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Key Facts: SentinelOne THP Exam

S1-301

Exam Code

SentinelOne

Not disclosed

Passing Score

SentinelOne

Advanced

Difficulty Level

SentinelOne University

MCQ + Scenarios

Exam Format

SentinelOne

S1 University

Exam Delivery

SentinelOne

40-60 hours

Recommended Study

OpenExamPrep estimate

The S1-301 Threat Hunting Professional is SentinelOne's advanced practitioner certification for security analysts and threat hunters who operate the Singularity XDR platform. It builds on the CTP (S1-201) foundation and validates hands-on expertise with Deep Visibility, PowerQuery-based hunt queries, STAR automated detection rules, and attack narrative investigation using Storyline.

Sample SentinelOne THP Practice Questions

Try these sample questions to test your SentinelOne THP exam readiness. Each question includes a detailed explanation. Start the interactive quiz above for the full 100+ question experience with AI tutoring.

1In SentinelOne's threat hunting methodology, what is the FIRST step a hunter should take before querying Deep Visibility?

A.Formulate a hypothesis based on threat intelligence or anomaly observations

B.Configure a STAR rule to alert on suspicious activity

C.Isolate all endpoints that show elevated CPU usage

D.Export all process events from the Singularity Data Lake

Explanation: SentinelOne's six-step threat hunting methodology begins with hypothesis formation. A hunter constructs an educated guess—often driven by threat intel, MITRE ATT&CK TTPs, or baseline anomalies—before issuing any Deep Visibility queries. This structured approach prevents aimless data dredging and focuses analyst effort on high-value investigative paths.

2Which SentinelOne component provides continuous, real-time collection of process, network, file, registry, and DNS telemetry that hunters query during an investigation?

A.Singularity Ranger (Network Discovery)

B.Deep Visibility

C.Remote Script Orchestration

D.Singularity Identity

Explanation: Deep Visibility is SentinelOne's EDR data collection and querying engine. It continuously records granular OS-level events—process creation, network connections, file system changes, registry modifications, DNS lookups, and more—and stores them in the Singularity Data Lake, making this telemetry searchable for threat hunters via the console or API.

3A threat hunter writes the following Deep Visibility PowerQuery: `| from process | where SrcProcName = 'powershell.exe' AND NetworkUrl != null | group by NetworkUrl`. What is the PRIMARY analytical goal of this query?

A.Identify PowerShell processes that establish outbound network connections, grouped by destination URL

B.Count all DNS queries made by any process in the last 24 hours

C.List all registry keys modified by PowerShell since agent installation

D.Retrieve memory dumps for PowerShell processes calling external hosts

Explanation: This PowerQuery pipes process events through a filter selecting PowerShell as the source process name with a non-null NetworkUrl, then groups results by the destination URL. The goal is to surface all unique external hosts that PowerShell processes contacted—a classic hunt for C2 beaconing or data exfiltration via PowerShell. The `group by` aggregation collapses duplicate connections to the same host for easier analysis.

4What is the Storyline™ ID (STID) used for during a SentinelOne threat hunting investigation?

A.It uniquely identifies a sensor agent installed on an endpoint

B.It is the unique identifier assigned to each STAR rule in the management console

C.It is the hash of the primary malicious file detected during an incident

D.It is a machine-built identifier that links all related processes, files, threads, and events belonging to the same attack narrative

Explanation: SentinelOne's patented Storyline™ technology automatically assigns a Storyline ID (STID) to correlate all events—process creations, file writes, network connections, registry changes—that belong to the same attack chain. A hunter can filter Deep Visibility by a single STID to instantly retrieve the full attack narrative without manually piecing together parent-child process relationships.

5When creating a STAR (Storyline Active Response) rule from a validated Deep Visibility query, which response action can STAR automatically execute on a matching endpoint WITHOUT requiring analyst interaction?

A.Delete the endpoint agent and reinstall with a clean policy

B.Open a ServiceNow ticket and assign it to the on-call analyst

C.Kill the matching process and optionally network-quarantine the endpoint

D.Upload a full memory image to the Singularity Data Lake for later analysis

Explanation: STAR rules can be configured with automated response actions including killing the matching process, quarantining the network at the endpoint level, or remediating/rolling back changes. These actions are executed by the SentinelOne agent on the endpoint when the STAR rule's telemetry match occurs, enabling machine-speed response without analyst approval for each event.

6A hunter observes an alert tagged with MITRE ATT&CK technique T1059.001. What behavior should the hunter focus on when pivoting to Deep Visibility?

A.Registry Run key persistence mechanisms added by a scheduled task

B.DNS tunneling via high-frequency TXT record queries

C.Pass-the-Hash lateral movement across SMB connections

D.PowerShell execution potentially used for command and scripting interpreter abuse

Explanation: MITRE ATT&CK T1059.001 is 'Command and Scripting Interpreter: PowerShell'. Alerts tagged with this technique indicate PowerShell was used as an execution mechanism. In Deep Visibility, the hunter should pivot to process events where SrcProcName or TgtFilePath involves PowerShell, examining command-line arguments, parent processes, and any subsequent network or file activity.

7In a SentinelOne Deep Visibility PowerQuery, what does the pipe character (`|`) accomplish syntactically?

A.It introduces a comment block that is ignored by the query engine

B.It specifies a logical OR condition between two filter expressions

C.It chains query commands so the output of one command becomes the input of the next

D.It defines the time range boundary for the query window

Explanation: In SentinelOne PowerQuery, the pipe (`|`) is used to chain commands—similar to Unix shell pipes. The results from one stage flow into the next, enabling hunters to filter, transform, group, sort, or summarize data in a multi-step pipeline. For example: `| from process | where SrcProcName = 'cmd.exe' | group by SrcProcCmdLine | sort count desc`.

8An analyst notices several endpoints connecting to the same external IP on port 4444 at regular 60-second intervals. Which threat hunting concept BEST describes this behavioral pattern?

A.Lateral movement via SMB relay

B.DNS amplification — using multiple DNS resolvers to saturate the target

C.Credential dumping via LSASS memory reads

D.Beaconing — a C2 callback pattern characterized by regular, periodic outbound connections

Explanation: Regular, periodic outbound connections to a fixed external IP on a common post-exploitation port (4444 is the default Metasploit reverse shell port) is the classic signature of C2 beaconing. Threat hunters look for this IOA (Indicator of Attack) by grouping network events by destination IP and calculating connection intervals, using Deep Visibility aggregations to surface suspicious periodicity.

9Which SentinelOne platform feature allows a threat hunter to turn a validated Deep Visibility query into a persistent, fleet-wide detection rule that triggers near-real-time alerts whenever new telemetry matches?

A.Singularity Ranger scan policy

B.Watchlist-based IOC import via CSV upload

C.STAR (Storyline Active Response) custom detection rule

D.Remote Script Orchestration scheduled task

Explanation: STAR (Storyline Active Response) allows hunters to convert a Deep Visibility query directly into a persistent detection rule. The rule continuously evaluates incoming telemetry from the Singularity Data Lake against the query logic, firing near-real-time alerts and optionally automated response actions across the entire managed fleet whenever the condition is matched.

10A hunter wants to find all parent-child process relationships where `cmd.exe` spawns `net.exe` across the enterprise. Which Deep Visibility event type and field combination is MOST relevant?

A.DNS event type, filtering on `DnsQuery` containing 'net'

B.File event type, filtering where `FilePath` ends with 'net.exe'

C.Network event type, filtering where `SrcProcName = 'net.exe'`

D.Process event type, filtering where `SrcProcName = 'cmd.exe'` AND `TgtFilePath` contains 'net.exe'

Explanation: In SentinelOne Deep Visibility, process creation events capture parent-child relationships. `SrcProcName` is the parent (source) process name and `TgtFilePath` or `TgtProcName` is the child process being spawned. Filtering on `SrcProcName = 'cmd.exe'` with a target of 'net.exe' surfaces all instances where the command shell spawned the net utility, a common lateral movement and reconnaissance pattern (T1087, T1018).

About the SentinelOne THP Exam

The SentinelOne Threat Hunting Professional (THP, S1-301) validates advanced skills in proactive threat hunting using the Singularity platform. Candidates must master Deep Visibility PowerQuery, STAR rule creation, MITRE ATT&CK technique mapping, behavioral IOC detection, and SIEM/SOAR integration workflows.

Assessment

Question count not published by the exam provider

Time Limit

Not publicly disclosed

Passing Score

Not publicly disclosed

Exam Fee

Bundled with SentinelOne University Premium (SentinelOne)

SentinelOne THP Exam Content Outline

~20%

Threat Hunting Methodology

Hypothesis formation, hunt lifecycle, dwell time, reactive vs proactive hunting, maturity models, documentation

~25%

Deep Visibility and PowerQuery

Event types, PowerQuery pipeline syntax, Storyline ID pivoting, Enhanced vs Legacy DV, fleet-wide querying

~20%

MITRE ATT&CK Mapping and Attack Analysis

Tactic and technique identification, LOLBin abuse, process chain analysis, credential and lateral movement TTPs

~15%

Behavioral IOCs and Anomaly Detection

IOA vs IOC, beaconing, process hollowing, DLL sideloading, fileless malware, stack counting, baselining

~10%

STAR Rules and Automated Detection

Creating, tuning, and scoping STAR rules; response actions; exclusion management; false-positive reduction

~10%

SIEM/SOAR Integration and Investigation Workflows

API-based SIEM integration, SOAR playbook design, alert enrichment, RSO, network quarantine, deep investigation

How to Pass the SentinelOne THP Exam

What You Need to Know

Passing score: Not publicly disclosed
Assessment: Question count not published by the exam provider
Time limit: Not publicly disclosed
Exam fee: Bundled with SentinelOne University Premium

Keys to Passing

Work through all 100 available questions
Review every answer and explanation
Track weak areas and revisit them
Use our AI tutor for tough concepts

SentinelOne THP Study Tips from Top Performers

1Master PowerQuery syntax: practice from/where/group by/sort/limit pipelines in Deep Visibility before the exam

2Know the six-step SentinelOne threat hunting methodology: hypothesis → query → analyze → pivot → operationalize → document

3Learn the key process event fields: SrcProcName, TgtFilePath, SrcProcCmdLine, SrcProcParentName, SrcProcIntegrityLevel, StorylineId

4Study LOLBin abuse: certutil, rundll32, mshta, regsvr32, msiexec, wmic, schtasks, powershell — know the MITRE T-codes and behavioral indicators for each

5Understand when to use STAR rules vs Watchlists vs Exclusions — they serve different purposes in the detection lifecycle

6Practice pivoting: given a Storyline ID or suspicious IP, know how to expand the investigation across the fleet

Frequently Asked Questions

What is the SentinelOne THP (S1-301) certification?

The SentinelOne Threat Hunting Professional (THP), exam code S1-301, is an advanced practitioner certification for security analysts who use the SentinelOne Singularity platform for proactive threat hunting. It validates skills in Deep Visibility PowerQuery, STAR rule creation, MITRE ATT&CK mapping, and behavioral anomaly detection.

What is the difference between SentinelOne CTP (S1-201) and THP (S1-301)?

The CTP (S1-201) covers foundational platform administration—sensor deployment, policy management, group configuration, and admin workflows. The THP (S1-301) is the advanced threat hunting credential focused on investigation: Deep Visibility queries, PowerQuery analysis, STAR automated detection rules, MITRE ATT&CK technique mapping, and incident investigation workflows.

How do I access SentinelOne University for the THP certification?

SentinelOne University is available at university.sentinelone.com. The THP learning path is included with SentinelOne University Premium enrollment. Contact SentinelOne at training@sentinelone.com or through your account representative for enrollment options and current pricing.

What is SentinelOne Deep Visibility?

Deep Visibility is SentinelOne's EDR data collection and threat hunting engine. It continuously records endpoint telemetry—process creation, file system activity, network connections, registry changes, DNS queries, and more—in the Singularity Data Lake. Hunters query this data using the console's search interface or PowerQuery, SentinelOne's advanced multi-step query language.

What are STAR rules in SentinelOne?

STAR (Storyline Active Response) rules allow hunters to convert validated Deep Visibility queries into persistent, automated detection rules. STAR continuously evaluates new telemetry from the Singularity Data Lake against the rule logic, firing near-real-time alerts and optionally triggering automated response actions (such as killing a process or isolating an endpoint) when the condition matches.

Is hands-on SentinelOne experience required for the THP exam?

Yes. The THP is an advanced practitioner certification that tests applied knowledge of the Singularity platform. Candidates without hands-on Deep Visibility querying and STAR rule experience will find the exam challenging. SentinelOne University's Threat Hunting learning path provides the required training, and practical lab experience with the platform is strongly recommended.