Cisco 300-220 Exam Dumps

The correct answer is reduction 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's CBRTHD blueprint emphasizes outcome-driven metrics. Reduced dwell time directly correlates with lower business impact, reduced data loss, and improved resilience.

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

The correct answer is it highlights consistent attacker tradecraft. Attribution depends on recognizing behavioral patterns that persist across campaigns.

Attackers frequently change malware, infrastructure, and exploits, but they are far less likely to change how 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 uses MITRE ATT&CK technique mapping to correlate observed behaviors with known threat actor profiles. These behavioral fingerprints provide far stronger attribution confidence than low-level indicators.

Therefore, Option C is the correct answer.

The correct answer is analyzing 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 on living-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 toward behavioral analysis and anomaly detection.

Option A and D rely on static indicators such as IPs, domains, and hashes. These sit at the lowest levels of the Pyramid of Pain and 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 detect Indicators 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 with MITRE ATT&CK TTP-based hunting, which focuses on tactics and techniques instead of tools or infrastructure. It also reflects a higher tier in the Threat 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, option C is the most accurate and strategically sound answer.

The correct answer is monitoring NetFlow records for abnormal beaconing patterns. Cisco Secure Network Analytics is fundamentally a behavioral 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 the lowest levels of the Pyramid of Pain.

Stealthwatch excels at detecting behavioral 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 of C2 traffic, even when encryption and legitimate cloud services are used. By analyzing NetFlow 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 with CBRTHD blueprint objectives related to:

Network-based threat hunting

Detecting command-and-control communications

Moving detection higher on the Pyramid of Pain

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

The correct answer is Network/host artifacts. To understand why, it is important to map the observed attacker behavior to the Pyramid of Pain, a model that ranks indicators by how difficult they are for adversaries to change once detected.

In this scenario, the adversary is using Nmap 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 behind network 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) and UDPs (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 on network and host artifacts forces 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, making C the correct answer.