fix(artifact): enforce risk data lineage

docs/handoff/2026-08-21-research-artifact-contract.md

@@ -45,6 +45,8 @@
 - `prepare_asset_return_snapshot` 从规范化长表行情生成不前向填充的 simple daily returns；
   显式 ingestion snapshot ID、源/字段/复权口径、价格值和缺失掩码共同形成
   `asset-returns-v1:<sha256>`，并把同一 ID 传给 covariance 与 run artifact。
+- artifact builder fail closed：每个 `CovarianceSnapshot.data_snapshot_id` 必须与 run 级
+  `data_snapshot_id` 完全一致，禁止把其他行情快照的风险分解静默发布到当前研究运行。
 - shrinkage 适配器本轮不实现：scikit-learn 尚非声明依赖，未来只允许薄适配
   `LedoitWolf` / `OAS`，不复制公式、不依赖环境偶然安装状态。
 

src/quant_engine/artifact.py

@@ -390,6 +390,7 @@ def _risk_trade_date(value: object) -> date:
 def _build_risk(
     result: FactorBacktestResult,
     run_id: str,
+    data_snapshot_id: str,
     risk_snapshots: Mapping[object, CovarianceSnapshot] | None,
 ) -> pd.DataFrame:
     if risk_snapshots is None:
@@ -414,6 +415,8 @@ def _build_risk(
                 f"covariance as_of_date {snapshot.as_of_date} must not be after trade date "
                 f"{trade_date}"
             )
+        if snapshot.data_snapshot_id != data_snapshot_id:
+            raise ValueError("covariance snapshot data lineage differs from research run")
         normalized[trade_date] = snapshot
 
     weights_by_date = result.position_weights
@@ -572,6 +575,6 @@ def build_research_run_artifact(
         _positions=_build_positions(result, normalized_run_id),
         _attribution=attribution,
         _attribution_daily=attribution_daily,
-        _risk=_build_risk(result, normalized_run_id, risk_snapshots),
+        _risk=_build_risk(result, normalized_run_id, normalized_snapshot, risk_snapshots),
         _performance=_build_performance(result, normalized_run_id, benchmark_returns),
     )

tests/test_artifact.py

@@ -164,6 +164,7 @@ def test_research_artifact_projects_annualized_risk_from_actual_positions() -> N
         covariance=covariance,
         return_frequency="1d",
         periods_per_year=252,
+        data_snapshot_id="qtdb-pro-20260108-v1",
     )
 
     artifact = _build(result, risk_snapshots={trade_date: snapshot})
@@ -182,6 +183,31 @@ def test_research_artifact_projects_annualized_risk_from_actual_positions() -> N
     assert risk["risk_contribution"].sum() == pytest.approx(1.0)
 
 
+def test_research_artifact_rejects_risk_from_a_different_data_snapshot() -> None:
+    result = _backtest_result()
+    trade_date = result.position_weights.index[-1].date()
+    covariance = pd.DataFrame(
+        [[0.0001, 0.0], [0.0, 0.0004]],
+        index=["A", "B"],
+        columns=["A", "B"],
+    )
+
+    with pytest.raises(ValueError, match="data lineage differs"):
+        _build(
+            result,
+            risk_snapshots={
+                trade_date: CovarianceSnapshot(
+                    snapshot_id="foreign-covariance",
+                    as_of_date="2026-01-07",
+                    covariance=covariance,
+                    return_frequency="1d",
+                    periods_per_year=252,
+                    data_snapshot_id="different-market-snapshot",
+                )
+            },
+        )
+
+
 def test_research_artifact_rejects_future_or_misaligned_risk_snapshots() -> None:
     result = _backtest_result()
     trade_date = result.position_weights.index[-1].date()
@@ -201,6 +227,7 @@ def test_research_artifact_rejects_future_or_misaligned_risk_snapshots() -> None
                     covariance=covariance,
                     return_frequency="1d",
                     periods_per_year=252,
+                    data_snapshot_id="qtdb-pro-20260108-v1",
                 )
             },
         )
@@ -215,6 +242,7 @@ def test_research_artifact_rejects_future_or_misaligned_risk_snapshots() -> None
                     covariance=covariance.loc[["B"], ["B"]],
                     return_frequency="1d",
                     periods_per_year=252,
+                    data_snapshot_id="qtdb-pro-20260108-v1",
                 )
             },
         )