Autonomous Threat Hunting

GLOSSARY

Autonomous threat hunting glossary

The vocabulary of AI-driven hunting, in plain language.

In one paragraph

This glossary defines the terms used across the guide. Definitions are short and practical; where a term comes from a published framework, the framework is linked. Terms are listed alphabetically, and each has its own anchor so other pages can link to it.

Guide updated September 2026 · Autonomous Threat Hunting editors

A

Agent
Software that takes a goal, chooses steps and tools, and acts across systems to reach it, checking its own progress. In hunting, agents plan and run queries and summarize findings.
Agentic threat hunting
Threat hunting in which software agents plan and run the steps of a hunt, such as choosing queries, reading results and deciding what to check next, rather than only suggesting them to an analyst. In this guide it covers Levels 2 to 4 of the autonomy model.
Approval gate
A point in an automated workflow where the system stops until a named person approves or rejects the next step. Common gates sit before a detection is deployed and before a response action runs.
ATT&CK coverage map
A view showing which MITRE ATT&CK techniques a set of detections or hunts is mapped to. A mapping records what the logic is meant to address, not proof that it would find the technique in your data; check which ATT&CK version the map uses. Source
Autonomy level
In this guide, one of five levels (0 to 4) describing how much a hunting system does without being asked. An editorial model, not an industry standard.

B

Backtesting
Running a new detection rule against historical data before release to estimate how often it would fire and whether it would have caught known activity.

C

Continuous hunting
Hunting that runs on a schedule or on the arrival of new intelligence, without a person requesting each hunt. Level 3 in this guide's autonomy model.
Corroboration
Checking a hunt hit against other data sources to see whether they support or contradict it, before presenting it to a person.

D

Data lake
A store for large volumes of raw data, often in cloud object storage or a warehouse, that security teams query alongside a SIEM for some data.
Detection drift
The gradual loss of a detection's effect when the data sources, schemas or field names beneath it change. Rules promoted from hunts need retesting whenever their sources change.
Detection promotion
Turning the logic of a successful hunt into a standing detection rule, usually after a backtest and a review.
Detection rule
Logic that runs continuously on incoming data and raises an alert when a defined pattern appears.
Detection-as-code
Managing detection rules as code in version control, with review, testing and automated deployment, instead of editing them by hand in a console.
Directed hunt
A hunt that starts from a hypothesis a person supplies, after which the system plans and runs the queries. Level 2 in this guide's autonomy model.
Dry run
A mode in which an automated hunt shows the queries it would run and their expected scope without executing them or changing anything. Useful for checking scope and cost before a hunt runs for real.

E

EDR
Endpoint detection and response: software on laptops and servers that records activity and can contain a host.

F

False positive
A result that looks malicious but turns out to be benign. In autonomous hunting it applies both to findings handed to a reviewer and to detections promoted from hunts.
Running one logical query across several data platforms where the data already lives, instead of copying the data into one store first.

H

Human in the loop
A design in which a person must review or approve defined steps, such as confirming a finding or approving an action, before the system proceeds.
Hunt library
The collection of hunts a system can run on a schedule or on demand, usually grown from intelligence and past findings. Each entry needs an owner and a review date.
Hunt report
The record an autonomous system produces for one hunt: the hypothesis, the data sources and time range, the exact queries, the findings with their corroboration, what was not checked and the proposed next step.
Hypothesis
A testable statement about attacker behavior that a hunt sets out to confirm or rule out, naming the data needed to test it.

I

Indicator of compromise (IOC)
A specific artifact of malicious activity, such as a file hash, domain or IP address. Useful but short-lived compared with behaviors.

L

Least privilege
Giving an identity only the access it needs for its task. For a hunting agent, this usually means read-only access limited to the data sources its agreed hunts require.

M

MCP
Model Context Protocol, an open protocol that lets AI applications connect to external tools and data sources. Some hunting products state MCP support.
MITRE ATT&CK
A public knowledge base of adversary tactics and techniques maintained by MITRE. Enterprise v19.2 lists 15 tactics. Source

O

OCSF
Open Cybersecurity Schema Framework, an open schema for normalizing security event data so events from different sources share field names and structure.

P

Playbook
A written sequence of steps for a recurring task, such as hunting for one behavior or responding to one kind of incident. Automated systems may run playbooks as reusable templates.

Q

Query budget
A limit on how many queries, how much data scanned or how much compute an automated system may use on a data platform in a period, with a defined behavior when the limit is reached.

R

Retrohunt
Searching historical data for activity that matches new intelligence or a new rule, to find past intrusions or test a rule before deployment.

S

Service identity
A dedicated non-human account or credential that a system uses to reach a platform, so its activity can be logged, limited and revoked separately from people's accounts.
SIEM
Security information and event management: a platform that collects, stores and searches security logs. In this guide, SIEMs appear as data platforms that hunting systems read from.
Sigma
A generic and open signature format for detection rules, with more than 3000 community rules and tools that convert rules into platform query languages. Source
Staged action
A response step, such as isolating a host or revoking a session, that a system prepares but does not run until a person approves it.
STIX/TAXII
Standards for describing threat intelligence (STIX) and exchanging it between systems (TAXII).

T

Tactic (ATT&CK)
In MITRE ATT&CK, the adversary's goal at a stage of an intrusion, such as Initial Access or Credential Access. Enterprise v19.2 lists 15 tactics, each with an ID such as TA0006. Source
Technique (ATT&CK)
In MITRE ATT&CK, how an adversary achieves a tactic's goal. ATT&CK v19 lists 222 Enterprise techniques, and hunts and detections are usually mapped at this level. Source
Threat hunting
Proactively searching for attacker activity that existing detections have not flagged, starting from a hypothesis.
Threat intelligence
Information about adversaries, their behavior and their tools, from advisories, feeds and investigations, used to decide what to look for.
TTP
Tactics, techniques and procedures: how an adversary operates. Hunting on TTPs lasts longer than hunting on indicators alone.