diff --git a/tensorrt_llm/auto_parallel/parallelization.py b/tensorrt_llm/auto_parallel/parallelization.py
index d25d273d112..0e0e0d78c3f 100644
--- a/tensorrt_llm/auto_parallel/parallelization.py
+++ b/tensorrt_llm/auto_parallel/parallelization.py
@@ -1,7 +1,6 @@
 import contextlib
 import copy
 import itertools
-import pickle  # nosec B403
 import re
 from abc import ABC, abstractmethod
 from dataclasses import dataclass, field
@@ -12,6 +11,7 @@
 import torch
 from filelock import FileLock
 
+from tensorrt_llm import serialization
 from tensorrt_llm._utils import (str_dtype_to_trt, trt_dtype_to_np,
                                  trt_dtype_to_torch)
 from tensorrt_llm.functional import AllReduceParams, create_allreduce_plugin
@@ -39,6 +39,13 @@
 
 default_int_dtype = trt.int64
 
+# These dataclasses are used in ParallelConfig serialization. If there are other classes need to be serialized, please add to this list.
+BASE_AUTOPP_CLASSES = {
+    "tensorrt_llm.auto_parallel.parallelization": ["ParallelConfig"],
+    "tensorrt_llm.auto_parallel.config": ["AutoParallelConfig", "CostModel"],
+    "tensorrt_llm.auto_parallel.simplifier": ["GraphConfig", "StageType"]
+}
+
 
 @dataclass
 class ParallelConfig:
@@ -55,12 +62,13 @@ class ParallelConfig:
 
     def save(self, filename):
         with open(filename, 'wb') as file:
-            pickle.dump(self, file)
+            serialization.dump(self, file)
 
     @staticmethod
     def from_file(filename) -> "ParallelConfig":
         with open(filename, "rb") as file:
-            return pickle.load(file)  # nosec B301
+            return serialization.load(file,
+                                      approved_imports=BASE_AUTOPP_CLASSES)
 
     def print_graph_strategy(self, file=None):
         for index, (node_name,
diff --git a/tensorrt_llm/executor/serialization.py b/tensorrt_llm/serialization.py
similarity index 100%
rename from tensorrt_llm/executor/serialization.py
rename to tensorrt_llm/serialization.py
diff --git a/tests/unittest/llmapi/test_serialization.py b/tests/unittest/llmapi/test_serialization.py
index e2bf6ed2df6..02caa0c72cc 100644
--- a/tests/unittest/llmapi/test_serialization.py
+++ b/tests/unittest/llmapi/test_serialization.py
@@ -1,6 +1,12 @@
+import os
+import tempfile
+
 import torch
 
-import tensorrt_llm.executor.serialization as serialization
+from tensorrt_llm import serialization
+from tensorrt_llm.auto_parallel.config import AutoParallelConfig
+from tensorrt_llm.auto_parallel.parallelization import ParallelConfig
+from tensorrt_llm.auto_parallel.simplifier import GraphConfig, StageType
 
 
 class TestClass:
@@ -77,5 +83,38 @@ def test_serialization_complex_object_disallowed_class():
         excep) == "Import torch._utils | _rebuild_tensor_v2 is not allowed"
 
 
+def test_parallel_config_serialization():
+    with tempfile.TemporaryDirectory() as tmpdir:
+        # Create a ParallelConfig instance with some test data
+        config = ParallelConfig()
+        config.version = "test_version"
+        config.network_hash = "test_hash"
+        config.auto_parallel_config = AutoParallelConfig(
+            world_size=2, gpus_per_node=2, cluster_key="test_cluster")
+        config.graph_config = GraphConfig(num_micro_batches=2,
+                                          num_blocks=3,
+                                          num_stages=2)
+        config.cost = 1.5
+        config.stage_type = StageType.START
+
+        config_path = os.path.join(tmpdir, "parallel_config.pkl")
+        config.save(config_path)
+
+        loaded_config = ParallelConfig.from_file(config_path)
+
+        # Verify the loaded config matches the original
+        assert loaded_config.version == config.version
+        assert loaded_config.network_hash == config.network_hash
+        assert loaded_config.auto_parallel_config.world_size == config.auto_parallel_config.world_size
+        assert loaded_config.auto_parallel_config.gpus_per_node == config.auto_parallel_config.gpus_per_node
+        assert loaded_config.auto_parallel_config.cluster_key == config.auto_parallel_config.cluster_key
+        assert loaded_config.graph_config.num_micro_batches == config.graph_config.num_micro_batches
+        assert loaded_config.graph_config.num_blocks == config.graph_config.num_blocks
+        assert loaded_config.graph_config.num_stages == config.graph_config.num_stages
+        assert loaded_config.cost == config.cost
+        assert loaded_config.stage_type == config.stage_type
+
+
 if __name__ == "__main__":
     test_serialization_allowed_class()
+    test_parallel_config_serialization()