Threat-hunting expedition

As explained in Cyber Threat Hunting

A threat-hunting expedition is a bounded investigation in which a threat hunter tests for evidence of a suspected threat or attack.

A threat-hunting expedition is a bounded, hypothesis-driven investigation that proactively tests whether an attack or threat has evaded existing detection. It turns a defined hunting play into evidence-gathering work: search available data, interpret clues, and determine whether the hypothesis is supported. section 2.1 section 1.5

Preparation gives an expedition direction. Define the hypothesis, scope, threat landscape, validation approach, and required data and tools in a hunting play before execution. This structure makes hunts repeatable and measurable while leaving room to adjust techniques when data, access, parsing, or search performance is limited. section 2.1 section 1.5

During execution, hunters typically:

• Translate planned procedures into an initial set of searches. section 3.2.2
• Follow evidence through events and related systems, building a threat-execution timeline. section 3.0
• Open or update an incident case when findings require incident-response involvement. section 3.2.2 section 4.3.2
• Record findings, data-collection gaps, and recommendations that improve later hunts and detections. section 4.6

Tracing a malicious document

A suspicious Word attachment that bypasses endpoint controls becomes the hypothesis: similar activity may exist elsewhere. Search Sysmon process-creation events for Word spawning PowerShell, then pivot from a created .ps1 file to related cscript, PowerShell, cmd, and rundll32 events. Arrange the resulting events by time to reconstruct the execution chain and identify the affected endpoint. section 3.1.1 section 3.1.4

Figure 3.9 Threat-hunting process: Execution phase

Use the execution-phase diagram to orient the transition from planned searches to evidence, incident handling, and scoped findings. section 3.2.2

An expedition need not prove its hypothesis to be useful. A negative or inconclusive result can reflect an absent threat, incomplete environmental context, missing data, unsuitable techniques, or unfamiliar technology. Discuss those constraints, research relevant TTPs, and seek alternate data sources rather than treating the outcome as failure. section 1.5

Expeditions also produce operational value beyond confirmed attacks: vulnerabilities, configuration problems, detection-rule ideas, and information for partner teams. Their results can be tracked through counts of expeditions, incidents, vulnerabilities, configuration findings, monitoring rules, and support provided to incident work. section 12.5.3 section 4.6

How Cyber Threat Hunting covers it

How deep it goes

Details preparation, searches, evidence pivots, timelines, incident escalation, and post-hunt improvement; defers deeper scoping in the initial scenario.

Examples

Traces a malicious Word attachment through Sysmon events into PowerShell, cscript, cmd, rundll32, files, and a timeline.

What it assumes

Assumes familiarity with the environment and threat landscape while introducing a first hunt through a simple endpoint scenario.

What you can do after

Apply it via Sysmon and searchable event stores to test hypotheses, assemble evidence, and escalate incidents.

How it connects

Connects hunting plays, hypotheses, Sysmon, threat intelligence, incident response, threat modeling, and risk management.

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Related concepts

• threat modeluses · A threat model is a structured analysis or representation of a system’s relevant threats, adversaries, assets, attack paths, assumptions, and possible mitigations.
• vulnerabilities uncoveredproduces · The total count of vulnerabilities discovered through the threat-hunting process.
• security incidents uncoveredproduces · The count of security incidents discovered by threat hunting and referred for incident response.
• statisticsused by · Statistics is the discipline and set of methods for collecting, summarizing, analyzing, and interpreting data, including numerical descriptions used to characterize observations and support inference.

This explainer was generated by Manning's knowledge graph from the text of Cyber Threat Hunting. The section links point to the parts of the book it draws on.