Advanced Threat Hunting Techniques and How Investigations Work

An alert is only one reason to investigate. Advanced threat hunting starts with a testable hypothesis about attacker behaviour, then uses endpoint, identity, network and cloud telemetry to look for evidence. Analysts investigate activity that automated detection may not fully explain, validate suspicious patterns against the wider environment and escalate confirmed threats for response.

Threat hunting complements automated detection rather than replacing it. A hunt may begin with threat intelligence, an unusual change in normal activity or concern about a high-risk asset. Whatever the trigger, an isolated match is a lead rather than proof of malicious activity.

How Does Threat Hunting Work?

Threat hunting tests whether suspicious or potentially malicious behaviour is present in an organisation’s environment. Threat intelligence can provide context about actors and techniques, while incident response becomes relevant when an event requires action.

These activities support one another but serve different purposes. A suspicious login, for example, may prompt a hunt to establish whether it forms part of wider activity. If evidence confirms an active threat, the investigation can move into containment, eradication and recovery.

Use Intelligence As Context

Indicators of compromise (IOCs) are artefacts associated with possible compromise, such as malicious domains, IP addresses or file hashes. Indicators of attack (IOAs) focus on suspicious behaviour, while tactics, techniques and procedures (TTPs) describe how threat actors operate.

An indicator should not be treated as a conclusion. Its value depends on factors such as context, reliability and its relationship to other activity. This is why threat intelligence quality matters more than simply accumulating more feeds.

Security teams should correlate external intelligence with internal endpoint, identity, firewall and cloud records. When multiple sources support the same hypothesis, analysts have stronger grounds for deciding whether further investigation or response is necessary.

How Do Hypothesis-Driven Threat Hunts Work?

A hypothesis gives hunters a testable question about possible threat activity. Analysts examine relevant telemetry and determine whether the evidence suggests normal behaviour, a detection gap, inadequate visibility or activity requiring further action.

A useful hypothesis identifies:

• The behaviour being tested
• The systems, users or applications involved
• The telemetry required
• Evidence that would support or challenge the hypothesis
• The next action if suspicious activity is confirmed

For example, intelligence about attackers abusing legitimate administrative software could become a question about whether the organisation is seeing unusual use of those tools. Analysts can then examine account, device and execution data without assuming that the activity is malicious before evaluating the evidence.

Map Hunts To Adversary Behaviour

MITRE ATT&CK can provide a structured way of organising adversary tactics and techniques. Hunters can select relevant behaviours, determine which telemetry could expose them and assess whether existing security controls provide adequate visibility.

Mapping alone does not prove that an organisation can detect or investigate a technique. Security teams should establish whether the necessary data exists and whether findings can translate into action.

This is where threat hunting can feed directly into detection engineering. As security operations evolve, effective detection engineering becomes increasingly important because discoveries from investigations need to become repeatable detection capability.

What Are The Main Threat Hunting Models?

Security teams can use different hunting approaches depending on the trigger, evidence available and business risk.

Structured Hunts

A structured hunt starts with a defined hypothesis, often informed by threat intelligence or known adversary behaviour.

A team investigating credential theft, for example, could examine identity records for suspicious sign-ins followed by unusual access. Because the investigation begins with a specific question, teams can document its queries, evidence and outcomes for future hunts.

Unstructured Hunts

An unstructured hunt starts with an anomaly rather than a predefined attacker scenario. An unexpected server connection might lead analysts to examine preceding endpoint events, identity activity and network traffic.

The challenge is context. Unusual activity is not necessarily malicious, so analysts need enough telemetry to evaluate alternative explanations.

Situational Hunts

A situational hunt concentrates on an asset or emerging concern that carries particular risk. A critical server, major technology change or emerging threat may justify focused investigation.

These models can overlap. An anomaly discovered during an unstructured hunt may create a more specific hypothesis for a structured investigation.

How Can Threat Hunting Detect Living-Off-The-Land & Fileless Activity?

Living-off-the-land activity involves legitimate system tools being used for malicious purposes. Fileless techniques can involve scripts, memory, legitimate utilities or execution methods that may not depend on a conventional malicious file stored on disk.

The challenge is that administrators also use built-in utilities, scripting environments and remote management tools. Hunters therefore need to examine behaviour and context rather than relying on tool names.

Analysts might compare process execution, related sign-ins, user identity, device history and subsequent network connections. An administrative tool becomes a stronger investigative lead when its execution differs from the account or device's expected behaviour.

Where appropriate telemetry exists, investigators can also examine script activity, unusual process relationships and related events across devices. Where memory acquisition is available, memory analysis may provide additional evidence, although its usefulness depends on the circumstances and available tooling.

Correlate Endpoint, Identity & Network Telemetry

Security information and event management (SIEM) helps organisations centralise security data, while endpoint telemetry provides another perspective on device activity.

CyberOne also publishes dedicated guidance on Microsoft Sentinel and expert threat detection for organisations building security operations around Microsoft technology.

Correlation allows hunters to assess sequences rather than isolated events. A suspicious login becomes more useful when analysts can connect it to endpoint activity, privilege changes or network behaviour.

The same principle should inform detection improvements. New rules need to provide useful visibility without overwhelming analysts with noise. CyberOne’s guidance on reducing SIEM alert fatigue explores this wider operational challenge.

Turn Hunt Findings Into Better Security Decisions

A hunt should create value beyond determining whether one hypothesis was correct.

Teams should document the investigation, data sources, findings and legitimate explanations identified along the way. Confirmed findings can inform new detection logic, improved logging, access controls and future hunts.

This turns hunting into a feedback loop between investigation, detection engineering and incident response rather than an isolated technical exercise.

For organisations without the internal capacity to maintain this work consistently, managed detection and response can provide another operating model. CyberOne’s guide to managed detection and response services explores that approach.

Where Does MXDR Fit Into Threat Hunting?

CyberOne’s Managed Extended Detection & Response guidance provides further context for organisations considering managed security operations.

Managed support may be relevant when investigation competes with platform management, governance and other security priorities. The important decision is not simply whether an organisation performs threat hunting, but how findings move into detection, response and security improvement.

Organisations comparing potential approaches can also explore the five pillars of effective MXDR and CyberOne’s MDR and MXDR buying factors.

Make Threat Hunting Part Of Security Decision-Making

Advanced threat hunting is most useful when it connects investigation with broader security decisions. Leaders should make sure analysts have appropriate telemetry, clear ownership and a defined route for turning findings into action.

Security operations also need to connect with identity, infrastructure and business-critical system owners. This allows findings to influence detection engineering, access decisions and incident response rather than remaining inside individual investigations.

The goal is a repeatable process: form a hypothesis, examine the evidence, reach a defensible conclusion and use what was learned to strengthen the next investigation.

Discuss how threat hunting and managed detection and response could support your organisation’s security priorities with CyberOne.

Frequently Asked Questions