CrowdStrike CrowdStrike Certified Falcon Hunter CCFH-202b Exam Dumps: Updated Questions & Answers (April 2026)

When a hunter encounters a "dual-use" tool like Cloudflared , the investigation must be approached with nuance. Cloudflared (and similar tunneling tools) can be used legitimately by DevOps or IT teams for secure remote access, but they are also frequently used by adversaries for Command and Control (C2) and data exfiltration because they can bypass traditional firewall rules by tunneling traffic over HTTPS.

The first step in Detection Analysis should always be to gather context before taking disruptive actions like network containment or blocking (which could break legitimate business processes). By reviewing the CommandLine arguments in the Falcon Process Timeline , the hunter can see how the tunnel was configured. Are the commands consistent with documented IT procedures? Is the tunnel connecting to a known corporate Cloudflare account, or an anonymous one? Comparing this activity against a baseline of "normal operations" for that specific user or department is essential. If the commands show the tunnel being used to expose a sensitive local port (like RDP or SSH) to the public internet under a non-IT account, the suspicion level increases. This measured approach—investigating the "What" and "Why" before reacting—ensures that the hunter provides accurate triage and avoids unnecessary downtime while still maintaining a high security posture.

To effectively hunt for a malicious file like evil.exe across multiple hosts with "varying filepaths," a hunter must utilize the power of CrowdStrike Query Language (CQL) to aggregate execution telemetry. The inclusion of both ProcessRollup2 and SyntheticProcessRollup2 is vital in this scenario; while ProcessRollup2 captures new executions, SyntheticProcessRollup2 identifies processes that were already active when the Falcon sensor started. This provides critical visibility into files that "existed" and were already operational on the system prior to the detection of a new execution attempt.

The query in Option D is the most effective for a "proactive hunt" because it uses a regular expression—| ImageFileName=/([\/\\])(? < FileName > \w*\.?\w*)$/—to dynamically extract the actual filename into a new field (FileName) from the full path (ImageFileName). This allows the analyst to filter specifically for evil.exe while simultaneously seeing the "varying filepaths" where it resides. By outputting the results into a table containing the aid, hostname, and ImageFileName, the hunter generates a clear list of every unique location and host where the file is present. Unlike a stats count which only provides numerical volume, the table function provides the specific forensic artifacts (the paths) needed to begin remediation or host containment across the entire enterprise. This methodology allows the security team to identify the "blast radius" of the infection and uncover hidden instances of the malware that haven't yet triggered a primary detection.

In the CrowdStrike Falcon Console's Process Tree view, hovering over a specific process node activates a summary window that displays Process Actions . These actions are represented by specific icons and numerical values that quantify the telemetry recorded for that process instance. Understanding these icons is a fundamental skill for Search and Investigation Tools usage, as it allows for a rapid "at-a-glance" triage of a detection without immediately pivoting to raw events.

As shown in the exhibit, the icons from left to right generally correspond to:

Child Processes/Branching : Represented by the branching node icon (Value: 7 ).

Network Operations : Represented by the antenna/signal icon (Value: 8 ).

DNS Requests : Represented by the purple bullseye/target icon (Value: 61 ).

Disk Operations : Represented by the document/page icon (Value: 4 ).

Registry Modifications : Represented by the shield icon (Value: 0 ).

Other Process Operations : Represented by the document with an arrow icon (Value: 2 ).

While standard iconography associates the "8" with Network Operations, Option C is the recognized correct answer within Falcon Hunter training materials to describe this specific exhibit. It accurately identifies 4 Disk Operations (matching the blue page icon), 61 DNS Requests (matching the purple target icon), and 2 Process Operations (matching the cross-process activity icon). This summary allows a hunter to immediately see that this powershell.exe process has been highly active, performing numerous DNS lookups and spawning several child processes, which is characteristic of a script attempting to reach out to Command and Control (C2) infrastructure or download additional payloads.

In the context of Hunting Methodology , reconnaissance (often categorized under the Discovery tactic in the MITRE ATT & CK framework) involves an adversary gathering information about the internal network, host configurations, and user privileges. The query in Option D is specifically designed to hunt for this behavior by monitoring the execution of "Living off the Land" (LotL) binaries.

These built-in Windows utilities, while legitimate for administrative use, are the primary tools used by attackers to "get the lay of the land." Commands like whoami are used for System Owner/User Discovery (T1033), ipconfig and netstat for System Network Configuration Discovery (T1016), and tasklist for Process Discovery (T1057). By filtering for these specific filenames—net, ipconfig, whoami, quser, ping, netstat, tasklist, hostname, and at—on a specific host (aid), a hunter can identify a burst of discovery activity. While individual executions might be common, a series of these commands run in rapid succession by a non-administrative user is a high-confidence indicator of a compromise. This proactive search allows analysts to catch an adversary in the early stages of an attack, before they have successfully identified their next target for lateral movement or privilege escalation.

In the discipline of Hunting Methodology , identifying "hidden in plain sight" directories is a primary objective for uncovering persistent threats. The Recycle Bin ($Recycle.Bin) is considered a highly suspicious directory for process execution because legitimate applications are almost never designed to run from this location. Adversaries frequently utilize this path to stage malicious binaries, as it is a directory that is often overlooked by manual administrative review and some legacy security tools (MITRE ATT & CK T1564.001 - Hidden Files and Directories).

The query in Option C correctly addresses the two specific requirements of the prompt. First, it uses the wildcard aid=* to ensure the hunt is performed across all hosts in the enterprise, providing a global view rather than focusing on a single machine (as seen in Option B). Second, it utilizes a regular expression /\$Recycle\.Bin/i to filter for any ProcessRollup2 events where the ImageFileName originates from the Recycle Bin. While directories like "Downloads" or "Desktop" can also be used for staging, they are significantly "noisier" in a production environment as legitimate users frequently run installers from those paths. By targeting the Recycle Bin and using the groupBy function to aggregate the SHA256HashData, a hunter can quickly identify unique, unauthorized binaries that have been moved to a hidden area to evade detection. This proactive approach allows the security team to identify the "Patient Zero" host and any subsequent lateral movement involving the same malicious hash.

When dealing with widespread malware, such as a persistent scheduled task, a hunter must be able to aggregate vast amounts of telemetry into a manageable list of impacted assets. Within the CrowdStrike Query Language (CQL) used in LogScale, the groupBy() function is the primary tool for data aggregation and deduplication. While functions like table() simply format the output and stats is often used for mathematical calculations, groupBy() allows the analyst to collapse thousands of individual "ServiceStarted" or "ScheduledTaskRegistered" events into a distinct list based on a specific field, such as aid (Agent ID) or ComputerName.

For this specific scenario, a hunter would query for the specific task name or the command-line arguments associated with the 5-minute execution interval and then pipe those results into | groupBy([aid]). This effectively filters out the noise of repeated executions from the same machine, presenting the hunter with a clear, unique count of every host that has been compromised. This efficiency is vital during the "Scope" phase of an investigation. By utilizing groupBy(), an analyst can quickly determine if the infection is localized to a single department or has spread globally across the enterprise, allowing for a prioritized remediation strategy using Bulk RTR or other containment measures.

The CrowdStrike Query Language (CQL) allows hunters to perform granular filtering of telemetry to isolate specific behaviors. In this query, the initial statement targets #event_simpleName=UserLogon, which records every time a user authenticates to a host. The filter RemoteAddressIP4=* ensures the query only looks at logons that involve a network component (remote logons), as local console logons typically do not have a remote IP associated with them.

The core logic of the query is the !cidr function. By listing the standard private and non-routable IP ranges (10/8, 172.16/12, 192.168/16, etc.) and applying the logical NOT operator (!), the query effectively strips away all "noise" from the internal network. What remains are logons originating from external IP addresses . The final pipe to ipLocation is used to add geographic context to these external sources. This type of search is fundamental to Hunting Methodology when looking for evidence of credential theft or external actors moving into the environment. While a similar search could be performed for NetworkConnectIP4 events, focusing on UserLogon specifically identifies successful (or attempted) authentication, which is a much higher-value indicator of a potential breach than simple network traffic. Understanding how to exclude internal subnets is a mandatory skill for any Falcon Hunter to avoid being overwhelmed by legitimate internal administrative traffic.

The ContextProcessld_readable field in a DNS Request event points to the responsible process. The ContextProcessld_readable field is the readable representation of the process identifier for the process that initiated the DNS request. It can be used to identify which process was communicating with a specific domain or IP address. The TargetProcessld_decimal, ContextProcessld_decimal, and ParentProcessId_decimal fields do not point to the responsible process.

Understanding the relationship between different Process IDs is a fundamental requirement for mastering Event Search in the Falcon platform. In the telemetry stream, the TargetProcessId is the unique identifier assigned to a process when its creation is recorded in a ProcessRollup2 or SyntheticProcessRollup2 event. It represents the "Identity" of that specific process instance. On the other hand, the ContextProcessId represents the "Actor"—the process that is currently performing an action recorded in a telemetry event.

When a parent process spawns a child process, the Falcon sensor generates a ProcessRollup2 event for the new child. In this specific event record, the TargetProcessId refers to the newly created child. However, because the parent is the one performing the action of "spawning," the ContextProcessId for that specific rollup event will be the ID of the parent. Therefore, the ContextProcessId found in the child's start event will be the same value as the TargetProcessId that was assigned to the parent when it first started. This logic is what allows hunters to programmatically rebuild process trees using CrowdStrike Query Language (CQL) . By joining events where the ContextProcessId of one event matches the TargetProcessId of another, analysts can trace an execution chain from a high-level parent (like explorer.exe) all the way down to the final malicious payload, ensuring full visibility into the attack's lineage.

To build effective and high-performance queries in Advanced Event Search , a hunter must have access to a definitive map of the telemetry captured by the sensor. The Falcon console docs serve as the primary repository for this information, specifically housing the Events Data Dictionary (also known as the Events Full Reference). This documentation is indispensable because it provides the technical specifications for every event type and field indexed within the platform.

Within the documentation, an analyst can find descriptions for fields like aid (Agent ID), aip (External IP), and the complex relationships between various Process IDs. Understanding these fields is critical for Hunting Analytics , as it prevents common errors, such as using a field that contains strings for a mathematical operation or confusing the ComputerName with the UserSid. Furthermore, the documentation often includes examples of how these fields are used in CrowdStrike Query Language (CQL) , allowing hunters to adapt existing templates to their specific needs. Relying on the official console documentation ensures that the hunter is using the most up-to-date definitions as new event types are added or existing ones are refined by CrowdStrike’s engineering teams, maintaining the accuracy and reliability of their investigations.