-driven and signature-based defenses insufficient. As a result, mature threat hunting programs shift focus towardbehavioral analysis and anomaly detection.

Option A and D rely on static indicators such as IPs, domains, and hashes. These sit at thelowest levels of the Pyramid of Painand are trivial for attackers to change. Option B is purely reactive and limited to known malware, offering little value against stealthy intrusions.

By correlating identity logs (authentication patterns, geolocation anomalies), endpoint telemetry (process execution, parent-child relationships), and network activity (unusual connections, lateral movement patterns), hunters can detectIndicators of Attack (IOAs)rather than waiting for confirmed compromise. This enables identification of credential misuse, privilege abuse, and lateral movement even when no malware is present.

This methodology aligns withMITRE ATT&CK TTP-based hunting, which focuses on tactics and techniques instead of tools or infrastructure. It also reflects a higher tier in theThreat Hunting Maturity Model, where organizations proactively search for unknown threats rather than responding to alerts.

In professional SOC environments, this shift dramatically increases detection coverage against advanced adversaries and reduces dwell time. Therefore, optionCis the most accurate and strategically sound answer.

The correct answer isdocumenting findings and updating detection logic. This represents thepost-hunt operationalization phase, which is critical for long-term security improvement.

While options A and C are necessary response actions, they address only thecurrent incident. Threat hunting’s strategic value comes from transforming discoveries intorepeatable detections, playbooks, and controls.

Professional threat hunting programs ensure that:

Successful hunts produce new SIEM rules

Detection gaps are closed

Findings are documented for future analysts

Lessons learned inform security architecture decisions

Option D continues exploration but fails to institutionalize knowledge. Without operationalizing results, organizations repeatedly rediscover the same threats.

This phase directly increases maturity in theThreat Hunting Maturity Model, shifting organizations from hero-driven hunting to scalable, resilient detection. It also moves defendersup the Pyramid of Pain, forcing adversaries to change tactics rather than indicators.

Therefore, optionBis the correct and most strategically important answer.

The correct answer isUse Deep Packet Inspection (DPI) to block malicious domains. The key detail in this scenario is that the endpoint is makingcontinuous outbound TCP connections to a known Command-and-Control (C2) server over port 80, which strongly indicates active malware beaconing or payload retrieval.

Deep Packet Inspection enables security controls—such as next-generation firewalls or network security analytics platforms—to inspectapplication-layer content, including HTTP headers, URLs, domains, and payload characteristics. This allows defenders to block C2 communicationbased on domain names, URL patterns, or behavioral signatures, even if attackers change IP addresses. Since C2 infrastructure is frequently rotated, IP-based blocking alone is insufficient for long-term mitigation.

Option A (browser extension deny list) may help prevent a specific initial infection vector, but it does not addresspost-compromise C2 traffic, especially if malware communicates independently of the browser. Option B (antivirus quarantine) is reactive and limited by signature coverage; modern malware often evades AV detection. Option D (IDS) can detect similar connections but typically does notblocktraffic unless integrated with an IPS or firewall, making it less effective for mitigation.

From a professional threat hunting and SOC standpoint, blocking C2 communication at thenetwork layer using DPIis a high-impact defensive control. It disrupts attacker command channels, prevents data exfiltration, and buys time for endpoint remediation and forensic investigation.

This aligns withMITRE ATT&CK – Command and Control (TA0011)mitigation strategies and reflects a mature security posture:detect at the endpoint, disrupt at the network. Therefore, optionCis the most effective action to mitigate similar connections in the future.

The correct answer isC. Modifying this key requires administrative privileges, which the malware might not have.

The exhibit shows persistence established under the registry path:

HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Run

This registry key is aper-user startup location, meaning any executable listed there will automatically run whenthat specific userlogs in. Crucially,write access to HKEY_CURRENT_USER (HKCU) does not require administrative privileges—only the privileges of the compromised user account.

In contrast,

HKEY_LOCAL_MACHINE\Software\Microsoft\Windows\CurrentVersion\Run

appliessystem-wideand causes programs to execute at startup forall users. However, modifying this key requireslocal administrator privileges. In many real-world breaches, attackers initially compromisestandard user accounts, not administrators. As a result, malware often chooses HKCU-based persistence mechanisms because they arereliable, stealthy, and achievable without privilege escalation.

Options A and D are incorrect because both registry paths are fully supported in modern versions of Windows and are explicitly designed for startup execution. Option B is incorrect because neither key automatically removes entries after a reboot—both are persistent by design.

From a threat hunting and endpoint detection perspective, this distinction is critical. HKCU persistence indicates:

User-level compromise

No confirmed administrative access (yet)

Potential precursor to privilege escalation attempts

This technique maps toMITRE ATT&CK – Persistence: Boot or Logon Autostart Execution (T1547.001). Mature SOC teams monitorboth HKCU and HKLM Run keys, but they interpret them differently when reconstructing attacker capability and progression.

In summary, the attacker usedHKCUbecause it enables persistencewithout requiring administrative privileges, makingOption Cthe correct and professionally accurate answer.

The correct answer isMonitoring failed AWS console login attempts. The Bash script shown in the exhibit is clearly designed toparse AWS CloudTrail logsand extract specific authentication-related events.

Breaking down the script behavior from a professional cloud security perspective:

gunzip -c *.json.gz indicates the script is processingcompressed CloudTrail log files, which are typically stored in .json.gz format.

jq -c '.Records[]' parses individual CloudTrail records, a common approach when analyzing AWS activity logs.

The filter conditions explicitly check for:

eventSource == "signin.amazonaws.com"

eventName == "ConsoleLogin"

responseElements.ConsoleLogin == "Failure"

These fields are definitive indicators offailed AWS Management Console login attempts. Additionally, the script extracts contextual fields such as:

Event time

Source IP address

Error message

AWS region

Username

MFA usage status

This data is exactly what security teams use to detectcredential abuse, password spraying, brute-force attempts, and compromised IAM accounts. Monitoring failed console logins is a foundational cloud threat hunting activity, especially for identifying early stages of account takeover.

Option B is incorrect because the script does not establish AWS CLI sessions or authenticate to accounts. Option C is incorrect because instance errors would involve services like ec2.amazonaws.com and different event names. Option D is incorrect because the script is analyzing—not archiving—records, and it applies filtering logic rather than storage or lifecycle management.

From a threat hunting and cloud security standpoint, this script supportsidentity-focused detection, which is critical in AWS environments where IAM misuse is one of the most common initial access vectors. It aligns withMITRE ATT&CK – Credential Access and Initial Access, particularly techniques involving valid account abuse.

In summary, the script’s clear purpose is tomonitor failed AWS console login attempts, makingOption Athe correct and professionally validated answer.

The correct answer isstandardizing hunt documentation and hypotheses. Mature threat hunting programs move beyond ad-hoc, intuition-driven efforts.

Standardization enables:

Knowledge sharing

Consistent methodology

Repeatable hunts

Easier onboarding of new analysts

Option A and B support operations but do not improve hunting maturity. Option D is unrealistic and risky.

By documenting hypotheses, data sources, queries, findings, and outcomes, organizations institutionalize knowledge and continuously improve detection capabilities.

This is a defining characteristic ofhigh-maturity threat hunting programs.

Therefore, optionCis correct.

The correct answer isauthentication and remote execution logs. Lateral movement using legitimate tools relies heavily oncredential use and remote management protocols, not malware execution.

Attackers commonly use:

RDP

SMB administrative shares

WinRM

WMI

SSH

These techniques generateauthentication events, remote logons, and service execution logsrather than malware alerts. Antivirus tools are ineffective here because no malicious binaries are involved.

Option A is ineffective against living-off-the-land attacks. Option B is unrelated to lateral movement. Option D may show some activity but lacks the necessary depth to identify privilege misuse or session hopping.

Authentication telemetry enables hunters to detect anomalies such as:

Logons between non-associated systems

Sudden administrative access

Credential reuse across hosts

Abnormal session timing and frequency

This data is foundational forcredential-based attack detection, which remains one of the most common breach paths today. It also aligns withMITRE ATT&CK Lateral Movement and Credential Access tactics.

Thus, optionCis the correct answer.

The correct answer isSimple. The exhibit shows an EDR query filtering onspecific IPv4 addresses, which are classicIndicators of Compromise (IOCs). Within thePyramid of Painmodel, IP addresses sit at thelowest level, representing the least painful indicators for adversaries to change.

The Pyramid of Pain categorizes detection indicators by how costly they are for attackers to replace:

Simple→ Hashes, IP addresses, domain names

Easy→ Network artifacts (URI patterns, user-agent strings)

Challenging→ Host artifacts (registry keys, file paths, mutexes)

Tough→ Tactics, Techniques, and Procedures (TTPs)

In this scenario, the threat-hunting team is querying EDR telemetry for outbound connections toknown C2 IP addresses. While this is a valid and common detection technique—especially for rapid containment—it provides minimal long-term defensive value. Attackers can easily rotate C2 infrastructure by changing IPs, using cloud hosting, fast-flux DNS, or proxy networks.

Option C (Easy) would apply if the team were hunting fornetwork artifacts, such as suspicious URI paths or protocol misuse. Option B (Challenging) would involvehost-based artifacts, like malware persistence keys or file system changes. Option A (Tough) represents the highest maturity—detectingadversary behavior and techniques, such as beaconing patterns, lateral movement workflows, or credential abuse—none of which are present here.

From a professional threat-hunting standpoint, IP-based detections are best used asshort-term controlsfor blocking known threats or scoping an incident. Mature organizations use them as a starting point, then pivot toward higher-fidelity detections that sit higher on the Pyramid of Pain and impose greater operational cost on attackers.

In summary, querying known C2IP addressescorresponds to theSimplelevel of the Pyramid of Pain, makingOption Dthe correct answer.

The correct answer isCredential Access. In the MITRE ATT&CK framework,password sprayingis classified under theCredential Access tactic (TA0006), specifically techniqueT1110.003 – Password Spraying. This classification is based on the attacker’s primary objective:gaining valid credentialsby systematically attempting a small number of common or weak passwords across many user accounts.

Password spraying differs from brute-force attacks in that it intentionally avoids rapid or repeated attempts against a single account, thereby evading account lockout controls and basic detection mechanisms. Instead, attackers “spray” one password (for example,Winter2025!orPassword123) across a large number of users, exploiting the likelihood that at least one account will use that password.

Although successful password spraying often leads toinitial access, MITRE classifies it underCredential Accessbecause the technique’s defining action is theacquisition of credentials, not the system entry itself. Initial access is the outcome, while credential theft is the method. This distinction is critical for threat hunters, as it guides where detections and controls should be focused.

From a professional threat hunting perspective, defenders monitor authentication telemetry such as failed and successful logins across identity providers, VPNs, cloud services, and email platforms. Indicators include multiple authentication failures across many accounts from a single source IP, followed by one or more successful logins. Identity-centric logging and anomaly detection are foundational here, reinforcing the principle thatidentity is the primary attack surface in modern environments.

Understanding password spraying as a credential access technique helps organizations prioritize protections such as strong password policies, MFA enforcement, adaptive authentication, and detection logic tuned for low-and-slow authentication abuse.

The correct answer isExploit public-facing application. The log excerpt in the exhibit clearly shows amalicious HTTP GET requesttargeting aWordPress plugin PHP filewith a craftedSQL injection payload:

UNION ALL SELECT CONCAT(...)

This syntax is a classic indicator ofSQL injection, a well-documented attack technique used to exploit insufficient input validation in web applications. According to the MITRE ATT&CK framework, this behavior maps to theInitial Access tactic (TA0001)and the techniqueExploit Public-Facing Application (T1190). The attacker is directly interacting with a publicly accessible web service and abusing a vulnerability in the application code to gain unauthorized access.

From a threat hunting and forensic standpoint, this is a textbook example of how attackers commonly achieve initial access to web servers. The attacker did not authenticate via remote services (such as SSH or RDP), nor did they rely on user interaction (as in a drive-by compromise). Instead, they sent a specially crafted request to a vulnerable endpoint exposed to the internet. This makes option B incorrect becauseExternal Remote Servicesrequires legitimate service access mechanisms. Option C is also incorrect becauseCommand and Scripting Interpreteris typically usedafterinitial access, once code execution is already achieved. Option D does not apply because there is no evidence of malicious content being delivered to end users.

The forensic team’s actions—isolating the server, cloning the disk, and analyzing logs—are standard post-incident procedures to reconstruct the attack chain. Web server access logs are especially valuable in these cases, as they often reveal malicious payloads, attacker IP addresses, targeted endpoints, and timestamps.

For defenders and threat hunters, this scenario reinforces the importance of monitoring web logs for anomalous query strings, enforcing secure coding practices, conducting regular vulnerability scans, and promptly patching third-party plugins. Public-facing applications remain one of themost exploited initial access vectors, making this technique a critical focus area in modern threat hunting programs.

The correct answer isit highlights consistent attacker tradecraft. Attribution depends on recognizingbehavioral patternsthat persist across campaigns.

Attackers frequently change malware, infrastructure, and exploits, but they are far less likely to changehow they prefer to operate. Consistent use of SMB for lateral movement and deliberate avoidance of PowerShell reflect conscious operational choices.

Option A is unrelated to lateral movement behavior. Option B assumes malware development, which may not exist. Option D addresses impact, not attribution.

Cisco-aligned threat hunting usesMITRE ATT&CK technique mappingto correlate observed behaviors with known threat actor profiles. These behavioral fingerprints provide far stronger attribution confidence than low-level indicators.

Therefore,Option Cis the correct answer.

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 answer isit reveals operational discipline and intent. Attribution relies heavily on understandinghow attackers think and operate, not just the tools they use.

Operational discipline—such as careful reconnaissance, avoiding noisy exploitation, and operating during business hours—is ahuman behavioral pattern. These patterns are far more stable than infrastructure or malware and often correlate strongly with specific threat actor groups.

Option A and D focus on tooling, which changes frequently. Option B relates to persistence, not attribution.

Threat intelligence professionals use operational characteristics to distinguish between opportunistic criminals and advanced adversaries. Business-hour activity, careful lateral movement, and deliberate escalation often indicatetargeted intrusions, espionage, or financially motivated but sophisticated actors.

This information helps analysts align observed behavior with known threat actor profiles, improving attribution confidence. Thus, optionCis correct.

The correct answer isIndicators of attack (IOAs). Unstructured threat hunting is typically triggered byweak signals, anomalies, or suspicious behaviorsthat do not yet meet the threshold of confirmed compromise. These early signals are best described as indicators of attack rather than indicators of compromise.

To understand this distinction, it’s important to separateIOAsfromIOCs. Indicators of compromise (Option A) include confirmed artifacts such as malicious hashes, known bad IP addresses, or identified malware. When IOCs are present, the organization is already reacting to a known or validated threat, which aligns more closely withstructured threat huntingor incident response—not unstructured hunting.

Unstructured threat hunting is exploratory in nature. It is often initiated when analysts notice something “off,” such as unusual login behavior, abnormal process execution, unexpected network traffic patterns, or deviations from baseline behavior. These observations suggestattacker intent or activity in progress, but without definitive proof of compromise. That uncertainty is precisely what drives unstructured hunts.

Option B (tactics, techniques, and procedures) is incorrect because TTPs are typically used to formhypothesis-driven, structured huntsbased on known adversary behavior frameworks like MITRE ATT&CK. Option C (customized threat identification) is vague and not a recognized trigger within professional threat hunting models.

From a SOC and threat hunting maturity perspective, unstructured hunting commonly occurs inlower to mid maturity environments, where hunters rely on intuition, experience, and anomaly detection rather than predefined hypotheses. It often serves as thestarting pointfor discovering new attack patterns, which can later be formalized into structured hunts and detection logic.

In short, unstructured threat hunting begins when defenders detectindicators of attack—signals that something malicious may be happening, even if there is no confirmed compromise yet. This makesOption Dthe correct and professionally accurate answer.

The correct answer isinternal systems authenticating to multiple hosts using SMB in a short time. This behavior is a classic indicator ofcredential-based lateral movement.

When attackers obtain valid credentials, they often move laterally by:

Accessing administrative shares (e.g., C$, ADMIN$)

Using SMB, WMI, WinRM, or RDP

Authenticating to multiple systems rapidly

Cisco Secure Network Analytics excels at identifyingeast-west traffic anomalies, which are central to lateral movement detection. A single host authenticating to many internal systems over SMB in a short time deviates strongly from normal user behavior.

Option A relates to external traffic, not lateral movement. Option C may indicate command-and-control or staging but not lateral movement. Option D aligns more with beaconing behavior.

This technique aligns withMITRE ATT&CK – Lateral Movementand is explicitly covered in theCBRTHD blueprintunder network-based threat hunting.

Thus,Option Bis the correct answer.