Check feature indexes in forced split file (fixes #5517)

src/boosting/gbdt.cpp

@@ -14,6 +14,7 @@
 
 #include <chrono>
 #include <ctime>
+#include <queue>
 #include <sstream>
 
 namespace LightGBM {
@@ -138,6 +139,9 @@ void GBDT::Init(const Config* config, const Dataset* train_data, const Objective
   // get parser config file content
   parser_config_str_ = train_data_->parser_config_str();
 
+  // check that forced splits does not use feature indices larger than dataset size
+  CheckForcedSplitFeatures();
+
   // if need bagging, create buffer
   data_sample_strategy_->ResetSampleConfig(config_.get(), true);
   ResetGradientBuffers();
@@ -155,6 +159,26 @@ void GBDT::Init(const Config* config, const Dataset* train_data, const Objective
   }
 }
 
+void GBDT::CheckForcedSplitFeatures() {
+  std::queue<Json> forced_split_nodes;
+  forced_split_nodes.push(forced_splits_json_);
+  while (!forced_split_nodes.empty()) {
+    Json node = forced_split_nodes.front();
+    forced_split_nodes.pop();
+    const int feature_index = node["feature"].int_value();
+    if (feature_index > max_feature_idx_) {
+      Log::Fatal("Forced splits file includes feature index %d, but maximum feature index in dataset is %d",
+        feature_index, max_feature_idx_);
+    }
+    if (node.object_items().count("left") > 0) {
+      forced_split_nodes.push(node["left"]);
+    }
+    if (node.object_items().count("right") > 0) {
+      forced_split_nodes.push(node["right"]);
+    }
+  }
+}
+
 void GBDT::AddValidDataset(const Dataset* valid_data,
                            const std::vector<const Metric*>& valid_metrics) {
   if (!train_data_->CheckAlign(*valid_data)) {

src/boosting/gbdt.h

@@ -58,6 +58,11 @@ class GBDT : public GBDTBase {
             const ObjectiveFunction* objective_function,
             const std::vector<const Metric*>& training_metrics) override;
 
+  /*!
+  * \brief Traverse the tree of forced splits and check that all indices  are less than the number of features.
+  */
+  void CheckForcedSplitFeatures();
+
   /*!
   * \brief Merge model from other boosting object. Will insert to the front of current boosting object
   * \param other

tests/python_package_test/test_engine.py

@@ -2887,6 +2887,25 @@ def test_node_level_subcol():
     assert ret != ret2
 
 
+def test_forced_split_feature_indices(tmp_path):
+    X, y = make_synthetic_regression()
+    forced_split = {
+        "feature": 0,
+        "threshold": 0.5,
+        "left": {"feature": X.shape[1], "threshold": 0.5},
+    }
+    tmp_split_file = tmp_path / "forced_split.json"
+    with open(tmp_split_file, "w") as f:
+        f.write(json.dumps(forced_split))
+    lgb_train = lgb.Dataset(X, y)
+    params = {
+        "objective": "regression",
+        "forcedsplits_filename": tmp_split_file
+    }
+    with pytest.raises(lgb.basic.LightGBMError, match="Forced splits file includes feature index"):
+        bst = lgb.train(params, lgb_train)
+
+
 def test_forced_bins():
     x = np.empty((100, 2))
     x[:, 0] = np.arange(0, 1, 0.01)