080ce56de7
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Models (5 tables):
- AttackPath: named reusable attack scenario with template flag
- AttackPathStep: ordered kill-chain step (technique + test link)
- AttackPathExecution: a run with Red/Blue leads, timing, stored metrics
- AttackPathStepResult: per-step detected/not_detected/skipped result
- TimelineEntry: timestamped Red/Blue/system actions for MTTD/MTTR
Migration b036atk: raw SQL to avoid SQLAlchemy DDL hook issues
Service (attack_path_service.py):
- Full CRUD for paths + steps (add, update, delete, reorder)
- Execution lifecycle: create → start → execute steps → complete/abort
- Pre-creates pending step results on execution creation
- Auto-adds system timeline entries on key state transitions
- complete_execution() computes: detection_rate, mttd_seconds,
furthest_undetected_step, detected/not_detected/skipped counts
- get_kill_chain_metrics(): per-step breakdown + phase summary
Router /api/v1/attack-paths (20 endpoints):
POST/GET/PATCH/DELETE attack paths
GET/POST/PATCH/DELETE steps + reorder
POST/GET executions per path
GET/POST/start/complete/abort executions
POST/GET step results
POST/GET timeline entries
GET kill-chain metrics
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>