feat(phase-28): add scoring system, operational metrics and executive dashboard (T-224 to T-226)
This commit is contained in:
@@ -11,6 +11,13 @@ class Settings(BaseSettings):
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MINIO_SECRET_KEY: str = "minioadmin"
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MINIO_BUCKET: str = "evidence"
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# Scoring weights (must sum to 100)
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SCORING_WEIGHT_TESTS: int = 40
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SCORING_WEIGHT_DETECTION_RULES: int = 20
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SCORING_WEIGHT_D3FEND: int = 15
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SCORING_WEIGHT_FRESHNESS: int = 15
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SCORING_WEIGHT_PLATFORM_DIVERSITY: int = 10
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class Config:
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env_file = ".env"
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@@ -24,6 +24,8 @@ from app.routers import d3fend as d3fend_router
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from app.routers import detection_rules as detection_rules_router
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from app.routers import campaigns as campaigns_router
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from app.routers import heatmap as heatmap_router
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from app.routers import scores as scores_router
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from app.routers import operational_metrics as operational_metrics_router
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from app.storage import ensure_bucket_exists
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from app.jobs.mitre_sync_job import start_scheduler, scheduler
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@@ -72,6 +74,8 @@ app.include_router(d3fend_router.router, prefix="/api/v1")
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app.include_router(detection_rules_router.router, prefix="/api/v1")
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app.include_router(campaigns_router.router, prefix="/api/v1")
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app.include_router(heatmap_router.router, prefix="/api/v1")
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app.include_router(scores_router.router, prefix="/api/v1")
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app.include_router(operational_metrics_router.router, prefix="/api/v1")
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@app.get("/health")
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56
backend/app/routers/operational_metrics.py
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56
backend/app/routers/operational_metrics.py
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@@ -0,0 +1,56 @@
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"""Operational metrics endpoints — MTTD, MTTR, Detection Efficacy, and more.
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Provides operational KPIs for security teams with trend analysis
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and team-level breakdowns.
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"""
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy.orm import Session
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from app.database import get_db
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from app.dependencies.auth import get_current_user
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from app.models.user import User
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from app.services.operational_metrics_service import (
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get_all_operational_metrics,
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get_operational_trend,
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get_metrics_by_team,
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)
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router = APIRouter(prefix="/metrics/operational", tags=["operational-metrics"])
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# ── GET /metrics/operational ──────────────────────────────────────────
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@router.get("")
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def operational_metrics(
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get all operational metrics (MTTD, MTTR, Detection Efficacy, etc.)."""
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return get_all_operational_metrics(db)
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# ── GET /metrics/operational/trend ────────────────────────────────────
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@router.get("/trend")
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def operational_trend(
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period: str = Query("90d", pattern="^(30d|90d|1y)$"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get weekly trend data for operational metrics."""
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return get_operational_trend(db, period)
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# ── GET /metrics/operational/by-team ──────────────────────────────────
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@router.get("/by-team")
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def metrics_by_team(
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get metrics broken down by Red Team vs Blue Team."""
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return get_metrics_by_team(db)
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189
backend/app/routers/scores.py
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189
backend/app/routers/scores.py
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@@ -0,0 +1,189 @@
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"""Scoring endpoints — technique, tactic, threat actor, and organization scores.
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Provides granular scoring with breakdowns and configurable weights.
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"""
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from typing import Optional
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from fastapi import APIRouter, Depends, HTTPException, Query
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from pydantic import BaseModel
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from sqlalchemy.orm import Session
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from app.database import get_db
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from app.dependencies.auth import get_current_user, require_role
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from app.models.user import User
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from app.models.technique import Technique
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from app.models.threat_actor import ThreatActor
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from app.config import settings
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from app.services.scoring_service import (
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calculate_technique_score,
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calculate_tactic_score,
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calculate_actor_coverage_score,
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calculate_organization_score,
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get_score_history,
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)
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router = APIRouter(prefix="/scores", tags=["scores"])
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# ── GET /scores/technique/{mitre_id} ─────────────────────────────────
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@router.get("/technique/{mitre_id}")
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def score_technique(
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mitre_id: str,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get detailed score with breakdown for a specific technique."""
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technique = (
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db.query(Technique)
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.filter(Technique.mitre_id == mitre_id)
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.first()
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)
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if not technique:
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raise HTTPException(status_code=404, detail="Technique not found")
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result = calculate_technique_score(technique, db)
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return {
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"mitre_id": technique.mitre_id,
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"name": technique.name,
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"tactic": technique.tactic,
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"status_global": technique.status_global.value if technique.status_global else None,
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**result,
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}
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# ── GET /scores/tactic/{tactic} ──────────────────────────────────────
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@router.get("/tactic/{tactic}")
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def score_tactic(
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tactic: str,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get average score for a tactic."""
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return calculate_tactic_score(tactic, db)
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# ── GET /scores/threat-actor/{id} ────────────────────────────────────
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@router.get("/threat-actor/{actor_id}")
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def score_threat_actor(
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actor_id: str,
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get coverage score against a specific threat actor."""
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actor = db.query(ThreatActor).filter(ThreatActor.id == actor_id).first()
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if not actor:
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raise HTTPException(status_code=404, detail="Threat actor not found")
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return calculate_actor_coverage_score(actor_id, db)
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# ── GET /scores/organization ─────────────────────────────────────────
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@router.get("/organization")
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def score_organization(
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get the overall organization security score."""
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return calculate_organization_score(db)
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# ── GET /scores/history ──────────────────────────────────────────────
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@router.get("/history")
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def score_history(
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period: str = Query("90d", pattern="^(30d|90d|1y)$"),
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db: Session = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""Get historical score data points (weekly)."""
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return get_score_history(db, period)
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# ── GET /scores/config ───────────────────────────────────────────────
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@router.get("/config")
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def get_scoring_config(
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current_user: User = Depends(require_role("admin")),
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):
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"""Get current scoring weights (admin only)."""
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return {
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"weights": {
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"tests": settings.SCORING_WEIGHT_TESTS,
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"detection_rules": settings.SCORING_WEIGHT_DETECTION_RULES,
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"d3fend": settings.SCORING_WEIGHT_D3FEND,
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"freshness": settings.SCORING_WEIGHT_FRESHNESS,
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"platform_diversity": settings.SCORING_WEIGHT_PLATFORM_DIVERSITY,
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},
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"total": (
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settings.SCORING_WEIGHT_TESTS
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+ settings.SCORING_WEIGHT_DETECTION_RULES
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+ settings.SCORING_WEIGHT_D3FEND
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+ settings.SCORING_WEIGHT_FRESHNESS
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+ settings.SCORING_WEIGHT_PLATFORM_DIVERSITY
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),
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}
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# ── PATCH /scores/config ─────────────────────────────────────────────
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class ScoringConfigUpdate(BaseModel):
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tests: Optional[int] = None
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detection_rules: Optional[int] = None
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d3fend: Optional[int] = None
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freshness: Optional[int] = None
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platform_diversity: Optional[int] = None
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@router.patch("/config")
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def update_scoring_config(
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payload: ScoringConfigUpdate,
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current_user: User = Depends(require_role("admin")),
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):
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"""Update scoring weights (admin only).
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Note: Since we're using Opcion A (env vars / Settings), changes
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are applied at runtime but won't persist across restarts unless
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the .env file is also updated. For production, consider migrating
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to Option B (database table).
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"""
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if payload.tests is not None:
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settings.SCORING_WEIGHT_TESTS = payload.tests
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if payload.detection_rules is not None:
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settings.SCORING_WEIGHT_DETECTION_RULES = payload.detection_rules
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if payload.d3fend is not None:
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settings.SCORING_WEIGHT_D3FEND = payload.d3fend
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if payload.freshness is not None:
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settings.SCORING_WEIGHT_FRESHNESS = payload.freshness
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if payload.platform_diversity is not None:
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settings.SCORING_WEIGHT_PLATFORM_DIVERSITY = payload.platform_diversity
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return {
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"message": "Scoring config updated",
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"weights": {
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"tests": settings.SCORING_WEIGHT_TESTS,
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"detection_rules": settings.SCORING_WEIGHT_DETECTION_RULES,
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"d3fend": settings.SCORING_WEIGHT_D3FEND,
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"freshness": settings.SCORING_WEIGHT_FRESHNESS,
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"platform_diversity": settings.SCORING_WEIGHT_PLATFORM_DIVERSITY,
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},
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"total": (
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settings.SCORING_WEIGHT_TESTS
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+ settings.SCORING_WEIGHT_DETECTION_RULES
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+ settings.SCORING_WEIGHT_D3FEND
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+ settings.SCORING_WEIGHT_FRESHNESS
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+ settings.SCORING_WEIGHT_PLATFORM_DIVERSITY
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),
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}
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468
backend/app/services/operational_metrics_service.py
Normal file
468
backend/app/services/operational_metrics_service.py
Normal file
@@ -0,0 +1,468 @@
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"""Operational metrics service — MTTD, MTTR, Detection Efficacy, and more.
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Calculates security operations KPIs from test data and audit logs.
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"""
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from datetime import datetime, timedelta
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from typing import Optional
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from sqlalchemy import func, case, and_, or_, extract
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from sqlalchemy.orm import Session
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from app.models.test import Test
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from app.models.technique import Technique
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from app.models.test_detection_result import TestDetectionResult
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from app.models.audit import AuditLog
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from app.models.enums import TestState, TestResult
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def _safe_stats(values: list[float]) -> dict:
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"""Compute mean, median, min, max from a list of floats."""
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if not values:
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return None
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sorted_vals = sorted(values)
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n = len(sorted_vals)
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return {
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"mean_hours": round(sum(sorted_vals) / n, 1),
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"median_hours": round(sorted_vals[n // 2], 1),
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"min_hours": round(sorted_vals[0], 1),
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"max_hours": round(sorted_vals[-1], 1),
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"sample_size": n,
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}
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# ── MTTD (Mean Time to Detect) ───────────────────────────────────────
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def calculate_mttd(db: Session) -> Optional[dict]:
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"""Calculate Mean Time to Detect.
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For each validated test: time between entering red_executing and
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entering blue_evaluating (extracted from audit_log timestamps).
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"""
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# Get validated tests that have both timestamps available
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# Using audit log entries for state transitions
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tests = (
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db.query(Test)
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.filter(Test.state == TestState.validated)
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.all()
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)
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detection_times = []
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for test in tests:
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# Find the red_executing and blue_evaluating transition timestamps
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red_start = (
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db.query(AuditLog.timestamp)
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.filter(
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AuditLog.entity_type == "test",
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AuditLog.entity_id == str(test.id),
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AuditLog.action.in_(["test_start_execution", "start_execution"]),
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)
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.order_by(AuditLog.timestamp.asc())
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.first()
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)
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blue_start = (
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db.query(AuditLog.timestamp)
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.filter(
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AuditLog.entity_type == "test",
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AuditLog.entity_id == str(test.id),
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AuditLog.action.in_(["test_submit_red", "submit_red"]),
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)
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.order_by(AuditLog.timestamp.asc())
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.first()
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)
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if red_start and blue_start and blue_start[0] > red_start[0]:
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hours = (blue_start[0] - red_start[0]).total_seconds() / 3600
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detection_times.append(hours)
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return _safe_stats(detection_times)
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# ── MTTR (Mean Time to Respond/Remediate) ─────────────────────────────
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def calculate_mttr(db: Session) -> Optional[dict]:
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"""Calculate Mean Time to Respond.
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For tests with remediation_status = completed: time between
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detection_result being set and remediation_status = completed.
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"""
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# Tests with completed remediation
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tests = (
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db.query(Test)
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.filter(
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Test.remediation_status == "completed",
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Test.blue_validated_at.isnot(None),
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)
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.all()
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)
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response_times = []
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for test in tests:
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# Find when remediation was completed from audit log
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remediation_complete = (
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db.query(AuditLog.timestamp)
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.filter(
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AuditLog.entity_type == "test",
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AuditLog.entity_id == str(test.id),
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AuditLog.action.ilike("%remediation%"),
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)
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.order_by(AuditLog.timestamp.desc())
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.first()
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)
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detection_time = test.blue_validated_at
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if remediation_complete and detection_time:
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hours = (remediation_complete[0] - detection_time).total_seconds() / 3600
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if hours > 0:
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response_times.append(hours)
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return _safe_stats(response_times)
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# ── Detection Efficacy ───────────────────────────────────────────────
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def calculate_detection_efficacy(db: Session) -> dict:
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"""Calculate detection efficacy: detected / total validated tests."""
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validated_tests = (
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db.query(Test)
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.filter(Test.state == TestState.validated)
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.all()
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)
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total = len(validated_tests)
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if total == 0:
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return {
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"percentage": 0,
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"detected": 0,
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"partially": 0,
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"not_detected": 0,
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"total": 0,
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}
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detected = len([t for t in validated_tests if t.detection_result == TestResult.detected])
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partially = len([t for t in validated_tests if t.detection_result == TestResult.partially_detected])
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not_detected = len([t for t in validated_tests if t.detection_result == TestResult.not_detected])
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percentage = round((detected / total) * 100, 1) if total > 0 else 0
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return {
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"percentage": percentage,
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"detected": detected,
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"partially": partially,
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"not_detected": not_detected,
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"total": total,
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}
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# ── Alert Fidelity ──────────────────────────────────────────────────
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def calculate_alert_fidelity(db: Session) -> dict:
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"""Calculate alert fidelity: ratio of triggered detection rules."""
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total_evaluated = (
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db.query(func.count(TestDetectionResult.id))
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.filter(TestDetectionResult.triggered.isnot(None))
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.scalar()
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) or 0
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triggered = (
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db.query(func.count(TestDetectionResult.id))
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.filter(TestDetectionResult.triggered == True)
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.scalar()
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) or 0
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not_triggered = total_evaluated - triggered
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return {
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"percentage": round((triggered / total_evaluated) * 100, 1) if total_evaluated > 0 else 0,
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"triggered": triggered,
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"not_triggered": not_triggered,
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"total_evaluated": total_evaluated,
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}
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# ── Coverage Velocity ────────────────────────────────────────────────
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def calculate_coverage_velocity(db: Session) -> dict:
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"""Calculate techniques validated per week."""
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# Count techniques that changed to validated/partial in the last 12 weeks
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twelve_weeks_ago = datetime.utcnow() - timedelta(weeks=12)
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weekly_counts = (
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db.query(
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func.date_trunc("week", Technique.last_review_date).label("week"),
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func.count(Technique.id).label("count"),
|
||||
)
|
||||
.filter(
|
||||
Technique.last_review_date >= twelve_weeks_ago,
|
||||
Technique.last_review_date.isnot(None),
|
||||
)
|
||||
.group_by(func.date_trunc("week", Technique.last_review_date))
|
||||
.order_by("week")
|
||||
.all()
|
||||
)
|
||||
|
||||
if weekly_counts:
|
||||
counts = [row.count for row in weekly_counts]
|
||||
avg_per_week = round(sum(counts) / len(counts), 1)
|
||||
# Trend: compare last 4 weeks vs previous 4 weeks
|
||||
recent = counts[-4:] if len(counts) >= 4 else counts
|
||||
earlier = counts[-8:-4] if len(counts) >= 8 else counts[:len(counts) // 2] if counts else []
|
||||
|
||||
recent_avg = sum(recent) / len(recent) if recent else 0
|
||||
earlier_avg = sum(earlier) / len(earlier) if earlier else 0
|
||||
|
||||
if recent_avg > earlier_avg * 1.1:
|
||||
trend = "improving"
|
||||
elif recent_avg < earlier_avg * 0.9:
|
||||
trend = "declining"
|
||||
else:
|
||||
trend = "stable"
|
||||
else:
|
||||
avg_per_week = 0
|
||||
trend = "stable"
|
||||
|
||||
return {
|
||||
"techniques_per_week": avg_per_week,
|
||||
"trend": trend,
|
||||
}
|
||||
|
||||
|
||||
# ── Validation Throughput ────────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_validation_throughput(db: Session) -> dict:
|
||||
"""Calculate tests validated/rejected per week."""
|
||||
twelve_weeks_ago = datetime.utcnow() - timedelta(weeks=12)
|
||||
|
||||
# Tests validated
|
||||
validated_weekly = (
|
||||
db.query(
|
||||
func.date_trunc("week", Test.red_validated_at).label("week"),
|
||||
func.count(Test.id).label("count"),
|
||||
)
|
||||
.filter(
|
||||
Test.red_validated_at >= twelve_weeks_ago,
|
||||
Test.state.in_([TestState.validated, TestState.rejected]),
|
||||
)
|
||||
.group_by(func.date_trunc("week", Test.red_validated_at))
|
||||
.order_by("week")
|
||||
.all()
|
||||
)
|
||||
|
||||
if validated_weekly:
|
||||
counts = [row.count for row in validated_weekly]
|
||||
avg_per_week = round(sum(counts) / len(counts), 1)
|
||||
recent = counts[-4:] if len(counts) >= 4 else counts
|
||||
earlier = counts[-8:-4] if len(counts) >= 8 else counts[:len(counts) // 2] if counts else []
|
||||
|
||||
recent_avg = sum(recent) / len(recent) if recent else 0
|
||||
earlier_avg = sum(earlier) / len(earlier) if earlier else 0
|
||||
|
||||
if recent_avg > earlier_avg * 1.1:
|
||||
trend = "improving"
|
||||
elif recent_avg < earlier_avg * 0.9:
|
||||
trend = "declining"
|
||||
else:
|
||||
trend = "stable"
|
||||
else:
|
||||
avg_per_week = 0
|
||||
trend = "stable"
|
||||
|
||||
return {
|
||||
"tests_per_week": avg_per_week,
|
||||
"trend": trend,
|
||||
}
|
||||
|
||||
|
||||
# ── Rejection Rate ──────────────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_rejection_rate(db: Session) -> dict:
|
||||
"""Calculate rejection rate, broken down by red_lead and blue_lead."""
|
||||
validated_count = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.state == TestState.validated)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
rejected_count = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.state == TestState.rejected)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
total = validated_count + rejected_count
|
||||
overall_pct = round((rejected_count / total) * 100, 1) if total > 0 else 0
|
||||
|
||||
# By red_lead (red_validation_status == "rejected")
|
||||
red_rejected = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.red_validation_status == "rejected")
|
||||
.scalar()
|
||||
) or 0
|
||||
red_total = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.red_validation_status.in_(["approved", "rejected"]))
|
||||
.scalar()
|
||||
) or 0
|
||||
red_pct = round((red_rejected / red_total) * 100, 1) if red_total > 0 else 0
|
||||
|
||||
# By blue_lead
|
||||
blue_rejected = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.blue_validation_status == "rejected")
|
||||
.scalar()
|
||||
) or 0
|
||||
blue_total = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.blue_validation_status.in_(["approved", "rejected"]))
|
||||
.scalar()
|
||||
) or 0
|
||||
blue_pct = round((blue_rejected / blue_total) * 100, 1) if blue_total > 0 else 0
|
||||
|
||||
return {
|
||||
"percentage": overall_pct,
|
||||
"by_red_lead": red_pct,
|
||||
"by_blue_lead": blue_pct,
|
||||
}
|
||||
|
||||
|
||||
# ── Aggregated Operational Metrics ───────────────────────────────────
|
||||
|
||||
|
||||
def get_all_operational_metrics(db: Session) -> dict:
|
||||
"""Get all operational metrics in a single response."""
|
||||
return {
|
||||
"mttd": calculate_mttd(db),
|
||||
"mttr": calculate_mttr(db),
|
||||
"detection_efficacy": calculate_detection_efficacy(db),
|
||||
"alert_fidelity": calculate_alert_fidelity(db),
|
||||
"coverage_velocity": calculate_coverage_velocity(db),
|
||||
"validation_throughput": calculate_validation_throughput(db),
|
||||
"rejection_rate": calculate_rejection_rate(db),
|
||||
}
|
||||
|
||||
|
||||
# ── Trend Data ───────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def get_operational_trend(db: Session, period: str = "90d") -> list:
|
||||
"""Get weekly trend data for operational metrics."""
|
||||
now = datetime.utcnow()
|
||||
if period == "30d":
|
||||
start = now - timedelta(days=30)
|
||||
elif period == "1y":
|
||||
start = now - timedelta(days=365)
|
||||
else:
|
||||
start = now - timedelta(days=90)
|
||||
|
||||
# Build weekly data points
|
||||
data_points = []
|
||||
current = start
|
||||
while current < now:
|
||||
week_end = min(current + timedelta(days=7), now)
|
||||
|
||||
# Detection efficacy for tests validated up to this week
|
||||
validated_up_to = (
|
||||
db.query(Test)
|
||||
.filter(
|
||||
Test.state == TestState.validated,
|
||||
Test.red_validated_at <= week_end,
|
||||
)
|
||||
.all()
|
||||
)
|
||||
|
||||
total = len(validated_up_to)
|
||||
detected = len([t for t in validated_up_to if t.detection_result == TestResult.detected])
|
||||
efficacy = round((detected / total) * 100, 1) if total > 0 else 0
|
||||
|
||||
data_points.append({
|
||||
"date": current.strftime("%Y-%m-%d"),
|
||||
"detection_efficacy": efficacy,
|
||||
"validated_tests": total,
|
||||
"detected_tests": detected,
|
||||
})
|
||||
|
||||
current = week_end
|
||||
|
||||
return data_points
|
||||
|
||||
|
||||
# ── By Team ──────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def get_metrics_by_team(db: Session) -> dict:
|
||||
"""Get metrics broken down by Red vs Blue team."""
|
||||
# Red team metrics
|
||||
red_tests_completed = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.state.in_([
|
||||
TestState.blue_evaluating,
|
||||
TestState.in_review,
|
||||
TestState.validated,
|
||||
TestState.rejected,
|
||||
]))
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
red_avg_time = None
|
||||
red_times = []
|
||||
# Time for red team to complete their phase
|
||||
tests_with_red = (
|
||||
db.query(Test)
|
||||
.filter(Test.red_validated_at.isnot(None), Test.created_at.isnot(None))
|
||||
.all()
|
||||
)
|
||||
for t in tests_with_red:
|
||||
hours = (t.red_validated_at - t.created_at).total_seconds() / 3600
|
||||
if hours > 0:
|
||||
red_times.append(hours)
|
||||
if red_times:
|
||||
red_avg_time = round(sum(red_times) / len(red_times), 1)
|
||||
|
||||
# Blue team metrics
|
||||
blue_tests_completed = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.state.in_([
|
||||
TestState.in_review,
|
||||
TestState.validated,
|
||||
TestState.rejected,
|
||||
]))
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
blue_avg_time = None
|
||||
blue_times = []
|
||||
tests_with_blue = (
|
||||
db.query(Test)
|
||||
.filter(
|
||||
Test.blue_validated_at.isnot(None),
|
||||
Test.red_validated_at.isnot(None),
|
||||
)
|
||||
.all()
|
||||
)
|
||||
for t in tests_with_blue:
|
||||
hours = (t.blue_validated_at - t.red_validated_at).total_seconds() / 3600
|
||||
if hours > 0:
|
||||
blue_times.append(hours)
|
||||
if blue_times:
|
||||
blue_avg_time = round(sum(blue_times) / len(blue_times), 1)
|
||||
|
||||
return {
|
||||
"red_team": {
|
||||
"tests_completed": red_tests_completed,
|
||||
"avg_completion_hours": red_avg_time,
|
||||
"rejection_rate": calculate_rejection_rate(db)["by_red_lead"],
|
||||
},
|
||||
"blue_team": {
|
||||
"tests_completed": blue_tests_completed,
|
||||
"avg_completion_hours": blue_avg_time,
|
||||
"rejection_rate": calculate_rejection_rate(db)["by_blue_lead"],
|
||||
},
|
||||
}
|
||||
467
backend/app/services/scoring_service.py
Normal file
467
backend/app/services/scoring_service.py
Normal file
@@ -0,0 +1,467 @@
|
||||
"""Scoring service — granular 0-100 scoring for techniques, tactics, actors, and org.
|
||||
|
||||
Uses configurable weights from Settings to compute coverage scores with
|
||||
detailed breakdowns.
|
||||
"""
|
||||
|
||||
from datetime import datetime, timedelta
|
||||
from typing import Optional
|
||||
|
||||
from sqlalchemy import func
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from app.config import settings
|
||||
from app.models.technique import Technique
|
||||
from app.models.test import Test
|
||||
from app.models.detection_rule import DetectionRule
|
||||
from app.models.test_detection_result import TestDetectionResult
|
||||
from app.models.defensive_technique import DefensiveTechniqueMapping
|
||||
from app.models.threat_actor import ThreatActor, ThreatActorTechnique
|
||||
from app.models.enums import TestState, TestResult
|
||||
|
||||
|
||||
# ── Technique-level scoring ──────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_technique_score(technique: Technique, db: Session) -> dict:
|
||||
"""Calculate a 0-100 score for a technique with detailed breakdown.
|
||||
|
||||
Weights (configurable via settings):
|
||||
- tests_validated: weight from SCORING_WEIGHT_TESTS
|
||||
- detection_rules: weight from SCORING_WEIGHT_DETECTION_RULES
|
||||
- d3fend_coverage: weight from SCORING_WEIGHT_D3FEND
|
||||
- freshness: weight from SCORING_WEIGHT_FRESHNESS
|
||||
- platform_diversity: weight from SCORING_WEIGHT_PLATFORM_DIVERSITY
|
||||
"""
|
||||
w_tests = settings.SCORING_WEIGHT_TESTS
|
||||
w_detection = settings.SCORING_WEIGHT_DETECTION_RULES
|
||||
w_d3fend = settings.SCORING_WEIGHT_D3FEND
|
||||
w_freshness = settings.SCORING_WEIGHT_FRESHNESS
|
||||
w_diversity = settings.SCORING_WEIGHT_PLATFORM_DIVERSITY
|
||||
|
||||
breakdown = {}
|
||||
|
||||
# ── 1. Tests validated with detection ──────────────────────────
|
||||
all_tests = (
|
||||
db.query(Test)
|
||||
.filter(Test.technique_id == technique.id)
|
||||
.all()
|
||||
)
|
||||
validated_tests = [t for t in all_tests if t.state == TestState.validated]
|
||||
detected_tests = [
|
||||
t for t in validated_tests
|
||||
if t.detection_result == TestResult.detected
|
||||
]
|
||||
|
||||
if validated_tests:
|
||||
test_ratio = len(detected_tests) / len(validated_tests)
|
||||
test_score = round(test_ratio * w_tests, 1)
|
||||
else:
|
||||
test_ratio = 0
|
||||
test_score = 0
|
||||
|
||||
breakdown["tests_validated"] = {
|
||||
"score": test_score,
|
||||
"max": w_tests,
|
||||
"detail": f"{len(detected_tests)}/{len(validated_tests)} tests detected"
|
||||
if validated_tests
|
||||
else "No validated tests",
|
||||
}
|
||||
|
||||
# ── 2. Detection rules coverage ───────────────────────────────
|
||||
total_rules = (
|
||||
db.query(func.count(DetectionRule.id))
|
||||
.filter(
|
||||
DetectionRule.mitre_technique_id == technique.mitre_id,
|
||||
DetectionRule.is_active == True,
|
||||
)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
triggered_rules = 0
|
||||
if total_rules > 0:
|
||||
triggered_rules = (
|
||||
db.query(func.count(TestDetectionResult.id))
|
||||
.join(
|
||||
DetectionRule,
|
||||
DetectionRule.id == TestDetectionResult.detection_rule_id,
|
||||
)
|
||||
.filter(
|
||||
DetectionRule.mitre_technique_id == technique.mitre_id,
|
||||
TestDetectionResult.triggered == True,
|
||||
)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
detection_ratio = min(triggered_rules / total_rules, 1.0)
|
||||
detection_score = round(detection_ratio * w_detection, 1)
|
||||
else:
|
||||
detection_ratio = 0
|
||||
detection_score = 0
|
||||
|
||||
breakdown["detection_rules"] = {
|
||||
"score": detection_score,
|
||||
"max": w_detection,
|
||||
"detail": f"{triggered_rules}/{total_rules} rules triggered"
|
||||
if total_rules > 0
|
||||
else "No detection rules available",
|
||||
}
|
||||
|
||||
# ── 3. D3FEND coverage ────────────────────────────────────────
|
||||
total_countermeasures = (
|
||||
db.query(func.count(DefensiveTechniqueMapping.id))
|
||||
.filter(DefensiveTechniqueMapping.attack_technique_id == technique.id)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
# Consider a countermeasure "verified" if we have validated tests
|
||||
# with detection for the technique (simplified heuristic)
|
||||
verified_countermeasures = 0
|
||||
if total_countermeasures > 0 and len(detected_tests) > 0:
|
||||
# Rough heuristic: each detected test validates ~1 countermeasure
|
||||
verified_countermeasures = min(len(detected_tests), total_countermeasures)
|
||||
d3fend_ratio = verified_countermeasures / total_countermeasures
|
||||
d3fend_score = round(d3fend_ratio * w_d3fend, 1)
|
||||
else:
|
||||
d3fend_ratio = 0
|
||||
d3fend_score = 0
|
||||
|
||||
breakdown["d3fend_coverage"] = {
|
||||
"score": d3fend_score,
|
||||
"max": w_d3fend,
|
||||
"detail": f"{verified_countermeasures}/{total_countermeasures} countermeasures"
|
||||
if total_countermeasures > 0
|
||||
else "No D3FEND mappings",
|
||||
}
|
||||
|
||||
# ── 4. Freshness ──────────────────────────────────────────────
|
||||
# Most recent validated test date
|
||||
most_recent_test = (
|
||||
db.query(func.max(Test.red_validated_at))
|
||||
.filter(
|
||||
Test.technique_id == technique.id,
|
||||
Test.state == TestState.validated,
|
||||
)
|
||||
.scalar()
|
||||
)
|
||||
|
||||
now = datetime.utcnow()
|
||||
if most_recent_test:
|
||||
days_ago = (now - most_recent_test).days
|
||||
if days_ago < 90:
|
||||
freshness_pct = 1.0
|
||||
elif days_ago < 180:
|
||||
freshness_pct = 0.5
|
||||
else:
|
||||
freshness_pct = 0.0
|
||||
freshness_score = round(freshness_pct * w_freshness, 1)
|
||||
freshness_detail = f"Last test {days_ago} days ago"
|
||||
else:
|
||||
freshness_pct = 0
|
||||
freshness_score = 0
|
||||
freshness_detail = "No validated tests"
|
||||
|
||||
breakdown["freshness"] = {
|
||||
"score": freshness_score,
|
||||
"max": w_freshness,
|
||||
"detail": freshness_detail,
|
||||
}
|
||||
|
||||
# ── 5. Platform diversity ─────────────────────────────────────
|
||||
available_platforms = technique.platforms or []
|
||||
total_platforms = len(available_platforms) if available_platforms else 3 # default 3
|
||||
|
||||
tested_platforms = set()
|
||||
for t in validated_tests:
|
||||
if t.platform:
|
||||
tested_platforms.add(t.platform.lower())
|
||||
|
||||
if total_platforms > 0 and tested_platforms:
|
||||
diversity_ratio = min(len(tested_platforms) / total_platforms, 1.0)
|
||||
diversity_score = round(diversity_ratio * w_diversity, 1)
|
||||
else:
|
||||
diversity_ratio = 0
|
||||
diversity_score = 0
|
||||
|
||||
breakdown["platform_diversity"] = {
|
||||
"score": diversity_score,
|
||||
"max": w_diversity,
|
||||
"detail": f"{len(tested_platforms)}/{total_platforms} platforms covered"
|
||||
if tested_platforms
|
||||
else "No platforms tested",
|
||||
}
|
||||
|
||||
# ── Total ─────────────────────────────────────────────────────
|
||||
total = min(
|
||||
test_score + detection_score + d3fend_score + freshness_score + diversity_score,
|
||||
100,
|
||||
)
|
||||
|
||||
return {
|
||||
"total_score": round(total, 1),
|
||||
"breakdown": breakdown,
|
||||
}
|
||||
|
||||
|
||||
# ── Tactic-level scoring ─────────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_tactic_score(tactic: str, db: Session) -> dict:
|
||||
"""Calculate average score for all techniques in a tactic."""
|
||||
techniques = (
|
||||
db.query(Technique)
|
||||
.filter(Technique.tactic.ilike(f"%{tactic}%"))
|
||||
.all()
|
||||
)
|
||||
|
||||
if not techniques:
|
||||
return {
|
||||
"tactic": tactic,
|
||||
"average_score": 0,
|
||||
"techniques_count": 0,
|
||||
"techniques_scored": 0,
|
||||
}
|
||||
|
||||
scores = []
|
||||
for tech in techniques:
|
||||
result = calculate_technique_score(tech, db)
|
||||
scores.append(result["total_score"])
|
||||
|
||||
return {
|
||||
"tactic": tactic,
|
||||
"average_score": round(sum(scores) / len(scores), 1) if scores else 0,
|
||||
"techniques_count": len(techniques),
|
||||
"techniques_scored": len([s for s in scores if s > 0]),
|
||||
}
|
||||
|
||||
|
||||
# ── Threat actor scoring ─────────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_actor_coverage_score(actor_id: str, db: Session) -> dict:
|
||||
"""Calculate coverage score for a specific threat actor's techniques."""
|
||||
actor = db.query(ThreatActor).filter(ThreatActor.id == actor_id).first()
|
||||
if not actor:
|
||||
return {"total_score": 0, "techniques_count": 0, "techniques_covered": 0}
|
||||
|
||||
# Get all techniques used by this actor
|
||||
actor_techniques = (
|
||||
db.query(ThreatActorTechnique)
|
||||
.filter(ThreatActorTechnique.threat_actor_id == actor.id)
|
||||
.all()
|
||||
)
|
||||
|
||||
technique_ids = [at.technique_id for at in actor_techniques]
|
||||
if not technique_ids:
|
||||
return {
|
||||
"actor_id": str(actor.id),
|
||||
"actor_name": actor.name,
|
||||
"total_score": 0,
|
||||
"techniques_count": 0,
|
||||
"techniques_covered": 0,
|
||||
"techniques_detail": [],
|
||||
}
|
||||
|
||||
techniques = (
|
||||
db.query(Technique)
|
||||
.filter(Technique.id.in_(technique_ids))
|
||||
.all()
|
||||
)
|
||||
|
||||
scores = []
|
||||
details = []
|
||||
for tech in techniques:
|
||||
result = calculate_technique_score(tech, db)
|
||||
score = result["total_score"]
|
||||
scores.append(score)
|
||||
details.append({
|
||||
"mitre_id": tech.mitre_id,
|
||||
"name": tech.name,
|
||||
"score": score,
|
||||
"breakdown": result["breakdown"],
|
||||
})
|
||||
|
||||
avg_score = round(sum(scores) / len(scores), 1) if scores else 0
|
||||
|
||||
return {
|
||||
"actor_id": str(actor.id),
|
||||
"actor_name": actor.name,
|
||||
"total_score": avg_score,
|
||||
"techniques_count": len(techniques),
|
||||
"techniques_covered": len([s for s in scores if s > 50]),
|
||||
"techniques_detail": details,
|
||||
}
|
||||
|
||||
|
||||
# ── Organization-level scoring ────────────────────────────────────────
|
||||
|
||||
|
||||
def calculate_organization_score(db: Session) -> dict:
|
||||
"""Calculate the overall organization security score."""
|
||||
# All techniques
|
||||
all_techniques = db.query(Technique).all()
|
||||
total_count = len(all_techniques)
|
||||
|
||||
if total_count == 0:
|
||||
return {
|
||||
"overall_score": 0,
|
||||
"total_coverage": 0,
|
||||
"critical_coverage": 0,
|
||||
"detection_maturity": 0,
|
||||
"response_readiness": 0,
|
||||
"techniques_evaluated": 0,
|
||||
"techniques_total": 0,
|
||||
}
|
||||
|
||||
# Calculate scores for all techniques (with caching for performance)
|
||||
all_scores = []
|
||||
evaluated_count = 0
|
||||
|
||||
for tech in all_techniques:
|
||||
result = calculate_technique_score(tech, db)
|
||||
score = result["total_score"]
|
||||
all_scores.append(score)
|
||||
if score > 0:
|
||||
evaluated_count += 1
|
||||
|
||||
# Total coverage: average of all evaluated techniques
|
||||
evaluated_scores = [s for s in all_scores if s > 0]
|
||||
total_coverage = (
|
||||
round(sum(evaluated_scores) / len(evaluated_scores), 1)
|
||||
if evaluated_scores
|
||||
else 0
|
||||
)
|
||||
|
||||
# Critical coverage: techniques with high-severity templates
|
||||
# (simplified: techniques that have tests are "critical")
|
||||
from app.models.test_template import TestTemplate
|
||||
|
||||
critical_mitre_ids = set(
|
||||
row[0]
|
||||
for row in db.query(TestTemplate.mitre_technique_id)
|
||||
.filter(TestTemplate.severity.in_(["high", "critical"]))
|
||||
.distinct()
|
||||
.all()
|
||||
)
|
||||
|
||||
critical_techniques = [
|
||||
t for t in all_techniques if t.mitre_id in critical_mitre_ids
|
||||
]
|
||||
if critical_techniques:
|
||||
critical_scores = []
|
||||
for tech in critical_techniques:
|
||||
result = calculate_technique_score(tech, db)
|
||||
critical_scores.append(result["total_score"])
|
||||
critical_coverage = round(sum(critical_scores) / len(critical_scores), 1)
|
||||
else:
|
||||
critical_coverage = 0
|
||||
|
||||
# Detection maturity: based on detection rule coverage
|
||||
total_rules = (
|
||||
db.query(func.count(DetectionRule.id))
|
||||
.filter(DetectionRule.is_active == True)
|
||||
.scalar()
|
||||
) or 0
|
||||
triggered_total = (
|
||||
db.query(func.count(TestDetectionResult.id))
|
||||
.filter(TestDetectionResult.triggered == True)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
detection_maturity = (
|
||||
round((triggered_total / total_rules) * 100, 1)
|
||||
if total_rules > 0
|
||||
else 0
|
||||
)
|
||||
detection_maturity = min(detection_maturity, 100)
|
||||
|
||||
# Response readiness: based on remediation completion
|
||||
remediation_total = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.remediation_status.isnot(None))
|
||||
.scalar()
|
||||
) or 0
|
||||
remediation_completed = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(Test.remediation_status == "completed")
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
response_readiness = (
|
||||
round((remediation_completed / remediation_total) * 100, 1)
|
||||
if remediation_total > 0
|
||||
else 0
|
||||
)
|
||||
|
||||
# Overall score: weighted average of sub-scores
|
||||
overall = round(
|
||||
total_coverage * 0.4
|
||||
+ critical_coverage * 0.25
|
||||
+ detection_maturity * 0.2
|
||||
+ response_readiness * 0.15,
|
||||
1,
|
||||
)
|
||||
|
||||
return {
|
||||
"overall_score": overall,
|
||||
"total_coverage": total_coverage,
|
||||
"critical_coverage": critical_coverage,
|
||||
"detection_maturity": detection_maturity,
|
||||
"response_readiness": response_readiness,
|
||||
"techniques_evaluated": evaluated_count,
|
||||
"techniques_total": total_count,
|
||||
}
|
||||
|
||||
|
||||
# ── Score history ────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def get_score_history(db: Session, period: str = "90d") -> list:
|
||||
"""Get historical score snapshots.
|
||||
|
||||
Since we don't have a dedicated history table, we approximate by
|
||||
computing scores based on test dates within time windows.
|
||||
Returns a list of weekly data points.
|
||||
"""
|
||||
from app.models.audit import AuditLog
|
||||
|
||||
now = datetime.utcnow()
|
||||
if period == "30d":
|
||||
start = now - timedelta(days=30)
|
||||
elif period == "1y":
|
||||
start = now - timedelta(days=365)
|
||||
else: # 90d default
|
||||
start = now - timedelta(days=90)
|
||||
|
||||
# Group validated tests by week
|
||||
weeks = []
|
||||
current = start
|
||||
while current < now:
|
||||
week_end = min(current + timedelta(days=7), now)
|
||||
|
||||
# Count validated tests up to this week
|
||||
validated_up_to = (
|
||||
db.query(func.count(Test.id))
|
||||
.filter(
|
||||
Test.state == TestState.validated,
|
||||
Test.red_validated_at <= week_end,
|
||||
)
|
||||
.scalar()
|
||||
) or 0
|
||||
|
||||
total_techniques = (
|
||||
db.query(func.count(Technique.id)).scalar()
|
||||
) or 1
|
||||
|
||||
# Simple approximation: coverage percentage as score proxy
|
||||
score_approx = round((validated_up_to / total_techniques) * 100, 1)
|
||||
|
||||
weeks.append({
|
||||
"date": current.strftime("%Y-%m-%d"),
|
||||
"score": min(score_approx, 100),
|
||||
"validated_tests": validated_up_to,
|
||||
})
|
||||
|
||||
current = week_end
|
||||
|
||||
return weeks
|
||||
@@ -3,6 +3,7 @@ import LoginPage from "./pages/LoginPage";
|
||||
import DashboardPage from "./pages/DashboardPage";
|
||||
import TechniquesPage from "./pages/TechniquesPage";
|
||||
import MatrixPage from "./pages/MatrixPage";
|
||||
import ExecutiveDashboardPage from "./pages/ExecutiveDashboardPage";
|
||||
import TechniqueDetailPage from "./pages/TechniqueDetailPage";
|
||||
import TestsPage from "./pages/TestsPage";
|
||||
import TestCreatePage from "./pages/TestCreatePage";
|
||||
@@ -37,6 +38,14 @@ export default function App() {
|
||||
<Route path="/dashboard" element={<DashboardPage />} />
|
||||
<Route path="/techniques" element={<TechniquesPage />} />
|
||||
<Route path="/matrix" element={<MatrixPage />} />
|
||||
<Route
|
||||
path="/executive-dashboard"
|
||||
element={
|
||||
<ProtectedRoute roles={["admin", "red_lead", "blue_lead"]}>
|
||||
<ExecutiveDashboardPage />
|
||||
</ProtectedRoute>
|
||||
}
|
||||
/>
|
||||
<Route path="/techniques/:mitreId" element={<TechniqueDetailPage />} />
|
||||
<Route path="/tests" element={<TestsPage />} />
|
||||
<Route path="/tests/new" element={<TestCreatePage />} />
|
||||
|
||||
101
frontend/src/api/operational-metrics.ts
Normal file
101
frontend/src/api/operational-metrics.ts
Normal file
@@ -0,0 +1,101 @@
|
||||
import client from "./client";
|
||||
|
||||
// ── Types ────────────────────────────────────────────────────────────
|
||||
|
||||
export interface MTTDMetric {
|
||||
mean_hours: number;
|
||||
median_hours: number;
|
||||
min_hours: number;
|
||||
max_hours: number;
|
||||
sample_size: number;
|
||||
}
|
||||
|
||||
export interface MTTRMetric {
|
||||
mean_hours: number;
|
||||
median_hours: number;
|
||||
min_hours: number;
|
||||
max_hours: number;
|
||||
sample_size: number;
|
||||
}
|
||||
|
||||
export interface DetectionEfficacy {
|
||||
percentage: number;
|
||||
detected: number;
|
||||
partially: number;
|
||||
not_detected: number;
|
||||
total: number;
|
||||
}
|
||||
|
||||
export interface AlertFidelity {
|
||||
percentage: number;
|
||||
triggered: number;
|
||||
not_triggered: number;
|
||||
total_evaluated: number;
|
||||
}
|
||||
|
||||
export interface CoverageVelocity {
|
||||
techniques_per_week: number;
|
||||
trend: "improving" | "declining" | "stable";
|
||||
}
|
||||
|
||||
export interface ValidationThroughput {
|
||||
tests_per_week: number;
|
||||
trend: "improving" | "declining" | "stable";
|
||||
}
|
||||
|
||||
export interface RejectionRate {
|
||||
percentage: number;
|
||||
by_red_lead: number;
|
||||
by_blue_lead: number;
|
||||
}
|
||||
|
||||
export interface OperationalMetrics {
|
||||
mttd: MTTDMetric | null;
|
||||
mttr: MTTRMetric | null;
|
||||
detection_efficacy: DetectionEfficacy;
|
||||
alert_fidelity: AlertFidelity;
|
||||
coverage_velocity: CoverageVelocity;
|
||||
validation_throughput: ValidationThroughput;
|
||||
rejection_rate: RejectionRate;
|
||||
}
|
||||
|
||||
export interface OperationalTrendPoint {
|
||||
date: string;
|
||||
detection_efficacy: number;
|
||||
validated_tests: number;
|
||||
detected_tests: number;
|
||||
}
|
||||
|
||||
export interface TeamMetrics {
|
||||
red_team: {
|
||||
tests_completed: number;
|
||||
avg_completion_hours: number | null;
|
||||
rejection_rate: number;
|
||||
};
|
||||
blue_team: {
|
||||
tests_completed: number;
|
||||
avg_completion_hours: number | null;
|
||||
rejection_rate: number;
|
||||
};
|
||||
}
|
||||
|
||||
// ── API Functions ────────────────────────────────────────────────────
|
||||
|
||||
export async function getOperationalMetrics(): Promise<OperationalMetrics> {
|
||||
const { data } = await client.get<OperationalMetrics>("/metrics/operational");
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getOperationalTrend(
|
||||
period: string = "90d",
|
||||
): Promise<OperationalTrendPoint[]> {
|
||||
const { data } = await client.get<OperationalTrendPoint[]>("/metrics/operational/trend", {
|
||||
params: { period },
|
||||
});
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getMetricsByTeam(): Promise<TeamMetrics> {
|
||||
const { data } = await client.get<TeamMetrics>("/metrics/operational/by-team");
|
||||
return data;
|
||||
}
|
||||
100
frontend/src/api/scores.ts
Normal file
100
frontend/src/api/scores.ts
Normal file
@@ -0,0 +1,100 @@
|
||||
import client from "./client";
|
||||
|
||||
// ── Types ────────────────────────────────────────────────────────────
|
||||
|
||||
export interface ScoreBreakdownItem {
|
||||
score: number;
|
||||
max: number;
|
||||
detail: string;
|
||||
}
|
||||
|
||||
export interface TechniqueScore {
|
||||
mitre_id: string;
|
||||
name: string;
|
||||
tactic: string | null;
|
||||
status_global: string | null;
|
||||
total_score: number;
|
||||
breakdown: Record<string, ScoreBreakdownItem>;
|
||||
}
|
||||
|
||||
export interface TacticScore {
|
||||
tactic: string;
|
||||
average_score: number;
|
||||
techniques_count: number;
|
||||
techniques_scored: number;
|
||||
}
|
||||
|
||||
export interface ActorCoverageScore {
|
||||
actor_id: string;
|
||||
actor_name: string;
|
||||
total_score: number;
|
||||
techniques_count: number;
|
||||
techniques_covered: number;
|
||||
techniques_detail: Array<{
|
||||
mitre_id: string;
|
||||
name: string;
|
||||
score: number;
|
||||
breakdown: Record<string, ScoreBreakdownItem>;
|
||||
}>;
|
||||
}
|
||||
|
||||
export interface OrganizationScore {
|
||||
overall_score: number;
|
||||
total_coverage: number;
|
||||
critical_coverage: number;
|
||||
detection_maturity: number;
|
||||
response_readiness: number;
|
||||
techniques_evaluated: number;
|
||||
techniques_total: number;
|
||||
}
|
||||
|
||||
export interface ScoreHistoryPoint {
|
||||
date: string;
|
||||
score: number;
|
||||
validated_tests: number;
|
||||
}
|
||||
|
||||
export interface ScoringConfig {
|
||||
weights: {
|
||||
tests: number;
|
||||
detection_rules: number;
|
||||
d3fend: number;
|
||||
freshness: number;
|
||||
platform_diversity: number;
|
||||
};
|
||||
total: number;
|
||||
}
|
||||
|
||||
// ── API Functions ────────────────────────────────────────────────────
|
||||
|
||||
export async function getTechniqueScore(mitreId: string): Promise<TechniqueScore> {
|
||||
const { data } = await client.get<TechniqueScore>(`/scores/technique/${mitreId}`);
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getTacticScore(tactic: string): Promise<TacticScore> {
|
||||
const { data } = await client.get<TacticScore>(`/scores/tactic/${tactic}`);
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getActorCoverageScore(actorId: string): Promise<ActorCoverageScore> {
|
||||
const { data } = await client.get<ActorCoverageScore>(`/scores/threat-actor/${actorId}`);
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getOrganizationScore(): Promise<OrganizationScore> {
|
||||
const { data } = await client.get<OrganizationScore>("/scores/organization");
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getScoreHistory(period: string = "90d"): Promise<ScoreHistoryPoint[]> {
|
||||
const { data } = await client.get<ScoreHistoryPoint[]>("/scores/history", {
|
||||
params: { period },
|
||||
});
|
||||
return data;
|
||||
}
|
||||
|
||||
export async function getScoringConfig(): Promise<ScoringConfig> {
|
||||
const { data } = await client.get<ScoringConfig>("/scores/config");
|
||||
return data;
|
||||
}
|
||||
@@ -16,6 +16,7 @@ import {
|
||||
Crosshair,
|
||||
Zap,
|
||||
Grid3X3,
|
||||
Gauge,
|
||||
} from "lucide-react";
|
||||
import { useAuth } from "../context/AuthContext";
|
||||
|
||||
@@ -40,6 +41,7 @@ const mainLinks: NavItem[] = [
|
||||
{ to: "/test-catalog", label: "Test Catalog", icon: BookOpen },
|
||||
],
|
||||
},
|
||||
{ to: "/executive-dashboard", label: "Executive Dashboard", icon: Gauge },
|
||||
{ to: "/reports", label: "Reports", icon: BarChart3 },
|
||||
{ to: "/threat-actors", label: "Threat Actors", icon: Crosshair },
|
||||
{ to: "/campaigns", label: "Campaigns", icon: Zap },
|
||||
|
||||
527
frontend/src/pages/ExecutiveDashboardPage.tsx
Normal file
527
frontend/src/pages/ExecutiveDashboardPage.tsx
Normal file
@@ -0,0 +1,527 @@
|
||||
import { useQuery } from "@tanstack/react-query";
|
||||
import { useNavigate } from "react-router-dom";
|
||||
import {
|
||||
Loader2,
|
||||
AlertCircle,
|
||||
TrendingUp,
|
||||
TrendingDown,
|
||||
Minus,
|
||||
ArrowRight,
|
||||
} from "lucide-react";
|
||||
import {
|
||||
LineChart,
|
||||
Line,
|
||||
BarChart,
|
||||
Bar,
|
||||
XAxis,
|
||||
YAxis,
|
||||
CartesianGrid,
|
||||
Tooltip,
|
||||
ResponsiveContainer,
|
||||
Cell,
|
||||
} from "recharts";
|
||||
import { getOrganizationScore, getScoreHistory } from "../api/scores";
|
||||
import {
|
||||
getOperationalMetrics,
|
||||
getMetricsByTeam,
|
||||
} from "../api/operational-metrics";
|
||||
import { getCoverageByTactic } from "../api/metrics";
|
||||
import { getThreatActors } from "../api/threat-actors";
|
||||
import { getTechniques, type TechniqueSummary } from "../api/techniques";
|
||||
|
||||
// ── Score Gauge Component ────────────────────────────────────────────
|
||||
|
||||
function ScoreGauge({ score, label }: { score: number; label: string }) {
|
||||
const getColor = (s: number) => {
|
||||
if (s < 30) return "#ef4444";
|
||||
if (s < 50) return "#f97316";
|
||||
if (s < 70) return "#eab308";
|
||||
return "#22c55e";
|
||||
};
|
||||
|
||||
const color = getColor(score);
|
||||
const circumference = 2 * Math.PI * 54;
|
||||
const strokeDasharray = `${(score / 100) * circumference} ${circumference}`;
|
||||
|
||||
return (
|
||||
<div className="flex flex-col items-center">
|
||||
<div className="relative h-32 w-32">
|
||||
<svg className="h-32 w-32 -rotate-90" viewBox="0 0 120 120">
|
||||
<circle
|
||||
cx="60"
|
||||
cy="60"
|
||||
r="54"
|
||||
fill="none"
|
||||
stroke="#1f2937"
|
||||
strokeWidth="8"
|
||||
/>
|
||||
<circle
|
||||
cx="60"
|
||||
cy="60"
|
||||
r="54"
|
||||
fill="none"
|
||||
stroke={color}
|
||||
strokeWidth="8"
|
||||
strokeLinecap="round"
|
||||
strokeDasharray={strokeDasharray}
|
||||
className="transition-all duration-1000"
|
||||
/>
|
||||
</svg>
|
||||
<div className="absolute inset-0 flex flex-col items-center justify-center">
|
||||
<span className="text-3xl font-bold text-white">{Math.round(score)}</span>
|
||||
<span className="text-[10px] text-gray-500">/ 100</span>
|
||||
</div>
|
||||
</div>
|
||||
<span className="mt-2 text-xs font-medium text-gray-400">{label}</span>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
// ── KPI Card Component ──────────────────────────────────────────────
|
||||
|
||||
function KPICard({
|
||||
label,
|
||||
value,
|
||||
unit,
|
||||
trend,
|
||||
}: {
|
||||
label: string;
|
||||
value: string | number;
|
||||
unit?: string;
|
||||
trend?: "improving" | "declining" | "stable" | null;
|
||||
}) {
|
||||
const TrendIcon =
|
||||
trend === "improving"
|
||||
? TrendingUp
|
||||
: trend === "declining"
|
||||
? TrendingDown
|
||||
: Minus;
|
||||
|
||||
const trendColor =
|
||||
trend === "improving"
|
||||
? "text-green-400"
|
||||
: trend === "declining"
|
||||
? "text-red-400"
|
||||
: "text-gray-500";
|
||||
|
||||
return (
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<p className="text-xs text-gray-500 uppercase tracking-wider">{label}</p>
|
||||
<div className="mt-2 flex items-end justify-between">
|
||||
<div>
|
||||
<span className="text-2xl font-bold text-white">
|
||||
{value === null || value === undefined ? "N/A" : value}
|
||||
</span>
|
||||
{unit && <span className="ml-1 text-sm text-gray-500">{unit}</span>}
|
||||
</div>
|
||||
{trend && (
|
||||
<TrendIcon className={`h-5 w-5 ${trendColor}`} />
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
// ── Main Component ──────────────────────────────────────────────────
|
||||
|
||||
export default function ExecutiveDashboardPage() {
|
||||
const navigate = useNavigate();
|
||||
|
||||
const { data: orgScore, isLoading: loadingScore } = useQuery({
|
||||
queryKey: ["org-score"],
|
||||
queryFn: getOrganizationScore,
|
||||
});
|
||||
|
||||
const { data: scoreHistory } = useQuery({
|
||||
queryKey: ["score-history", "90d"],
|
||||
queryFn: () => getScoreHistory("90d"),
|
||||
});
|
||||
|
||||
const { data: opMetrics, isLoading: loadingMetrics } = useQuery({
|
||||
queryKey: ["operational-metrics"],
|
||||
queryFn: getOperationalMetrics,
|
||||
});
|
||||
|
||||
const { data: teamMetrics } = useQuery({
|
||||
queryKey: ["team-metrics"],
|
||||
queryFn: getMetricsByTeam,
|
||||
});
|
||||
|
||||
const { data: tacticCoverage } = useQuery({
|
||||
queryKey: ["tactic-coverage"],
|
||||
queryFn: getCoverageByTactic,
|
||||
});
|
||||
|
||||
const { data: threatActors } = useQuery({
|
||||
queryKey: ["threat-actors-top"],
|
||||
queryFn: () => getThreatActors({ limit: 5 }),
|
||||
});
|
||||
|
||||
const { data: allTechniques } = useQuery({
|
||||
queryKey: ["techniques-exec"],
|
||||
queryFn: () => getTechniques(),
|
||||
});
|
||||
|
||||
const isLoading = loadingScore || loadingMetrics;
|
||||
|
||||
if (isLoading) {
|
||||
return (
|
||||
<div className="flex h-64 items-center justify-center">
|
||||
<Loader2 className="h-8 w-8 animate-spin text-cyan-400" />
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
// Critical gaps: not_covered or not_evaluated techniques
|
||||
const criticalGaps: TechniqueSummary[] = (allTechniques || [])
|
||||
.filter((t) => t.status_global === "not_covered" || t.status_global === "not_evaluated")
|
||||
.slice(0, 10);
|
||||
|
||||
// Coverage by tactic for bar chart
|
||||
const tacticData = (tacticCoverage || []).map((tc) => ({
|
||||
name: tc.tactic
|
||||
.split("-")
|
||||
.map((w: string) => w.charAt(0).toUpperCase() + w.slice(1))
|
||||
.join(" "),
|
||||
coverage: tc.total > 0 ? Math.round(((tc.validated + tc.partial) / tc.total) * 100) : 0,
|
||||
}));
|
||||
|
||||
const getBarColor = (coverage: number) => {
|
||||
if (coverage < 30) return "#ef4444";
|
||||
if (coverage < 50) return "#f97316";
|
||||
if (coverage < 70) return "#eab308";
|
||||
return "#22c55e";
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="space-y-6">
|
||||
{/* Header */}
|
||||
<div>
|
||||
<h1 className="text-2xl font-bold text-white">Executive Dashboard</h1>
|
||||
<p className="mt-1 text-sm text-gray-400">
|
||||
Organization security posture overview
|
||||
</p>
|
||||
</div>
|
||||
|
||||
{/* Section 1: Score Card + Sub-scores */}
|
||||
<div className="grid grid-cols-1 gap-6 lg:grid-cols-4">
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-6 lg:col-span-1 flex flex-col items-center justify-center">
|
||||
<ScoreGauge
|
||||
score={orgScore?.overall_score ?? 0}
|
||||
label="Overall Score"
|
||||
/>
|
||||
<div className="mt-4 grid w-full grid-cols-2 gap-2">
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{orgScore?.total_coverage ?? 0}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Coverage</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{orgScore?.detection_maturity ?? 0}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Detection</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{orgScore?.critical_coverage ?? 0}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Critical</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{orgScore?.response_readiness ?? 0}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Response</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Section 2: Trend Chart */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4 lg:col-span-3">
|
||||
<h2 className="mb-3 text-sm font-semibold text-gray-300">
|
||||
Score Trend (90 days)
|
||||
</h2>
|
||||
<ResponsiveContainer width="100%" height={220}>
|
||||
<LineChart data={scoreHistory || []}>
|
||||
<CartesianGrid strokeDasharray="3 3" stroke="#1f2937" />
|
||||
<XAxis
|
||||
dataKey="date"
|
||||
tick={{ fill: "#6b7280", fontSize: 10 }}
|
||||
tickFormatter={(val) => {
|
||||
const d = new Date(val);
|
||||
return `${d.getMonth() + 1}/${d.getDate()}`;
|
||||
}}
|
||||
/>
|
||||
<YAxis
|
||||
domain={[0, 100]}
|
||||
tick={{ fill: "#6b7280", fontSize: 10 }}
|
||||
/>
|
||||
<Tooltip
|
||||
contentStyle={{
|
||||
backgroundColor: "#111827",
|
||||
border: "1px solid #374151",
|
||||
borderRadius: "8px",
|
||||
fontSize: "12px",
|
||||
}}
|
||||
labelStyle={{ color: "#9ca3af" }}
|
||||
/>
|
||||
<Line
|
||||
type="monotone"
|
||||
dataKey="score"
|
||||
stroke="#06b6d4"
|
||||
strokeWidth={2}
|
||||
dot={false}
|
||||
name="Score"
|
||||
/>
|
||||
</LineChart>
|
||||
</ResponsiveContainer>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Section 3: Top Threat Actors */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<h2 className="mb-3 text-sm font-semibold text-gray-300">
|
||||
Top Threat Actors
|
||||
</h2>
|
||||
<div className="space-y-2">
|
||||
{(threatActors?.items || []).map((actor) => (
|
||||
<div
|
||||
key={actor.id}
|
||||
className="flex items-center gap-3 rounded-lg bg-gray-800/50 p-3 cursor-pointer hover:bg-gray-800"
|
||||
onClick={() => navigate(`/threat-actors/${actor.id}`)}
|
||||
>
|
||||
<div className="flex h-8 w-8 items-center justify-center rounded-full bg-gray-700 text-xs font-bold text-gray-300">
|
||||
{actor.country?.slice(0, 2).toUpperCase() || "??"}
|
||||
</div>
|
||||
<div className="flex-1 min-w-0">
|
||||
<p className="text-sm font-medium text-white truncate">
|
||||
{actor.name}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500 truncate">
|
||||
{actor.target_sectors?.slice(0, 3).join(", ")}
|
||||
</p>
|
||||
</div>
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="w-24 h-2 rounded-full bg-gray-700 overflow-hidden">
|
||||
<div
|
||||
className="h-full rounded-full transition-all"
|
||||
style={{
|
||||
width: `${actor.coverage_pct}%`,
|
||||
backgroundColor:
|
||||
actor.coverage_pct > 70
|
||||
? "#22c55e"
|
||||
: actor.coverage_pct > 40
|
||||
? "#eab308"
|
||||
: "#ef4444",
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
<span className="w-10 text-right text-xs font-medium text-gray-300">
|
||||
{actor.coverage_pct}%
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Section 4: Operational KPIs */}
|
||||
<div className="grid grid-cols-2 gap-4 lg:grid-cols-4">
|
||||
<KPICard
|
||||
label="MTTD"
|
||||
value={opMetrics?.mttd?.mean_hours ?? "N/A"}
|
||||
unit={opMetrics?.mttd ? "hrs" : undefined}
|
||||
/>
|
||||
<KPICard
|
||||
label="MTTR"
|
||||
value={opMetrics?.mttr?.mean_hours ?? "N/A"}
|
||||
unit={opMetrics?.mttr ? "hrs" : undefined}
|
||||
/>
|
||||
<KPICard
|
||||
label="Detection Efficacy"
|
||||
value={opMetrics?.detection_efficacy?.percentage ?? 0}
|
||||
unit="%"
|
||||
/>
|
||||
<KPICard
|
||||
label="Validation Throughput"
|
||||
value={opMetrics?.validation_throughput?.tests_per_week ?? 0}
|
||||
unit="/week"
|
||||
trend={opMetrics?.validation_throughput?.trend}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{/* Section 5: Coverage by Tactic */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<h2 className="mb-3 text-sm font-semibold text-gray-300">
|
||||
Coverage by Tactic
|
||||
</h2>
|
||||
<ResponsiveContainer width="100%" height={300}>
|
||||
<BarChart
|
||||
data={tacticData}
|
||||
layout="vertical"
|
||||
margin={{ left: 120 }}
|
||||
>
|
||||
<CartesianGrid strokeDasharray="3 3" stroke="#1f2937" />
|
||||
<XAxis
|
||||
type="number"
|
||||
domain={[0, 100]}
|
||||
tick={{ fill: "#6b7280", fontSize: 10 }}
|
||||
tickFormatter={(v) => `${v}%`}
|
||||
/>
|
||||
<YAxis
|
||||
type="category"
|
||||
dataKey="name"
|
||||
width={120}
|
||||
tick={{ fill: "#9ca3af", fontSize: 10 }}
|
||||
/>
|
||||
<Tooltip
|
||||
contentStyle={{
|
||||
backgroundColor: "#111827",
|
||||
border: "1px solid #374151",
|
||||
borderRadius: "8px",
|
||||
fontSize: "12px",
|
||||
}}
|
||||
formatter={(value: number) => [`${value}%`, "Coverage"]}
|
||||
/>
|
||||
<Bar dataKey="coverage" radius={[0, 4, 4, 0]}>
|
||||
{tacticData.map((entry, index) => (
|
||||
<Cell
|
||||
key={`cell-${index}`}
|
||||
fill={getBarColor(entry.coverage)}
|
||||
/>
|
||||
))}
|
||||
</Bar>
|
||||
</BarChart>
|
||||
</ResponsiveContainer>
|
||||
</div>
|
||||
|
||||
{/* Section 6: Critical Gaps */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<h2 className="mb-3 text-sm font-semibold text-gray-300">
|
||||
Critical Gaps (Top 10 Uncovered Techniques)
|
||||
</h2>
|
||||
<div className="overflow-x-auto">
|
||||
<table className="w-full text-sm">
|
||||
<thead>
|
||||
<tr className="border-b border-gray-800 text-left text-xs text-gray-500">
|
||||
<th className="pb-2 pr-4">MITRE ID</th>
|
||||
<th className="pb-2 pr-4">Name</th>
|
||||
<th className="pb-2 pr-4">Tactic</th>
|
||||
<th className="pb-2 pr-4">Status</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody>
|
||||
{criticalGaps.map((tech) => (
|
||||
<tr
|
||||
key={tech.mitre_id}
|
||||
className="border-b border-gray-800/50 cursor-pointer hover:bg-gray-800/30"
|
||||
onClick={() => navigate(`/techniques/${tech.mitre_id}`)}
|
||||
>
|
||||
<td className="py-2 pr-4 font-mono text-xs text-cyan-400">
|
||||
{tech.mitre_id}
|
||||
</td>
|
||||
<td className="py-2 pr-4 text-gray-300 truncate max-w-[200px]">
|
||||
{tech.name}
|
||||
</td>
|
||||
<td className="py-2 pr-4 text-gray-500 text-xs">
|
||||
{tech.tactic
|
||||
?.split(",")[0]
|
||||
.trim()
|
||||
.split("-")
|
||||
.map((w: string) => w.charAt(0).toUpperCase() + w.slice(1))
|
||||
.join(" ")}
|
||||
</td>
|
||||
<td className="py-2 pr-4">
|
||||
<span
|
||||
className={`inline-block rounded-full px-2 py-0.5 text-[10px] font-medium ${
|
||||
tech.status_global === "not_covered"
|
||||
? "bg-red-500/10 text-red-400"
|
||||
: "bg-gray-500/10 text-gray-400"
|
||||
}`}
|
||||
>
|
||||
{tech.status_global?.replace(/_/g, " ")}
|
||||
</span>
|
||||
</td>
|
||||
</tr>
|
||||
))}
|
||||
{criticalGaps.length === 0 && (
|
||||
<tr>
|
||||
<td colSpan={4} className="py-4 text-center text-gray-500">
|
||||
No critical gaps found
|
||||
</td>
|
||||
</tr>
|
||||
)}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Section 7: Team Performance */}
|
||||
{teamMetrics && (
|
||||
<div className="grid grid-cols-1 gap-4 lg:grid-cols-2">
|
||||
{/* Red Team */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<h2 className="mb-3 flex items-center gap-2 text-sm font-semibold text-red-400">
|
||||
<div className="h-2 w-2 rounded-full bg-red-500" />
|
||||
Red Team
|
||||
</h2>
|
||||
<div className="grid grid-cols-3 gap-3">
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.red_team.tests_completed}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Tests Done</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.red_team.avg_completion_hours
|
||||
? `${teamMetrics.red_team.avg_completion_hours}h`
|
||||
: "N/A"}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Avg Time</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.red_team.rejection_rate}%
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Rejection</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Blue Team */}
|
||||
<div className="rounded-xl border border-gray-800 bg-gray-900 p-4">
|
||||
<h2 className="mb-3 flex items-center gap-2 text-sm font-semibold text-blue-400">
|
||||
<div className="h-2 w-2 rounded-full bg-blue-500" />
|
||||
Blue Team
|
||||
</h2>
|
||||
<div className="grid grid-cols-3 gap-3">
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.blue_team.tests_completed}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Tests Done</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.blue_team.avg_completion_hours
|
||||
? `${teamMetrics.blue_team.avg_completion_hours}h`
|
||||
: "N/A"}
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Avg Time</p>
|
||||
</div>
|
||||
<div className="rounded-lg bg-gray-800 px-3 py-2 text-center">
|
||||
<p className="text-lg font-bold text-white">
|
||||
{teamMetrics.blue_team.rejection_rate}%
|
||||
</p>
|
||||
<p className="text-[10px] text-gray-500">Rejection</p>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
Reference in New Issue
Block a user