| name | implementing-threat-intelligence-lifecycle-management |
| description | Implement a structured threat intelligence lifecycle encompassing planning, collection, processing, analysis, dissemination, and feedback stages to produce actionable intelligence for organizational decision-making. |
| domain | cybersecurity |
| subdomain | threat-intelligence |
| tags | ["threat-intelligence","lifecycle","intelligence-cycle","collection","analysis","dissemination","strategic-intelligence","cti-program"] |
| version | 1.0 |
| author | mahipal |
| license | Apache-2.0 |
Implementing Threat Intelligence Lifecycle Management
Overview
The threat intelligence lifecycle is a structured, iterative process for transforming raw data into actionable intelligence. Based on the intelligence cycle used by military and government agencies, it comprises six phases: Direction (requirements gathering), Collection (data acquisition), Processing (normalization and deduplication), Analysis (contextualization and assessment), Dissemination (distribution to stakeholders), and Feedback (evaluation and refinement). This skill covers building each phase with tooling, metrics, and integration points for a mature CTI program.
Prerequisites
- Python 3.9+ with
pymisp, stix2, requests, pandas libraries
- MISP or OpenCTI as threat intelligence platform
- Ticketing system (Jira, ServiceNow) for requirements management
- SIEM integration (Splunk, Elastic) for indicator operationalization
- Understanding of intelligence analysis techniques (ACH, Diamond Model)
Key Concepts
Intelligence Requirements (IR)
Priority Intelligence Requirements (PIRs) define what the organization needs to know. Examples: Which threat actors target our sector? What vulnerabilities are being actively exploited? Are our brand or credentials being traded on dark web? PIRs drive collection planning and ensure intelligence production is relevant.
Collection Management Framework
A collection management framework maps intelligence requirements to collection sources, tracks collection gaps, and ensures coverage across the threat landscape. Sources include OSINT, commercial feeds, ISAC sharing, internal telemetry, and human intelligence from industry contacts.
Intelligence Levels
Strategic intelligence informs executive decision-making (threat landscape, risk trends, geopolitical context). Operational intelligence supports security operations (campaign tracking, actor TTPs, attack timing). Tactical intelligence enables immediate defense (IOCs, detection rules, blocklists).
Practical Steps
Step 1: Define Intelligence Requirements
import json
from datetime import datetime
from enum import Enum
class Priority(Enum):
CRITICAL = 1
HIGH = 2
MEDIUM =
LOW =
:
():
. = requirement_id
.question = question
.priority = priority
.stakeholder = stakeholder
.level = intelligence_level
.sources = collection_sources []
.created = datetime.now().isoformat()
.status =
.last_answered =
():
{
: .,
: .question,
: .priority.name,
: .stakeholder,
: .level,
: .sources,
: .created,
: .status,
: .last_answered,
}
:
():
.requirements = []
():
.requirements.append(requirement)
()
():
filtered = [r r .requirements r.status == ]
priority:
filtered = [r r filtered r.priority == priority]
level:
filtered = [r r filtered r.level == level]
filtered
():
data = [r.to_dict() r .requirements]
(output_file, ) f:
json.dump(data, f, indent=)
()
mgr = RequirementsManager()
mgr.add_requirement(IntelligenceRequirement(
, ,
Priority.CRITICAL, , ,
[, , ],
))
mgr.add_requirement(IntelligenceRequirement(
, ,
Priority.CRITICAL, , ,
[, , , ],
))
mgr.add_requirement(IntelligenceRequirement(
, ,
Priority.HIGH, , ,
[, , ],
))
mgr.add_requirement(IntelligenceRequirement(
, ,
Priority.HIGH, , ,
[, , ],
))
mgr.export_requirements()