feat(scoring): composite recency decay and severity weights persisted in DB [FASE-5.1]

backend/alembic/versions/b030_phase5_scoring_and_snapshots.py

@@ -0,0 +1,117 @@
+"""Phase 5: scoring recency/severity columns and snapshot breakdown fields.
+
+Revision ID: b030phase5
+Revises: b029phase3
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import postgresql
+
+revision: str = "b030phase5"
+down_revision: Union[str, None] = "b029phase3"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def _column_names(table: str) -> set[str]:
+    bind = op.get_bind()
+    insp = sa.inspect(bind)
+    return {c["name"] for c in insp.get_columns(table)}
+
+
+def upgrade() -> None:
+    snap_cols = _column_names("coverage_snapshots")
+    if "by_tactic" not in snap_cols:
+        op.add_column(
+            "coverage_snapshots",
+            sa.Column("by_tactic", postgresql.JSONB(), nullable=False, server_default="{}"),
+        )
+    if "by_status" not in snap_cols:
+        op.add_column(
+            "coverage_snapshots",
+            sa.Column("by_status", postgresql.JSONB(), nullable=False, server_default="{}"),
+        )
+    if "stale_count" not in snap_cols:
+        op.add_column(
+            "coverage_snapshots",
+            sa.Column("stale_count", sa.Integer(), nullable=False, server_default="0"),
+        )
+    if "never_tested_count" not in snap_cols:
+        op.add_column(
+            "coverage_snapshots",
+            sa.Column("never_tested_count", sa.Integer(), nullable=False, server_default="0"),
+        )
+    if "coverage_percentage" not in snap_cols:
+        op.add_column(
+            "coverage_snapshots",
+            sa.Column("coverage_percentage", sa.Float(), nullable=False, server_default="0"),
+        )
+
+    cfg_cols = _column_names("scoring_config")
+    if "weight_recency" not in cfg_cols and "weight_freshness" in cfg_cols:
+        op.alter_column(
+            "scoring_config",
+            "weight_freshness",
+            new_column_name="weight_recency",
+        )
+        cfg_cols.remove("weight_freshness")
+        cfg_cols.add("weight_recency")
+    elif "weight_recency" not in cfg_cols:
+        op.add_column(
+            "scoring_config",
+            sa.Column("weight_recency", sa.Float(), nullable=False, server_default="10.0"),
+        )
+
+    if "weight_severity" not in cfg_cols and "weight_platform_diversity" in cfg_cols:
+        op.alter_column(
+            "scoring_config",
+            "weight_platform_diversity",
+            new_column_name="weight_severity",
+        )
+    elif "weight_severity" not in cfg_cols:
+        op.add_column(
+            "scoring_config",
+            sa.Column("weight_severity", sa.Float(), nullable=False, server_default="10.0"),
+        )
+
+    if "updated_by" not in cfg_cols:
+        op.add_column(
+            "scoring_config",
+            sa.Column(
+                "updated_by",
+                postgresql.UUID(as_uuid=True),
+                sa.ForeignKey("users.id", ondelete="SET NULL"),
+                nullable=True,
+            ),
+        )
+
+
+def downgrade() -> None:
+    cfg_cols = _column_names("scoring_config")
+    if "updated_by" in cfg_cols:
+        op.drop_column("scoring_config", "updated_by")
+    if "weight_severity" in cfg_cols:
+        op.alter_column(
+            "scoring_config",
+            "weight_severity",
+            new_column_name="weight_platform_diversity",
+        )
+    if "weight_recency" in cfg_cols:
+        op.alter_column(
+            "scoring_config",
+            "weight_recency",
+            new_column_name="weight_freshness",
+        )
+
+    for col in (
+        "coverage_percentage",
+        "never_tested_count",
+        "stale_count",
+        "by_status",
+        "by_tactic",
+    ):
+        if col in _column_names("coverage_snapshots"):
+            op.drop_column("coverage_snapshots", col)

backend/app/config.py

@@ -72,9 +72,12 @@ class Settings(BaseSettings):
 
     # ── Scoring weights (must sum to 100) ────────────────────────────
     SCORING_WEIGHT_TESTS: int = 40
-    SCORING_WEIGHT_DETECTION_RULES: int = 20
+    SCORING_WEIGHT_DETECTION_RULES: int = 25
     SCORING_WEIGHT_D3FEND: int = 15
-    SCORING_WEIGHT_FRESHNESS: int = 15
+    SCORING_WEIGHT_RECENCY: int = 10
+    SCORING_WEIGHT_SEVERITY: int = 10
+    # Legacy env names (mapped in scoring_config_service)
+    SCORING_WEIGHT_FRESHNESS: int = 10
     SCORING_WEIGHT_PLATFORM_DIVERSITY: int = 10
 
     class Config:

backend/app/domain/value_objects/scoring_weights.py

@@ -15,16 +15,16 @@ class ScoringWeights:
     tests: float
     detection_rules: float
     d3fend: float
-    freshness: float
+    recency: float
-    platform_diversity: float
+    severity: float
 
     def __post_init__(self) -> None:
         fields = [
             self.tests,
             self.detection_rules,
             self.d3fend,
-            self.freshness,
+            self.recency,
-            self.platform_diversity,
+            self.severity,
         ]
         for f in fields:
             if f < 0:
@@ -43,6 +43,15 @@ class ScoringWeights:
             tests=40.0,
             detection_rules=25.0,
             d3fend=15.0,
-            freshness=10.0,
+            recency=10.0,
-            platform_diversity=10.0,
+            severity=10.0,
         )
+
+    # Backward-compatible aliases for older API payloads
+    @property
+    def freshness(self) -> float:
+        return self.recency
+
+    @property
+    def platform_diversity(self) -> float:
+        return self.severity

backend/app/models/coverage_snapshot.py

@@ -10,7 +10,7 @@ from sqlalchemy import (
     Column, String, Float, Integer, DateTime,
     ForeignKey, Index, func,
 )
-from sqlalchemy.dialects.postgresql import UUID
+from sqlalchemy.dialects.postgresql import JSONB, UUID
 from sqlalchemy.orm import relationship
 
 from app.database import Base
@@ -30,6 +30,11 @@ class CoverageSnapshot(Base):
     not_covered_count = Column(Integer, nullable=False)
     in_progress_count = Column(Integer, nullable=False)
     not_evaluated_count = Column(Integer, nullable=False)
+    coverage_percentage = Column(Float, nullable=False, default=0.0)
+    by_tactic = Column(JSONB, nullable=False, default=dict)
+    by_status = Column(JSONB, nullable=False, default=dict)
+    stale_count = Column(Integer, nullable=False, default=0)
+    never_tested_count = Column(Integer, nullable=False, default=0)
     created_by = Column(
         UUID(as_uuid=True),
         ForeignKey("users.id", ondelete="SET NULL"),

backend/app/models/scoring_config.py

@@ -1,12 +1,8 @@
-"""ScoringConfig — single-row table for persisted scoring weights.
+"""ScoringConfig — single-row table for persisted scoring weights."""
-
-Replaces the mutable-settings approach where PATCH /scores/config
-mutated the in-process ``Settings`` object (lost on restart).
-"""
 
 import uuid
 
-from sqlalchemy import Column, Float, DateTime, func
+from sqlalchemy import Column, Float, DateTime, ForeignKey, func
 from sqlalchemy.dialects.postgresql import UUID
 
 from app.database import Base
@@ -17,8 +13,13 @@ class ScoringConfig(Base):
 
     id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4)
     weight_tests = Column(Float, nullable=False, default=40.0)
-    weight_detection_rules = Column(Float, nullable=False, default=20.0)
+    weight_detection_rules = Column(Float, nullable=False, default=25.0)
     weight_d3fend = Column(Float, nullable=False, default=15.0)
-    weight_freshness = Column(Float, nullable=False, default=15.0)
+    weight_recency = Column(Float, nullable=False, default=10.0)
-    weight_platform_diversity = Column(Float, nullable=False, default=10.0)
+    weight_severity = Column(Float, nullable=False, default=10.0)
+    updated_by = Column(
+        UUID(as_uuid=True),
+        ForeignKey("users.id", ondelete="SET NULL"),
+        nullable=True,
+    )
     updated_at = Column(DateTime(timezone=True), server_default=func.now(), onupdate=func.now())

backend/app/routers/scores.py

@@ -113,6 +113,8 @@ class ScoringConfigUpdate(BaseModel):
     tests: Optional[float] = None
     detection_rules: Optional[float] = None
     d3fend: Optional[float] = None
+    recency: Optional[float] = None
+    severity: Optional[float] = None
     freshness: Optional[float] = None
     platform_diversity: Optional[float] = None
 
@@ -134,8 +136,11 @@ def update_scoring_config(
             tests=payload.tests,
             detection_rules=payload.detection_rules,
             d3fend=payload.d3fend,
+            recency=payload.recency,
+            severity=payload.severity,
             freshness=payload.freshness,
             platform_diversity=payload.platform_diversity,
+            updated_by=current_user.id,
         )
         uow.commit()
 

backend/app/routers/snapshots.py

@@ -21,6 +21,7 @@ from app.services.snapshot_service import (
     create_snapshot,
     compare_snapshots,
     cleanup_old_snapshots,
+    get_coverage_evolution,
     serialize_snapshot_summary,
     list_snapshots as list_snapshots_svc,
     get_snapshot_or_raise,
@@ -82,6 +83,21 @@ def create_snapshot_endpoint(
     return serialize_snapshot_summary(snapshot)
 
 
+# ---------------------------------------------------------------------------
+# GET /snapshots/evolution — Coverage trend over time
+# ---------------------------------------------------------------------------
+
+
+@router.get("/evolution")
+def coverage_evolution(
+    months: int = Query(12, ge=1, le=36),
+    db: Session = Depends(get_db),
+    current_user: User = Depends(get_current_user),
+):
+    """Return coverage snapshots for trend charts (last *months* months)."""
+    return get_coverage_evolution(db, months=months)
+
+
 # ---------------------------------------------------------------------------
 # GET /snapshots/compare — Compare two snapshots
 # ---------------------------------------------------------------------------

backend/app/services/scoring_config_service.py

@@ -1,14 +1,8 @@
-"""Scoring configuration persistence service.
+"""Scoring configuration persistence service."""
-
-Reads and writes scoring weights from the ``scoring_config`` table.
-Falls back to environment-variable defaults (from ``Settings``) when
-no row has been persisted yet.
-
-This module is framework-agnostic: no FastAPI imports.
-"""
 
 from __future__ import annotations
 
+import uuid
 from typing import Any
 
 from sqlalchemy.orm import Session
@@ -18,29 +12,39 @@ from app.domain.value_objects.scoring_weights import ScoringWeights
 from app.models.scoring_config import ScoringConfig
 
 
-def get_scoring_weights(db: Session) -> ScoringWeights:
+def _row_recency(row: ScoringConfig) -> float:
-    """Return the active scoring weights.
+    return float(getattr(row, "weight_recency", None) or getattr(row, "weight_freshness", 10.0))
 
-    Reads the single ``scoring_config`` row.  If the table is empty
+
-    (first run or migration just applied), falls back to the values
+def _row_severity(row: ScoringConfig) -> float:
-    from the environment / ``Settings``.
+    return float(
-    """
+        getattr(row, "weight_severity", None)
+        or getattr(row, "weight_platform_diversity", 10.0)
+    )
+
+
+def get_scoring_weights(db: Session) -> ScoringWeights:
+    """Return the active scoring weights from the database or env defaults."""
     row = db.query(ScoringConfig).first()
     if row is not None:
         return ScoringWeights(
             tests=row.weight_tests,
             detection_rules=row.weight_detection_rules,
             d3fend=row.weight_d3fend,
-            freshness=row.weight_freshness,
+            recency=_row_recency(row),
-            platform_diversity=row.weight_platform_diversity,
+            severity=_row_severity(row),
         )
 
     return ScoringWeights(
         tests=float(settings.SCORING_WEIGHT_TESTS),
         detection_rules=float(settings.SCORING_WEIGHT_DETECTION_RULES),
         d3fend=float(settings.SCORING_WEIGHT_D3FEND),
-        freshness=float(settings.SCORING_WEIGHT_FRESHNESS),
+        recency=float(
-        platform_diversity=float(settings.SCORING_WEIGHT_PLATFORM_DIVERSITY),
+            getattr(settings, "SCORING_WEIGHT_RECENCY", settings.SCORING_WEIGHT_FRESHNESS)
+        ),
+        severity=float(
+            getattr(settings, "SCORING_WEIGHT_SEVERITY", settings.SCORING_WEIGHT_PLATFORM_DIVERSITY)
+        ),
     )
 
 
@@ -50,25 +54,26 @@ def update_scoring_weights(
     tests: float | None = None,
     detection_rules: float | None = None,
     d3fend: float | None = None,
+    recency: float | None = None,
+    severity: float | None = None,
     freshness: float | None = None,
     platform_diversity: float | None = None,
+    updated_by: uuid.UUID | None = None,
 ) -> dict[str, Any]:
-    """Upsert scoring weights into the database.
+    """Upsert scoring weights. Does not commit."""
+    if freshness is not None and recency is None:
+        recency = freshness
+    if platform_diversity is not None and severity is None:
+        severity = platform_diversity
 
-    Only provided fields are overwritten; ``None`` values keep the
-    current (or default) value.  Validates via ``ScoringWeights``
-    before persisting.
-
-    Returns a dict with ``weights`` and ``total``.
-    """
     current = get_scoring_weights(db)
 
     new = ScoringWeights(
         tests=tests if tests is not None else current.tests,
         detection_rules=detection_rules if detection_rules is not None else current.detection_rules,
         d3fend=d3fend if d3fend is not None else current.d3fend,
-        freshness=freshness if freshness is not None else current.freshness,
+        recency=recency if recency is not None else current.recency,
-        platform_diversity=platform_diversity if platform_diversity is not None else current.platform_diversity,
+        severity=severity if severity is not None else current.severity,
     )
 
     row = db.query(ScoringConfig).first()
@@ -79,10 +84,17 @@ def update_scoring_weights(
     row.weight_tests = new.tests
     row.weight_detection_rules = new.detection_rules
     row.weight_d3fend = new.d3fend
-    row.weight_freshness = new.freshness
+    if hasattr(row, "weight_recency"):
-    row.weight_platform_diversity = new.platform_diversity
+        row.weight_recency = new.recency
+    elif hasattr(row, "weight_freshness"):
+        row.weight_freshness = new.recency
+    if hasattr(row, "weight_severity"):
+        row.weight_severity = new.severity
+    elif hasattr(row, "weight_platform_diversity"):
+        row.weight_platform_diversity = new.severity
+    if updated_by is not None and hasattr(row, "updated_by"):
+        row.updated_by = updated_by
 
-    # Does not commit; caller (router) uses UnitOfWork.
     return _weights_dict(new)
 
 
@@ -96,10 +108,15 @@ def _weights_dict(w: ScoringWeights) -> dict[str, Any]:
         "tests": w.tests,
         "detection_rules": w.detection_rules,
         "d3fend": w.d3fend,
-        "freshness": w.freshness,
+        "recency": w.recency,
-        "platform_diversity": w.platform_diversity,
+        "severity": w.severity,
+        # Legacy keys for older clients
+        "freshness": w.recency,
+        "platform_diversity": w.severity,
     }
     return {
         "weights": weights,
-        "total": sum(weights.values()),
+        "total": sum(
+            [w.tests, w.detection_rules, w.d3fend, w.recency, w.severity]
+        ),
     }

backend/app/services/scoring_service.py

@@ -9,7 +9,7 @@ fixed number of aggregated queries so that organisation-wide calculations
 never produce N+1 traffic.
 """
 
-from datetime import datetime, timedelta
+from datetime import datetime, timedelta, timezone
 from typing import Optional
 
 from sqlalchemy import case, func
@@ -25,6 +25,61 @@ from app.models.threat_actor import ThreatActor, ThreatActorTechnique
 from app.models.enums import TestState, TestResult
 from app.services.scoring_config_service import get_scoring_weights
 
+_SEVERITY_FACTORS: dict[str, float] = {
+    "critical": 1.0,
+    "high": 0.85,
+    "medium": 0.65,
+    "low": 0.5,
+}
+
+
+def _recency_factor(last_tested: datetime | None) -> float:
+    """Decay factor: 1.0 when recent, decreasing over time."""
+    if not last_tested:
+        return 0.0
+    now = datetime.now(timezone.utc)
+    tested = last_tested
+    if tested.tzinfo is None:
+        tested = tested.replace(tzinfo=timezone.utc)
+    days_ago = (now - tested).days
+    if days_ago <= 90:
+        return 1.0
+    if days_ago <= 180:
+        return 0.8
+    if days_ago <= 365:
+        return 0.5
+    return 0.2
+
+
+def _severity_factor(severity_label: str | None) -> float:
+    """Map template severity to a 0–1 multiplier."""
+    if not severity_label:
+        return 0.7
+    return _SEVERITY_FACTORS.get(severity_label.lower(), 0.7)
+
+
+def _max_severity_by_mitre(db: Session) -> dict[str, str]:
+    """Highest severity label per MITRE id from active test templates."""
+    from app.models.test_template import TestTemplate
+
+    order = {"critical": 4, "high": 3, "medium": 2, "low": 1}
+    rows = (
+        db.query(TestTemplate.mitre_technique_id, TestTemplate.severity)
+        .filter(
+            TestTemplate.is_active == True,  # noqa: E712
+            TestTemplate.severity.isnot(None),
+        )
+        .all()
+    )
+    best: dict[str, str] = {}
+    for mitre_id, severity in rows:
+        if not mitre_id or not severity:
+            continue
+        current = best.get(mitre_id)
+        if current is None or order.get(severity.lower(), 0) > order.get(current.lower(), 0):
+            best[mitre_id] = severity
+    return best
+
 
 # ── Bulk scoring helpers (5 queries for ALL techniques) ───────────────
 
@@ -45,8 +100,15 @@ def bulk_technique_scores(db: Session) -> dict:
     w_tests = w.tests
     w_detection = w.detection_rules
     w_d3fend = w.d3fend
-    w_freshness = w.freshness
+    w_recency = w.recency
-    w_diversity = w.platform_diversity
+    w_severity = w.severity
+    severity_by_mitre = _max_severity_by_mitre(db)
+
+    last_validated = func.coalesce(
+        Test.blue_validated_at,
+        Test.red_validated_at,
+        Test.created_at,
+    )
 
     # Q1: test stats grouped by technique_id
     test_rows = (
@@ -56,8 +118,7 @@ def bulk_technique_scores(db: Session) -> dict:
             func.count(
                 case((Test.detection_result == TestResult.detected, Test.id))
             ).label("detected_count"),
-            func.max(Test.red_validated_at).label("latest_validated_at"),
+            func.max(last_validated).label("latest_validated_at"),
-            func.count(func.distinct(Test.platform)).label("platform_count"),
         )
         .filter(Test.state == TestState.validated)
         .group_by(Test.technique_id)
@@ -70,7 +131,6 @@ def bulk_technique_scores(db: Session) -> dict:
             "validated": row.validated_count,
             "detected": row.detected_count,
             "latest_validated_at": row.latest_validated_at,
-            "platform_count": row.platform_count,
         }
 
     # Q2: active detection rules per mitre_id
@@ -114,7 +174,6 @@ def bulk_technique_scores(db: Session) -> dict:
     # Q5: all techniques
     techniques = db.query(Technique).all()
 
-    now = datetime.utcnow()
     results: dict = {}
 
     for tech in techniques:
@@ -122,7 +181,6 @@ def bulk_technique_scores(db: Session) -> dict:
         validated = ts.get("validated", 0)
         detected = ts.get("detected", 0)
         latest_at = ts.get("latest_validated_at")
-        plat_count = ts.get("platform_count", 0)
 
         breakdown = {}
 
@@ -177,47 +235,41 @@ def bulk_technique_scores(db: Session) -> dict:
             ),
         }
 
-        # 4. Freshness
+        # 4. Recency decay
+        recency_mult = _recency_factor(latest_at)
+        recency_score = round(recency_mult * w_recency, 1)
         if latest_at:
-            days_ago = (now - latest_at).days
+            tested = latest_at
-            if days_ago < 90:
+            if tested.tzinfo is None:
-                freshness_pct = 1.0
+                days_ago = (datetime.utcnow() - tested).days
-            elif days_ago < 180:
-                freshness_pct = 0.5
             else:
-                freshness_pct = 0.0
+                days_ago = (datetime.now(timezone.utc) - tested.astimezone(timezone.utc)).days
-            freshness_score = round(freshness_pct * w_freshness, 1)
+            recency_detail = f"Last validated {days_ago} days ago (factor {recency_mult})"
-            freshness_detail = f"Last test {days_ago} days ago"
         else:
-            freshness_score = 0
+            recency_detail = "No validated tests"
-            freshness_detail = "No validated tests"
+        breakdown["recency"] = {
-        breakdown["freshness"] = {
+            "score": recency_score,
-            "score": freshness_score,
+            "max": w_recency,
-            "max": w_freshness,
+            "detail": recency_detail,
-            "detail": freshness_detail,
         }
 
-        # 5. Platform diversity
+        # 5. Severity / criticality (template-driven)
-        available = tech.platforms or []
+        sev_label = severity_by_mitre.get(tech.mitre_id)
-        total_platforms = len(available) if available else 3
+        sev_mult = _severity_factor(sev_label)
-        if total_platforms > 0 and plat_count > 0:
+        severity_score = round(sev_mult * w_severity, 1)
-            diversity_score = round(
+        breakdown["severity"] = {
-                min(plat_count / total_platforms, 1.0) * w_diversity, 1,
+            "score": severity_score,
-            )
+            "max": w_severity,
-        else:
-            diversity_score = 0
-        breakdown["platform_diversity"] = {
-            "score": diversity_score,
-            "max": w_diversity,
             "detail": (
-                f"{plat_count}/{total_platforms} platforms covered"
+                f"Template severity: {sev_label} (factor {sev_mult})"
-                if plat_count > 0 else "No platforms tested"
+                if sev_label
+                else "No severity template (default factor)"
             ),
         }
 
         total = min(
             test_score + detection_score + d3fend_score
-            + freshness_score + diversity_score,
+            + recency_score + severity_score,
             100,
         )
         results[tech.id] = {
@@ -265,8 +317,9 @@ def calculate_technique_score(technique: Technique, db: Session) -> dict:
     w_tests = w.tests
     w_detection = w.detection_rules
     w_d3fend = w.d3fend
-    w_freshness = w.freshness
+    w_recency = w.recency
-    w_diversity = w.platform_diversity
+    w_severity = w.severity
+    severity_by_mitre = _max_severity_by_mitre(db)
 
     breakdown = {}
 
@@ -360,65 +413,50 @@ def calculate_technique_score(technique: Technique, db: Session) -> dict:
         else "No D3FEND mappings",
     }
 
-    # ── 4. Freshness ──────────────────────────────────────────────
+    # ── 4. Recency ────────────────────────────────────────────────
-    most_recent_test = (
+    most_recent_test = None
-        db.query(func.max(Test.red_validated_at))
+    for t in validated_tests:
-        .filter(
+        candidate = t.blue_validated_at or t.red_validated_at or t.created_at
-            Test.technique_id == technique.id,
+        if candidate and (most_recent_test is None or candidate > most_recent_test):
-            Test.state == TestState.validated,
+            most_recent_test = candidate
-        )
-        .scalar()
-    )
 
-    now = datetime.utcnow()
+    recency_mult = _recency_factor(most_recent_test)
+    recency_score = round(recency_mult * w_recency, 1)
     if most_recent_test:
-        days_ago = (now - most_recent_test).days
+        days_ago = (
-        if days_ago < 90:
+            datetime.now(timezone.utc) - (
-            freshness_pct = 1.0
+                most_recent_test.replace(tzinfo=timezone.utc)
-        elif days_ago < 180:
+                if most_recent_test.tzinfo is None
-            freshness_pct = 0.5
+                else most_recent_test.astimezone(timezone.utc)
-        else:
+            )
-            freshness_pct = 0.0
+        ).days
-        freshness_score = round(freshness_pct * w_freshness, 1)
+        recency_detail = f"Last validated {days_ago} days ago (factor {recency_mult})"
-        freshness_detail = f"Last test {days_ago} days ago"
     else:
-        freshness_pct = 0
+        recency_detail = "No validated tests"
-        freshness_score = 0
-        freshness_detail = "No validated tests"
 
-    breakdown["freshness"] = {
+    breakdown["recency"] = {
-        "score": freshness_score,
+        "score": recency_score,
-        "max": w_freshness,
+        "max": w_recency,
-        "detail": freshness_detail,
+        "detail": recency_detail,
     }
 
-    # ── 5. Platform diversity ─────────────────────────────────────
+    # ── 5. Severity ───────────────────────────────────────────────
-    available_platforms = technique.platforms or []
+    sev_label = severity_by_mitre.get(technique.mitre_id)
-    total_platforms = len(available_platforms) if available_platforms else 3
+    sev_mult = _severity_factor(sev_label)
-
+    severity_score = round(sev_mult * w_severity, 1)
-    tested_platforms = set()
+    breakdown["severity"] = {
-    for t in validated_tests:
+        "score": severity_score,
-        if t.platform:
+        "max": w_severity,
-            tested_platforms.add(t.platform.lower())
+        "detail": (
-
+            f"Template severity: {sev_label} (factor {sev_mult})"
-    if total_platforms > 0 and tested_platforms:
+            if sev_label
-        diversity_ratio = min(len(tested_platforms) / total_platforms, 1.0)
+            else "No severity template (default factor)"
-        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,
+        test_score + detection_score + d3fend_score + recency_score + severity_score,
         100,
     )
 

backend/app/services/snapshot_service.py

@@ -9,7 +9,8 @@ number of SQL queries regardless of technique count.
 
 import logging
 import uuid
-from datetime import datetime
+from collections import defaultdict
+from datetime import datetime, timedelta, timezone
 
 from sqlalchemy import func
 from sqlalchemy.orm import Session
@@ -43,6 +44,11 @@ def serialize_snapshot_summary(snap: CoverageSnapshot) -> dict:
         "not_covered_count": snap.not_covered_count,
         "in_progress_count": snap.in_progress_count,
         "not_evaluated_count": snap.not_evaluated_count,
+        "coverage_percentage": getattr(snap, "coverage_percentage", 0.0),
+        "by_tactic": getattr(snap, "by_tactic", None) or {},
+        "by_status": getattr(snap, "by_status", None) or {},
+        "stale_count": getattr(snap, "stale_count", 0),
+        "never_tested_count": getattr(snap, "never_tested_count", 0),
         "created_by": str(snap.created_by) if snap.created_by else None,
         "created_at": snap.created_at.isoformat() if snap.created_at else None,
     }
@@ -148,6 +154,13 @@ def create_snapshot(
     not_covered_count = 0
     in_progress_count = 0
     not_evaluated_count = 0
+    stale_count = 0
+    never_tested_count = 0
+
+    by_tactic: dict[str, dict] = defaultdict(
+        lambda: {"total": 0, "validated": 0, "partial": 0, "score_sum": 0.0}
+    )
+    by_status: dict[str, int] = defaultdict(int)
 
     technique_rows: list[dict] = []
 
@@ -170,15 +183,43 @@ def create_snapshot(
             not_evaluated_count += 1
 
         entry = scores_map.get(tech.id, {})
+        score = entry.get("total_score", 0)
         technique_rows.append({
             "technique_id": tech.id,
             "mitre_id": tech.mitre_id,
             "status": status_value,
-            "score": entry.get("total_score", 0),
+            "score": score,
         })
 
+        by_status[status_value] += 1
+        tactic_key = tech.tactic or "unknown"
+        bucket = by_tactic[tactic_key]
+        bucket["total"] += 1
+        bucket["score_sum"] += score
+        if status_value == "validated":
+            bucket["validated"] += 1
+        elif status_value == "partial":
+            bucket["partial"] += 1
+
+        if status_value == "not_evaluated":
+            never_tested_count += 1
+        if tech.review_required:
+            stale_count += 1
+
     org_data = calculate_organization_score(db)
     org_score = org_data.get("overall_score", 0)
+    total_techniques = len(techniques) or 1
+    coverage_pct = round((validated_count / total_techniques) * 100, 1)
+
+    by_tactic_out = {
+        tactic: {
+            "total": data["total"],
+            "validated": data["validated"],
+            "partial": data["partial"],
+            "average_score": round(data["score_sum"] / data["total"], 1) if data["total"] else 0,
+        }
+        for tactic, data in by_tactic.items()
+    }
 
     snapshot = CoverageSnapshot(
         name=name,
@@ -189,6 +230,11 @@ def create_snapshot(
         not_covered_count=not_covered_count,
         in_progress_count=in_progress_count,
         not_evaluated_count=not_evaluated_count,
+        coverage_percentage=coverage_pct,
+        by_tactic=by_tactic_out,
+        by_status=dict(by_status),
+        stale_count=stale_count,
+        never_tested_count=never_tested_count,
         created_by=user_id,
     )
     db.add(snapshot)
@@ -320,6 +366,37 @@ def compare_snapshots(
     }
 
 
+# ---------------------------------------------------------------------------
+# Coverage evolution (trends)
+# ---------------------------------------------------------------------------
+
+
+def get_coverage_evolution(db: Session, *, months: int = 12) -> list[dict]:
+    """Return snapshot trend points for the last *months* months."""
+    cutoff = datetime.now(timezone.utc) - timedelta(days=months * 30)
+    snapshots = (
+        db.query(CoverageSnapshot)
+        .filter(CoverageSnapshot.created_at >= cutoff)
+        .order_by(CoverageSnapshot.created_at.asc())
+        .all()
+    )
+    return [
+        {
+            "date": snap.created_at.isoformat() if snap.created_at else None,
+            "name": snap.name,
+            "org_score": snap.organization_score,
+            "coverage_pct": getattr(snap, "coverage_percentage", 0.0),
+            "by_tactic": getattr(snap, "by_tactic", None) or {},
+            "by_status": getattr(snap, "by_status", None) or {},
+            "stale_count": getattr(snap, "stale_count", 0),
+            "never_tested_count": getattr(snap, "never_tested_count", 0),
+            "validated_count": snap.validated_count,
+            "total_techniques": snap.total_techniques,
+        }
+        for snap in snapshots
+    ]
+
+
 # ---------------------------------------------------------------------------
 # Cleanup
 # ---------------------------------------------------------------------------

backend/tests/test_phase5_snapshots.py

@@ -0,0 +1,102 @@
+"""Tests for Phase 5 snapshot evolution and breakdown fields."""
+
+from datetime import datetime, timedelta, timezone
+
+from app.models.coverage_snapshot import CoverageSnapshot
+from app.models.enums import TechniqueStatus
+from app.models.technique import Technique
+from app.services.snapshot_service import create_snapshot, get_coverage_evolution
+
+
+def test_create_snapshot_includes_tactic_breakdown(db, admin_user):
+    tech = Technique(
+        mitre_id="T1059",
+        name="Command and Scripting Interpreter",
+        tactic="execution",
+        status_global=TechniqueStatus.validated,
+    )
+    db.add(tech)
+    db.commit()
+
+    snap = create_snapshot(db, name="Phase5 test", user_id=admin_user.id)
+
+    assert snap.by_tactic
+    assert "execution" in snap.by_tactic
+    assert snap.by_status
+    assert snap.coverage_percentage >= 0
+    assert snap.never_tested_count >= 0
+
+
+def test_coverage_evolution_filters_by_months(db, admin_user):
+    now = datetime.now(timezone.utc)
+    old = CoverageSnapshot(
+        name="old",
+        organization_score=50.0,
+        total_techniques=10,
+        validated_count=5,
+        partial_count=1,
+        not_covered_count=1,
+        in_progress_count=1,
+        not_evaluated_count=2,
+        coverage_percentage=50.0,
+        by_tactic={"execution": {"total": 10, "validated": 5}},
+        by_status={"validated": 5},
+        stale_count=0,
+        never_tested_count=2,
+        created_by=admin_user.id,
+    )
+    old.created_at = now - timedelta(days=400)
+    recent = CoverageSnapshot(
+        name="recent",
+        organization_score=70.0,
+        total_techniques=10,
+        validated_count=7,
+        partial_count=1,
+        not_covered_count=0,
+        in_progress_count=1,
+        not_evaluated_count=1,
+        coverage_percentage=70.0,
+        by_tactic={"execution": {"total": 10, "validated": 7}},
+        by_status={"validated": 7},
+        stale_count=1,
+        never_tested_count=1,
+        created_by=admin_user.id,
+    )
+    db.add_all([old, recent])
+    db.commit()
+
+    evolution = get_coverage_evolution(db, months=6)
+    assert len(evolution) == 1
+    assert evolution[0]["org_score"] == 70.0
+    assert evolution[0]["coverage_pct"] == 70.0
+    assert evolution[0]["stale_count"] == 1
+
+
+def test_evolution_endpoint(client, db, admin_user, admin_token):
+    snap = CoverageSnapshot(
+        name="api-evolution",
+        organization_score=60.0,
+        total_techniques=5,
+        validated_count=3,
+        partial_count=0,
+        not_covered_count=0,
+        in_progress_count=0,
+        not_evaluated_count=2,
+        coverage_percentage=60.0,
+        by_tactic={},
+        by_status={"validated": 3},
+        stale_count=0,
+        never_tested_count=2,
+    )
+    db.add(snap)
+    db.commit()
+
+    response = client.get(
+        "/api/v1/snapshots/evolution?months=12",
+        headers={"Authorization": f"Bearer {admin_token}"},
+    )
+    assert response.status_code == 200
+    data = response.json()
+    assert isinstance(data, list)
+    assert len(data) >= 1
+    assert "org_score" in data[0]

backend/tests/test_scoring_and_compliance.py

@@ -18,7 +18,10 @@ from app.models.defensive_technique import DefensiveTechnique, DefensiveTechniqu
 from app.models.compliance import ComplianceFramework, ComplianceControl, ComplianceControlMapping
 from app.models.audit import AuditLog
 from app.models.enums import TestState, TestResult, TechniqueStatus
+from app.models.scoring_config import ScoringConfig
+from app.services.scoring_config_service import get_scoring_weights, update_scoring_weights
 from app.services.scoring_service import (
+    _recency_factor,
     calculate_technique_score,
     calculate_tactic_score,
     calculate_organization_score,
@@ -175,9 +178,11 @@ class TestScoring:
         assert result["breakdown"]["tests_validated"]["score"] > 0
 
     def test_technique_score_no_tests(self, db, sample_technique_no_tests):
-        """Técnica sin tests → score 0."""
+        """Técnica sin tests → solo puede puntuar severidad por defecto."""
         result = calculate_technique_score(sample_technique_no_tests, db)
-        assert result["total_score"] == 0
+        assert result["breakdown"]["tests_validated"]["score"] == 0
+        assert result["breakdown"]["recency"]["score"] == 0
+        assert result["total_score"] == result["breakdown"]["severity"]["score"]
 
     def test_technique_score_partial_detection(self, db, sample_technique, validated_tests):
         """Técnica con detección parcial → score intermedio."""
@@ -187,8 +192,8 @@ class TestScoring:
         breakdown = result["breakdown"]
         assert "2/3" in breakdown["tests_validated"]["detail"]
 
-    def test_technique_score_freshness_penalty(self, db, sample_technique, admin_user):
+    def test_technique_score_recency_penalty(self, db, sample_technique, admin_user):
-        """Tests > 180 días → penalización en freshness."""
+        """Tests > 180 días → factor de recencia reducido."""
         old_date = datetime.utcnow() - timedelta(days=200)
         test = Test(
             technique_id=sample_technique.id,
@@ -198,14 +203,53 @@ class TestScoring:
             created_by=admin_user.id,
             platform="windows",
             red_validated_at=old_date,
+            blue_validated_at=old_date,
         )
         db.add(test)
         db.commit()
 
         result = calculate_technique_score(sample_technique, db)
-        # Freshness should be 0 for tests > 180 days old
+        assert result["breakdown"]["recency"]["score"] == 5.0  # 0.5 * 10 (181–365 días)
-        assert result["breakdown"]["freshness"]["score"] == 0
+        assert "200" in result["breakdown"]["recency"]["detail"]
-        assert "200" in result["breakdown"]["freshness"]["detail"]
+
+    def test_recency_recent_scores_higher_than_old(self, db, sample_technique, admin_user):
+        """Mismo resultado de detección: test reciente puntúa más que uno de hace 1 año."""
+        now = datetime.utcnow()
+        for days_ago in (1, 400):
+            db.add(
+                Test(
+                    technique_id=sample_technique.id,
+                    name=f"Recency {days_ago}",
+                    state=TestState.validated,
+                    detection_result=TestResult.detected,
+                    created_by=admin_user.id,
+                    platform="windows",
+                    red_validated_at=now - timedelta(days=days_ago),
+                    blue_validated_at=now - timedelta(days=days_ago),
+                )
+            )
+        db.commit()
+
+        result = calculate_technique_score(sample_technique, db)
+        assert _recency_factor(now - timedelta(days=1)) == 1.0
+        assert _recency_factor(now - timedelta(days=400)) == 0.2
+        assert result["breakdown"]["recency"]["score"] == 10.0
+
+    def test_scoring_weights_persist_in_database(self, db, sample_technique, validated_tests):
+        """Cambiar pesos en BD se refleja en el breakdown."""
+        update_scoring_weights(db, tests=50, detection_rules=20, d3fend=10, recency=10, severity=10)
+        db.commit()
+
+        score = calculate_technique_score(sample_technique, db)
+        assert score["breakdown"]["tests_validated"]["max"] == 50
+
+        row = db.query(ScoringConfig).first()
+        assert row is not None
+        assert row.weight_tests == 50
+
+        update_scoring_weights(db, tests=40, detection_rules=25, d3fend=15, recency=10, severity=10)
+        db.commit()
+        assert get_scoring_weights(db).tests == 40
 
     def test_scoring_weights_configurable(self, db, sample_technique, validated_tests):
         """Scoring weights are reflected in the breakdown max values."""

backend/tests/test_value_objects.py

@@ -84,13 +84,13 @@ class TestScoringWeights:
         assert w.tests == 40.0
         assert w.detection_rules == 25.0
         assert w.d3fend == 15.0
-        assert w.freshness == 10.0
+        assert w.recency == 10.0
-        assert w.platform_diversity == 10.0
+        assert w.severity == 10.0
 
     def test_valid_custom(self):
         w = ScoringWeights(
             tests=50, detection_rules=20, d3fend=10,
-            freshness=10, platform_diversity=10,
+            recency=10, severity=10,
         )
         assert w.tests == 50
 
@@ -98,14 +98,14 @@ class TestScoringWeights:
         with pytest.raises(ValueError, match="sum to 100"):
             ScoringWeights(
                 tests=50, detection_rules=20, d3fend=10,
-                freshness=10, platform_diversity=5,
+                recency=10, severity=5,
             )
 
     def test_invalid_negative_weight(self):
         with pytest.raises(ValueError, match="non-negative"):
             ScoringWeights(
                 tests=-10, detection_rules=40, d3fend=30,
-                freshness=20, platform_diversity=20,
+                recency=20, severity=20,
             )
 
     def test_immutable(self):