The Cisco 300-220 exam validates your ability to conduct threat hunting and defend networks using Cisco technologies as part of the Cisco Certified CyberOps Professional certification path. This exam tests both foundational knowledge and practical decision-making in real-world threat scenarios. Whether you're advancing your cybersecurity career or strengthening your defensive capabilities, this page guides you through the exam structure, core topics, and an effective study approach to build confidence before test day.
Use this topic map to guide your study for Cisco 300-220 (Conducting Threat Hunting and Defending using Cisco Technologies for CyberOps) within the Cisco Certified CyberOps Professional path.
The 300-220 exam measures both your conceptual understanding and your ability to apply threat hunting logic in realistic situations. Questions progress in difficulty and require you to think through practical decisions that security teams face every day.
Questions become progressively more complex, requiring you to integrate multiple topics and apply judgment under realistic constraints.
An efficient study plan maps each topic to weekly milestones and builds from foundational concepts to applied scenarios. Dedicate time to both solo review and active practice, then validate your readiness with timed assessments that simulate exam conditions.
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Threat Hunting Processes and Threat Hunting Techniques typically account for a larger portion of the exam because they directly test your ability to conduct investigations and make real-world decisions. However, all six topic areas are important, and weakness in Threat Hunting Fundamentals or Threat Actor Attribution can hurt your overall score. Balance your study time proportionally, but spend extra effort on process workflows and hands-on technique application.
Threat modeling informs which hunts to prioritize by identifying your highest-risk assets and attack paths. Once you've modeled threats, you use those insights to structure your hunting processes: you form hypotheses based on your threat model, execute hunts using appropriate techniques, and then refine your model based on what you find. Together, they create a continuous cycle of defense improvement.
Practical experience with Cisco security tools (such as Cisco Secure Endpoint, Cisco Secure Network Analytics, and Cisco Secure Email) and log analysis platforms is valuable. Ideally, you should have performed at least one complete threat hunt from hypothesis to report, and reviewed real security logs or pcap files. If you lack production experience, lab scenarios that simulate threat hunting workflows will help bridge that gap.
Many candidates confuse reactive incident response with proactive threat hunting, leading to wrong answers on Processes questions. Others underestimate the importance of proper threat actor attribution and skip MITRE ATT&CK framework study. A third common error is choosing technically correct but contextually suboptimal answers in scenario questions, because they didn't fully read the business constraints or threat context. Always re-read scenario details before answering.
Reduce new material intake and focus on weak areas identified in your practice tests. Run two more timed mocks at full length, review explanations thoroughly, and note any patterns in your mistakes. In the last 2-3 days, do light review of key definitions and process flows rather than heavy studying. Get adequate sleep the night before so you're sharp and focused during the exam.
A mature SOC notices that several incidents over the past year involved attackers abusing legitimate administrative tools rather than deploying custom malware. Leadership asks the threat hunting team to improve detection coverage in a way that increases attacker cost rather than relying on easily replaceable indicators. Which detection strategy best aligns with this objective?
The correct answer is correlating attacker behavior across multiple MITRE ATT&CK techniques. This approach focuses on behavioral detection, which is the cornerstone of effective threat hunting and advanced security operations.
Attackers who abuse legitimate administrative tools---often referred to as living-off-the-land techniques---intentionally avoid malware-based detections. File hashes, signatures, and known indicators provide minimal value because there may be no malicious files at all. Options A and D sit at the lowest levels of the Pyramid of Pain, making them easy for adversaries to evade.
By correlating behavior across multiple ATT&CK techniques---such as credential access, lateral movement, privilege escalation, and command execution---defenders detect how the attacker operates rather than what tools they use. This forces adversaries to fundamentally change tradecraft, which is costly, risky, and time-consuming.
Option C improves visibility but does not inherently raise attacker cost. Threat intelligence feeds are reactive and often lag behind active campaigns.
From a professional threat hunting perspective, correlating multiple low-signal behaviors into a high-confidence attack pattern is how mature SOCs detect stealthy intrusions. This method also supports scalable detection engineering, improved alert fidelity, and reduced false positives.
This strategy directly aligns with higher tiers of the Threat Hunting Maturity Model and the top of the Pyramid of Pain, making option B the correct answer.
A SOC team must prepare for a new phishing campaign that tricks users into clicking a malicious URL to download a file. When the file executes, it creates a Windows process that harvests user credentials. The team must configure the SIEM tool to receive an alert if a suspicious process is detected. Which two rules must the team create in the SIEM tool? (Choose two.)
The correct answers are B. Processes in nonstandard file paths and C. Common processes with modified names. These two detection rules are highly effective for identifying malicious processes spawned by phishing-delivered malware.
Phishing payloads commonly drop executables into nonstandard directories such 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 frequently masquerade malware as legitimate processes by 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, options B and C align with MITRE ATT&CK -- Defense Evasion and Credential Access techniques. These rules focus on behavioral detection, not static indicators, making them resilient against attacker variation.
In short, detecting where a process runs from and what it pretends to be provides strong coverage against phishing-delivered malware, making B and C the correct and professionally validated choices.
A SOC analyst is using Cisco Secure Network Analytics (Stealthwatch) to hunt for command-and-control (C2) activity across the enterprise. The analyst wants to identify stealthy C2 channels that intentionally avoid known malicious IP addresses and domains. Which Stealthwatch hunting approach BEST supports this objective?
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.
A threat hunter uses Cisco Secure Network Analytics (Stealthwatch) to identify potential command-and-control traffic. Which characteristic MOST strongly indicates beaconing behavior?
The correct answer is small, 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 of low-volume, regular intervals connecting to the same external destination. Cisco Secure Network Analytics is purpose-built to detect this type of behavioral anomaly using 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 with MITRE ATT&CK -- Command and Control and is explicitly covered in the CBRTHD blueprint under network-based threat hunting. Detecting beaconing behavior forces attackers to significantly alter their communication strategy, increasing their operational cost.
Therefore, Option C is the correct and Cisco-aligned answer.
A threat hunter wants to detect credential dumping attempts that bypass traditional malware detection. Which telemetry source is MOST effective for this purpose?
The correct answer is endpoint memory access telemetry. Credential dumping often involves accessing sensitive memory regions, such as LSASS, rather than deploying obvious malware.
Modern attackers frequently use:
Legitimate tools
In-memory techniques
Living-off-the-land binaries
These methods bypass file-based detection entirely. Email, DNS, and firewall logs provide limited visibility into memory-level abuse.
Endpoint memory telemetry enables detection of:
Unauthorized LSASS access
Suspicious handle requests
Abnormal process injection
This telemetry is foundational for detecting credential access techniques in modern environments. Therefore, option B is correct.
