diff --git a/intel_extension_for_transformers/neural_chat/models/base_model.py b/intel_extension_for_transformers/neural_chat/models/base_model.py
index 1aa31ef1782..5f3616f89ff 100644
--- a/intel_extension_for_transformers/neural_chat/models/base_model.py
+++ b/intel_extension_for_transformers/neural_chat/models/base_model.py
@@ -58,6 +58,16 @@ def construct_parameters(query, model_name, device, assistant_model, config):
     params["device"] = device
     return params
 
+def safe_path(*paths):
+    # Prevent path traversal by ensuring the final path is within the base path or assets_path
+    current_working_directory = os.getcwd()
+    path_parts = current_working_directory.split('/')
+    base_path = '/' + path_parts[1]
+    assets_path = '/intel-extension-for-transformers/intel_extension_for_transformers/neural_chat/assets/'
+    final_path = os.path.abspath(*paths)
+    if final_path.startswith(base_path) or final_path.startswith(assets_path):
+        return final_path
+
 class BaseModel(ABC):
     """A base class for LLM."""
 
@@ -158,7 +168,7 @@ def predict_stream(self, query, origin_query="", config=None):
         my_origin_query = origin_query
 
         if is_audio_file(query):
-            if not os.path.exists(query):
+            if not os.path.exists(safe_path(query)):
                 raise ValueError(f"The audio file path {query} is invalid.")
 
         query_include_prompt = False
@@ -181,7 +191,7 @@ def predict_stream(self, query, origin_query="", config=None):
                             if response:
                                 logging.info("Get response: %s from cache", response)
                                 return response['choices'][0]['text'], link
-                        if plugin_name == "asr" and not os.path.exists(query):
+                        if plugin_name == "asr" and not os.path.exists(safe_path(query)):
                             continue
                         if plugin_name == "retrieval":
                             try:
@@ -281,7 +291,7 @@ def predict(self, query, origin_query="", config=None):
         config.ipex_int8 = self.ipex_int8
 
         if is_audio_file(query):
-            if not os.path.exists(query):
+            if not os.path.exists(safe_path(query)):
                 raise ValueError(f"The audio file path {query} is invalid.")
 
         query_include_prompt = False
@@ -302,7 +312,7 @@ def predict(self, query, origin_query="", config=None):
                             if response:
                                 logging.info("Get response: %s from cache", response)
                                 return response['choices'][0]['text']
-                        if plugin_name == "asr" and not os.path.exists(query):
+                        if plugin_name == "asr" and not os.path.exists(safe_path(query)):
                             continue
                         if plugin_name == "retrieval":
                             try: