fix: Additional validations for OpenAI frontend LoRA paths

python/openai/openai_frontend/engine/utils/triton.py

@@ -617,6 +617,34 @@ def _get_guided_json_from_tool(
     return None
 
 
+def _validate_lora_path_trtllm(repo_path: str, lora_path: str, lora_name: str):
+    if os.path.isabs(lora_path):
+        raise ValueError(
+            f"LoRA path '{lora_path}' for '{lora_name}' must be a relative path inside its model repository"
+        )
+
+    # NOTE: Error messages should never contain the real/absolute paths.
+    realpath_repo = os.path.realpath(repo_path)
+    realpath_lora = os.path.realpath(os.path.join(realpath_repo, lora_path))
+    # Always check if the LoRA path is inside the model repository before checking its existence.
+    if os.path.commonpath([realpath_repo, realpath_lora]) != realpath_repo:
+        raise ValueError(
+            f"LoRA path '{lora_path}' for '{lora_name}' must be inside its model repository"
+        )
+    if not os.path.exists(realpath_lora):
+        raise ServerError(
+            f"LoRA directory '{lora_path}' not found for '{lora_name}' in its model repository"
+        )
+
+    # Check if the files exist
+    for lora_file in ["model.lora_weights.npy", "model.lora_config.npy"]:
+        lora_file_path = os.path.join(realpath_lora, lora_file)
+        if not os.path.exists(lora_file_path):
+            raise ServerError(
+                f"LoRA file '{lora_file}' not found for '{lora_name}' at path: {lora_file_path}"
+            )
+
+
 def _parse_lora_configs(
     model_repository: str | list[str], model_name: str, model_version: int, backend: str
 ) -> None | List[tuple[str, str]]:
@@ -683,25 +711,10 @@ def _parse_lora_configs(
             with open(lora_config_path, "r") as f:
                 lora_config = json.load(f)
                 for lora_name, lora_path in lora_config.items():
-                    print(f"backend: {backend}")
                     if backend == "vllm":
                         lora_configs.append(TritonLoraConfig(name=lora_name))
                     else:
-                        lora_weights_path = os.path.join(
-                            lora_path, "model.lora_weights.npy"
-                        )
-                        lora_config_path = os.path.join(
-                            lora_path, "model.lora_config.npy"
-                        )
-                        if not os.path.exists(lora_weights_path):
-                            raise ServerError(
-                                f"LoRA weights file not found for '{lora_name}' at path: {lora_weights_path}"
-                            )
-                        if not os.path.exists(lora_config_path):
-                            raise ServerError(
-                                f"LoRA config file not found for '{lora_name}' at path: {lora_config_path}"
-                            )
-
+                        _validate_lora_path_trtllm(repo_path, lora_path, lora_name)
                         lora_configs.append(
                             TritonLoraConfig(
                                 name=lora_name, path=lora_path, task_id=lora_task_id

python/openai/tests/test_lora.py

@@ -1,4 +1,4 @@
-# Copyright 2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# Copyright 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # Redistribution and use in source and binary forms, with or without
 # modification, are permitted provided that the following conditions
@@ -35,10 +35,22 @@
 from openai_frontend.engine.utils.triton import (
     _parse_lora_configs as parse_lora_configs,
 )
+from openai_frontend.engine.utils.triton import (
+    _validate_lora_path_trtllm as validate_lora_path_trtllm,
+)
 
 from .utils import OpenAIServer
 
 
+def is_vllm_installed():
+    try:
+        import vllm as _
+
+        return True
+    except ImportError:
+        return False
+
+
 @pytest.mark.parametrize(
     "model_repository,model_name,expect_error",
     [
@@ -74,13 +86,62 @@ def test_parse_lora_configs(model_repository: str, model_name: str, expect_error
             )
 
 
-def is_vllm_installed():
+@pytest.mark.skipif(
+    is_vllm_installed(),
+    reason="VLLM backend does not validate LoRA paths",
+)
+@pytest.mark.parametrize(
+    "lora_path,expect_error,error_message",
+    [
+        # Valid relative path inside repo (requires .npy files to exist at runtime).
+        ("tensorrt_llm_bls/1/luotuo-lora-7b-0.1-weights", False, None),
+        ("tensorrt_llm_bls/1/Japanese-Alpaca-LoRA-7b-v0-weights", False, None),
+        # Absolute path not allowed.
+        (
+            os.path.join(
+                os.path.abspath(os.curdir),
+                "tests/tensorrtllm_models",
+                "tensorrt_llm_bls/1/luotuo-lora-7b-0.1-weights",
+            ),
+            True,
+            f"must be a relative path inside its model repository",
+        ),
+        ("/etc/passwd", True, "must be a relative path inside its model repository"),
+        # Path outside repo (traversal).
+        ("tensorrt_llm_bls/1//../1/luotuo-lora-7b-0.1-weights", False, None),
+        ("../outside/lora", True, "must be inside its model repository"),
+        ("subdir/../../etc/passwd", True, "must be inside its model repository"),
+        # LoRA directory not found.
+        ("tensorrt_llm_bls/10", True, "LoRA directory 'tensorrt_llm_bls/10' not found"),
+        (
+            "tensorrt_llm_bls/1/non_exist",
+            True,
+            "LoRA directory 'tensorrt_llm_bls/1/non_exist' not found",
+        ),
+        # LoRA file not found.
+        ("tensorrt_llm_bls/1", True, "LoRA file 'model.lora_weights.npy' not found"),
+    ],
+)
+def test_validate_lora_path_trtllm(
+    lora_path: str,
+    expect_error: bool,
+    error_message: str,
+):
+    lora_name = ""
+    repo_path = "tests/tensorrtllm_models"
     try:
-        import vllm as _
-
-        return True
-    except ImportError:
-        return False
+        validate_lora_path_trtllm(repo_path, lora_path, lora_name)
+    except Exception as e:
+        if not expect_error:
+            raise pytest.fail(
+                f"repo_path='{repo_path}' raised exception unexpectedly: {e}"
+            )
+        assert error_message in str(e)
+    else:
+        if expect_error:
+            raise pytest.fail(
+                f"lora_path='{repo_path}' did not raise exception as expected."
+            )
 
 
 class LoRATest(unittest.TestCase):