name: cyber-threat-hunting
guardrail: true
description: Conducts hypothesis-driven, evidence-preserving threat hunts with bounded negative conclusions and telemetry-gap handling. Use for hunt hypotheses, scoped offline analysis, or analytic follow-up; not unscoped scanning, malware execution, or generic intelligence summaries.
metadata:
triggers:
files: []
keywords:
- threat hunting
- hunt hypothesis
- hunting query
- negative conclusion
- suspicious activity hunt
- telemetry gap
Cyber Threat Hunting
Priority: P0 (CRITICAL)
Preserve provenance and bound every conclusion to authorized evidence.
Structure
Input: falsifiable hypothesis, behavior, entities, scope, sources, window, expected signal, stop condition. Process: define positive/negative observations; normalize without overwriting originals; test narrowest evidence; correlate by entity/time; record gaps and alternatives. Output: status, cited evidence, bounded conclusion, limitations, owner.
Rules
- Active collection or network operations require
cyber-authorization, documented scope, and runtime-proven controls; unsupported or missing scope blocks execution.
- Use controlled synthetic/offline fixtures. Preserve query/version, fixture provenance, retention, clock, identity, and source limitations.
- Status is
confirmed, suspected, false-positive, blocked, or not-tested; only cited evidence supports a status.
- “No evidence found in the examined dataset/time window” is bounded negative evidence, never proof of no compromise.
- Include engagement/scope reference; skill/version/source; observation time; status; evidence references; limitations; accountable owner. Reuse shared skill IDs.
Anti-Patterns
- Never call an empty or incomplete dataset clean.
- Never treat one ambiguous hit as confirmed compromise.
- Never collect live telemetry before authorization or invent hunt metrics.
References (lazy, primary)