- Playbooks: versioned Markdown runbooks per technique × type (attack/detect/investigate/respond/hunt)
- PlaybookVersion: immutable snapshots on every update; restore to any previous version
- LessonLearned: post-mortem records linked to tests/campaigns/attack-paths or manual
- Alembic migration b037know (raw SQL, idempotent, no PostgreSQL enums)
- Router /api/v1/knowledge: 14 endpoints for playbooks + lessons + stats
- Pydantic validators for playbook_type, severity, entity_type (422 on invalid)
- Knowledge stats endpoint: totals + breakdown by severity and playbook type
- Soft-delete on both resources; include_inactive filter for admin recovery
- QA script: 70+ tests across CRUD, versioning, filtering, auth, soft-delete, regression
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Tarea 4.1 — OSINT Enrichment:
- Add OsintItem model with source_type, severity, CVSS metadata, review flag
- Add Alembic migration b022 with osint_items table and optimized indexes
- Add osint_enrichment_service with NVD API integration, deduplication, rate limiting
- Add OSINT router: GET /osint/items, /osint/summary, /osint/technique/{id}
- Add POST /osint/items/{id}/review to mark items as reviewed
- Add POST /osint/enrich/{technique_id} for manual single-technique enrichment
- Techniques with new CVEs are automatically flagged review_required=True
- Register weekly enrichment job in APScheduler
- Add NVD_API_KEY config setting for optional increased rate limits
Tarea 4.2 — Stale Coverage Detection:
- Add stale_detection_service that flags techniques with no validated test
in the last N days, or never-validated but with a coverage status
- Configurable threshold via STALE_THRESHOLD_DAYS setting (default 365)
- Register daily stale detection job in APScheduler
- Only flags techniques not already marked review_required
Full Jira/Tempo pipeline: link Aegis entities to Jira issues, auto-sync
status hourly, log time internally with integrity hashing, and optionally
push worklogs to Tempo.
- 1.1 JiraLink model + Worklog model: Alembic migration b020 with indexes,
enums (jiralinkentitytype, jirasyncdirection), and integrity_hash column
- 1.2 Jira service: atlassian-python-api wrapper with lazy singleton client,
search/create/sync operations, feature-flagged via JIRA_ENABLED
- 1.3 Jira router: CRUD endpoints for /jira/links, /jira/search,
/jira/create-issue with audit logging and entity-to-issue auto-creation
- 1.4 Tempo service: worklog push via tempo-api-python-client, auto-log from
test completions when TEMPO_ENABLED, graceful fallback on failure
- 1.5 Worklog service + router: immutable internal time records with SHA-256
integrity hash, CRUD at /worklogs, /worklogs/{id}/verify endpoint
- 1.6 Frontend: JiraLinkPanel component (search, link, sync, unlink) and
WorklogTimeline component (timeline view, manual log form) integrated into
TestDetailPage sidebar, CampaignDetailPage grid, TechniqueDetailPage
- 1.7 Jira sync job: APScheduler hourly job syncs all links from Jira,
registered in background scheduler alongside existing jobs
T-106: Create test_workflow_service.py with state-machine transitions for the complete test lifecycle (draft -> red_executing -> blue_evaluating -> in_review -> validated/rejected), dual validation by Red/Blue leads, and reopen capability with field cleanup.
T-107: Update status_service.py to use detection_result from Blue Team instead of legacy result field, and differentiate between partial progress (some validated) vs all-in-progress states.
T-108: Create atomic_import_service.py that downloads the Atomic Red Team repo as a ZIP (avoiding API rate limits), parses all atomics YAML files, and creates idempotent TestTemplate records mapped to MITRE techniques.
Includes validation tests for all three tasks (19 checks total).
Implements all database models for the Aegis platform with full
Alembic migration support.
Models created:
- User: Authentication with role-based access control
- Technique: MITRE ATT&CK techniques with coverage status tracking
- Test: Security tests with validation workflow (draft/review/validated)
- Evidence: File metadata for test evidence (stored in MinIO)
- IntelItem: Threat intelligence items linked to techniques
- AuditLog: System-wide audit trail with JSONB details
Enumerations:
- TechniqueStatus: not_evaluated, in_progress, validated, partial, etc.
- TestState: draft, in_review, validated, rejected
- TestResult: detected, not_detected, partially_detected
Services:
- audit_service.py: log_action() helper for audit logging
All models include proper foreign key relationships and PostgreSQL
enum types are managed correctly in migrations (create/drop).
