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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →A cyber threat hunt is a proactive, human-led search for adversary behavior that existing controls may have missed. A practical hunt moves through five steps: define its purpose and scope, create a testable hypothesis, prepare the necessary telemetry, evaluate and refine the evidence, then act on the findings and feed them back into security operations. This is a useful working sequence, not a universal standard; published SANS models use different numbers of stages.
1. Define the purpose, scope, and priorities
Start with a question the hunt is meant to answer. A broad instruction to “look for suspicious activity” is difficult to test and likely to produce an unfocused search. Identify the environment and the threat scenario you want to examine, then set boundaries for the work.
Set the boundaries
- Mission question: What behavior or possible compromise are you trying to confirm or rule out?
- Assets and users: Which endpoints, identities, cloud services, networks, or business units are in scope?
- Environment and time window: Which systems and period can you investigate with available data?
- Priority: Why is this hunt worth doing now? Consider business impact, threat intelligence, known exposure, and whether the environment has enough visibility to investigate.
These choices should reflect the organization’s context. A high-impact system or a credible threat lead may justify attention, but a hunt is only useful if the relevant activity can be examined in the data you have.
2. Create a testable hypothesis
Turn the mission question into a statement about what an adversary may be doing and where evidence of that behavior should appear. A useful hypothesis is actionable: it points to activity an analyst can search for and gives the hunt a way to find supporting or disconfirming evidence.
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Threat intelligence, asset context, and the MITRE ATT&CK tactics and techniques can help shape the hypothesis. ATT&CK provides a shared vocabulary for adversary behaviors; it is a behavior model, not proof that a particular technique occurred. MITRE’s TTP-based hunting approach uses ATT&CK techniques to search for behavior rather than relying only on static indicators.
Make the hypothesis falsifiable
Specify the behavior, the systems or identities where it might occur, and the evidence you would expect to find. For example, a hunt might ask whether activity associated with a suspected technique appears on a defined group of endpoints during a particular time window. The exact query depends on the telemetry and tools available; avoid treating a missing result as proof that the behavior did not happen if the needed data was not collected or retained.
3. Prepare telemetry, tools, and enrichment
Before searching, confirm that the data needed to test the hypothesis exists, covers the relevant assets and time window, and can be queried. Hunting depends on searchable visibility. If the required evidence is unavailable, record that as a visibility gap rather than implying the threat has been ruled out.
| Data source | What it can contribute |
|---|---|
| Endpoint process and file events | Evidence about activity and changes on endpoints. |
| Authentication and identity logs | Evidence related to account and identity activity. |
| DNS and network flow or packet data | Network-related evidence that can support investigation of behavior and connections. |
| Cloud activity logs | Evidence about activity in cloud environments. |
| Memory and other forensic data, when available | Additional material for investigation where the hypothesis and collection capability warrant it. |
The appropriate combination depends on the hunt. Validate data coverage, query capability, enrichment, and analyst tools before interpreting search results. Endpoint, network, cloud, and identity analysis are all relevant areas of threat-hunter work, but not every hunt requires every source.
4. Evaluate the evidence and refine the hunt
Search for patterns and anomalies that match the hypothesis, then correlate relevant events into a coherent account of what may have happened. Map observed behaviors to ATT&CK where that helps communicate the activity, and keep track of both supporting and disconfirming evidence.
Separate evidence from interpretation
- Record what was observed, where it appeared, and which time period it covers.
- Distinguish a confirmed event from an analyst’s interpretation of that event.
- Note gaps in collection or coverage that limit what the hunt can establish.
- Assess whether the evidence supports the hypothesis, contradicts it, or leaves it unresolved.
If the evidence does not support the hypothesis, determine whether it was meaningfully tested with the available data. Refine the hypothesis or develop a new one when warranted; a hunt is iterative, not a one-off query. A negative result from incomplete telemetry should not be presented as a definitive absence of adversary activity.
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5. Act, document, and feed findings back
Report the outcome in a way that helps security and incident-response teams decide what to do next. Include affected assets, relevant indicators, the suspected attack path, confidence, supporting evidence, and important data limitations.
Choose the operational next step
- Confirmed malicious activity: Coordinate containment and remediation with the incident-response function.
- Suspicious but unconfirmed activity: Document the evidence and uncertainty, and identify what further investigation or visibility would help resolve it.
- No supporting evidence found: State the scope and data examined so the result is not mistaken for proof that no threat exists.
- Visibility gap identified: Record the missing telemetry or coverage as an improvement need.
Feed useful results into security operations: improve SIEM rules or EDR policies, update relevant intelligence, address visibility gaps, and use the findings to set priorities for the next hunt. The objective is not only to find activity; it is also to improve the organization’s ability to detect, investigate, and respond.
How MITRE ATT&CK fits into a hunt
ATT&CK helps analysts describe adversary tactics and techniques in a common framework. Use it to shape a behavior-based hypothesis, organize observations, and communicate which behaviors evidence may indicate. A technique mapping is not, by itself, confirmation of an intrusion, and searching only for known indicators can miss behavior that does not match those indicators.
MITRE’s TTP-based hunting method is operating-system agnostic and combines ATT&CK techniques with a hunting analysis space to guide behavior-focused searches. In practice, the technique helps frame what to investigate; local telemetry and evidence determine what can actually be concluded.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How the five-step sequence relates to other models
There is no single required number of threat-hunting stages. SANS describes a separate practical model with six stages: purpose, scope, equip, plan/review, execute, and feedback. The five-step sequence here combines the work into a compact process for readers, while the six-stage model separates planning and review from execution.
SANS also uses a five-level Hunting Maturity Model to describe organizational capability. These are maturity levels, not steps in a single hunt:
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| Level | Name | What it describes |
|---|---|---|
| HMM 0 | Initial | Mostly automated alerting. |
| HMM 1 | Minimal | Indicator searches; hunting begins when the organization moves beyond simply waiting for alerts. |
| HMM 2 | Procedural | Established analysis procedures. |
| HMM 3 | Innovative | Development of new procedures. |
| HMM 4 | Leading | Automation of successful procedures. |
To compare hunt approaches, useful dimensions include where the hypothesis came from (such as intelligence, an anomaly, exposure, or an incident lead), which behavior model is used, the depth and time range of telemetry, the role of automation and analyst judgment, how results are validated, and how findings become detections or remediation.
What threat hunting can contribute
Hunting is intended to find behavior that existing controls may miss and to turn what analysts learn into response, remediation, and better detection. In a SANS survey of 494 organizations, as reproduced in a Sqrrl document hosted by NIST, 52% of respondents said hunting techniques found previously undetected threats, 74% said hunting reduced their attack surfaces, and 59% said it improved the speed and accuracy of responses. The cited passage does not state the survey year, so these figures should not be read as current measurements or guarantees of what any organization will achieve.
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