300-220 Conducting Threat Hunting and Defending using Cisco Technologies for Cybersecurity 300-220 CBRTHD Questions and Answers

The correct answer isC. Host 10.201.3.99 is attempting to contact the C2 server to retrieve the payload.

Cisco Secure Network Analytics (Stealthwatch) detectsCommand-and-Control (C2)activity by analyzingnetwork behavior, not by relying solely on known malicious indicators. In the exhibit, the critical investigative clue is theHTTP payload containing a suspicious external URL, which strongly suggests outbound communication from an internal host to an external command-and-control infrastructure.

The internal IP address10.201.3.99belongs to a workstation group (“Desktops”), indicating it is an internal endpoint, not a C2 server. This immediately rules out option B. Instead, the endpoint is acting as acompromised host (zombie)attempting to reach a remote server controlled by an attacker. This outbound beaconing behavior is a classic hallmark of C2 communication.

Option A is incorrect because packet count alone does not confirm C2 activity. C2 traffic is oftenlow-and-slow, intentionally designed to blend in with normal traffic patterns. Option D is also incorrect because the payload does not describe the zombie endpoint; rather, it shows aremote URL, which is likely part of malware staging or command retrieval.

From a threat hunting and SOC perspective, the most valuable information isdirectionality and intent:

Internal host → external suspicious domain

HTTP-based communication over an unusual port

Low data volume consistent with beaconing or payload retrieval

This aligns withMITRE ATT&CK – Command and Control (TA0011)techniques such asApplication Layer Protocols (T1071). Identifying which internal host is reaching out—and why—is essential for containment, endpoint isolation, and scope expansion.

Professionally, this insight enables the analyst to:

Quarantine host 10.201.3.99

Pivot to EDR telemetry on that endpoint

Block the external domain or IP

Hunt for similar beaconing patterns across the environment

In summary, the investigation is aided most by understanding thatan internal host is actively communicating with a C2 server, makingOption Cthe correct and operationally meaningful answer.

The correct answer isanalyzing authentication behavior anomalies across users and devices. Credential abuse is one of the most common and effective techniques used by modern attackers because it allows them to blend in with legitimate activity and bypass malware-based defenses.

Options A and B rely on malware indicators, which are often absent in credential-based attacks. Option D addresses only one potential delivery or command-and-control vector and does not detect misuse of valid credentials.

By analyzing authentication behavior, threat hunters can detect:

Impossible travel scenarios

Abnormal login times

Excessive failed logins followed by success

Logins from unusual devices or locations

Cisco tools such asCisco Secure Network Analytics, VPN telemetry, and identity logs provide rich data sources for this type of hunting. This approach focuses onIndicators of Attack (IOAs)rather than Indicators of Compromise (IOCs), pushing detection higher on thePyramid of Pain.

Within theCBRTHD blueprint, hunting for credential misuse is a core competency, especially in cloud and remote-access environments. Detecting these behaviors early significantly reduces attacker dwell time and limits the blast radius of compromise.

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

The correct answer isearlier detection of attacks before data exfiltration. This outcome directly translates toreduced business impact, which is the ultimate goal of threat hunting.

Alert volume (Option A) and false-positive reduction (Option B) measure operational efficiency, not security effectiveness. Option D measures spending, not outcomes.

Early detection:

Reduces dwell time

Prevents data loss

Limits operational disruption

Increases attacker cost

Cisco’sCBRTHD blueprintemphasizes outcome-driven security metrics, with early detection being one of the strongest indicators of threat hunting maturity.

Therefore,Option Cis the correct and executive-level answer.

The correct answer isit reveals consistent attacker tradecraft across incidents. Attribution relies onbehavioral consistency, not on malware samples or exploits.

Avoiding malware and abusing legitimate tools (living-off-the-land techniques) reflects adeliberate operational strategy. These behaviors tend to remain consistent across campaigns and are frequently documented in threat intelligence profiles.

Options A and D are incorrect because no exploit or ransomware is involved. Option B is incorrect; living-off-the-land techniques are modern, not outdated.

Cisco-aligned threat hunting emphasizesMITRE ATT&CK mappingand behavioral analysis to support attribution efforts. This approach is far more reliable than artifact-based attribution.

Thus,Option Cis the correct answer.

The correct answer ismapping trust relationships between identity systems. Hybrid identity environments introduce complex trust boundaries that attackers routinely exploit.

Modern breaches increasingly involveidentity pivoting, where attackers compromise a cloud identity and abuse synchronization, federation, or conditional access misconfigurations to escalate into on-prem Active Directory. These attack paths often do not rely on software vulnerabilities at all.

Option A is too narrow and focuses only on technical exploits. Option C measures severity but does not model movement. Option D analyzes traffic but does not explain privilege escalation pathways.

By mapping trust relationships—such as Azure AD Connect synchronization, service principals, hybrid admin roles, and conditional access exclusions—defenders can identifychained attack pathsthat enable privilege escalation without exploiting code.

From a threat hunting standpoint, this modeling enables:

Hypothesis-driven hunts

Detection of abnormal role assumptions

Visibility into identity abuse

This approach aligns withattack path modeling, a critical evolution of traditional threat modeling for identity-centric environments. Therefore, optionBis 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 isNetwork/host artifacts. To understand why, it is important to map the observed attacker behavior to thePyramid of Pain, a model that ranks indicators by how difficult they are for adversaries to change once detected.

In this scenario, the adversary is usingNmap OS fingerprinting, which involves sending carefully crafted packets and analyzing responses (TCP/IP stack behavior, TTL values, window sizes, flags, and timing characteristics). These behaviors leave behindnetwork and host artifacts, such as distinctive scan patterns, abnormal TCP flag combinations, OS fingerprinting probes, and consistent tool-specific traffic signatures.

On the Pyramid of Pain:

IP addresses (D)sit at the very bottom. Attackers can trivially change IPs using VPNs, proxies, or botnets.

Port probes (B)andUDPs (A)represent low-level indicators that are also easy to modify. An attacker can change scan ports, protocols, or scan timing with minimal effort.

Network/host artifacts (C)sit significantly higher. These include tool-generated behaviors, protocol anomalies, OS fingerprinting patterns, and scan logic inherent to tools like Nmap. Changing these requires attackers to reconfigure tools, write custom scanners, or significantly alter their operational approach.

From a threat hunting and SOC maturity perspective, detecting and alerting onnetwork and host artifactsforces attackers to expend more time and resources, increasing their operational cost. This aligns with the core objective of the Pyramid of Pain:maximize adversary pain by detecting behaviors, not easily replaceable indicators.

Professionally mature SOC teams focus on identifying scanning techniques (e.g., Nmap OS detection, TCP ACK probes, UDP probes) rather than blocking individual IPs. These detections are resilient, scalable, and effective against both commodity attackers and advanced adversaries.

In short, while IPs and ports are useful for short-term containment,network and host artifacts provide the highest-value indicators in this scenario, makingCthe correct 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 isit indicates disciplined and methodical tradecraft. Attribution relies on understandingattacker behavior patterns, not just tools or infrastructure.

Consistent operational discipline—such as cautious discovery, avoidance of noisy actions, and deliberate escalation—reflectshuman decision-making, which is difficult to change and often persists across campaigns.

Options A, B, and D focus on artifacts or infrastructure, which attackers frequently rotate. Behavioral patterns, however, form atradecraft fingerprint.

Cisco-aligned threat hunting usesMITRE ATT&CK technique mappingand behavioral consistency to support attribution, making this observation highly valuable.

Thus,Option Cis correct.

The correct answer isit reflects the attacker’s operational preferences. Attribution relies on understandinghow attackers operate, not just what tools they use.

Operational preferences—such as avoiding PowerShell logging, disabling AMSI, and favoring WMI—arebehavioral signatures. These patterns often persist across campaigns and are documented in threat intelligence reports associated with specific adversaries.

Option A is incorrect because malware families change frequently. Option B is unreliable due to infrastructure rotation. Option D is unrelated to post-access tradecraft.

Professional attribution focuses on:

Execution methods

Defensive evasion choices

Tooling preferences

Workflow consistency

Mapping these behaviors toMITRE ATT&CK techniquesenables analysts to compare findings against known threat actor profiles. This provides higher confidence attribution than artifact-based indicators.

Thus, optionCis the correct answer.

The correct answer isreduction in attacker dwell time. Dwell time measures how long an attacker remains undetected after initial compromise.

As threat hunting maturity increases:

Behavioral coverage improves

Detection occurs earlier in the attack lifecycle

Attackers are identified before achieving objectives

Options A and C measure activity, not effectiveness. Option D measures inputs, not outcomes.

Cisco’sCBRTHD blueprintemphasizes outcome-driven metrics. Reduced dwell time directly correlates with lower business impact, reduced data loss, and improved resilience.

Therefore,Option Bis the most meaningful and Cisco-aligned metric.

The correct answer isUnauthorized penetration test. Based on the scenario provided, there is no indication that the observed activity was planned, approved, or coordinated by the organization. Instead, the evidence points tomalicious, unauthorized accessusing a valid user account, followed by destructive actions on the file server.

The exhibit showsmultiple file deletions and modificationsoccurring within a very short time window after asuccessful remote sign-in. From a professional SOC and threat hunting perspective, this sequence strongly suggestsaccount compromisefollowed byintentional malicious activity, such as data destruction, ransomware staging, or anti-forensics behavior. Intrusion Prevention System alerts further reinforce that the activity violated security policies, which would not be the case during a sanctioned test.

Option A (White box penetration test) and Option D (Black box penetration test) both describetesting methodologies, not threat types. White box testing is conducted with full internal knowledge and explicit authorization, while black box testing is performed with limited knowledge but still under a formal, approved engagement. In both cases, SOC teams are typically informed ahead of time to prevent unnecessary incident escalation.

Option B (Authorized penetration test) is also incorrect because authorized tests are documented, scoped, and approved by management. They do not involve real user account compromise without prior notification, nor do they trigger IPS alerts treated as genuine incidents.

In contrast,unauthorized penetration testingrefers to real-world attacker behavior where an adversary attempts to compromise systems without permission. Even if the attacker’s techniques resemble penetration testing tools or methods, the lack of authorization makes it a true security incident.

From a threat hunting and incident response standpoint, this classification is critical. Treating unauthorized activity as a live threat ensures proper containment actions, such as account disabling, credential resets, forensic preservation, and scope expansion. Misclassifying such activity as a test could lead to delayed response and increased damage.

In short,authorization—not technique—determines intent. Since no authorization exists in this scenario, the activity represents anunauthorized penetration attempt, making optionCthe correct answer.

The correct answer isdocument findings and operationalize detections. In Cisco’s threat hunting methodology, confirmation of malicious activity isnot the end of the hunt.

The most critical next step is to:

Document attacker behavior

Identify detection gaps

Create or improve SIEM, EDR, or NDR detection rules

This ensures the organization does not repeatedly rediscover the same threat. Options C and D are incident response and communication activities, not threat hunting lifecycle steps. Option A skips the crucial improvement phase.

TheCBRTHD blueprintstrongly emphasizes:

Continuous improvement

Feedback loops

Detection engineering

By operationalizing findings, the SOC increases maturity and forces adversaries to change tactics.

Therefore,Option Bis correct.

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 isDiscovery of unknown attacker behaviors and closure of detection gaps. This outcome best reflects thestrategic valueof threat hunting beyond incident response.

Threat hunting is not primarily about cleanup actions such as credential resets or file removal—those areincident response tasks. The real value of hunting lies in uncoveringpreviously undetected attacker behaviors, understanding how adversaries bypass controls, and translating those findings intoimproved detection and prevention.

Option A represents low-value indicators that attackers can easily change. Option C assumes malware was involved, which is not the case. Option D is necessary but tactical, not strategic.

By identifying credential misuse patterns, lateral movement paths, and data exfiltration techniques, the team can:

Create new SIEM and EDR detections

Harden identity and access controls

Reduce dwell time for future intrusions

Force attackers higher up the Pyramid of Pain

This demonstratesorganizational resilience, not just containment. Mature security programs measure success by how effectively theyeliminate blind spots, not how many alerts they close.

Thus, optionBis the correct answer.