diff --git a/pyrit/models/data_type_serializer.py b/pyrit/models/data_type_serializer.py
index 578efca5cc..a5de83dbba 100644
--- a/pyrit/models/data_type_serializer.py
+++ b/pyrit/models/data_type_serializer.py
@@ -7,6 +7,7 @@
 import base64
 import hashlib
 import os
+import tempfile
 import time
 import wave
 from mimetypes import guess_type
@@ -194,19 +195,24 @@ async def save_formatted_audio(
 
         # save audio file locally first if in AzureStorageBlob so we can use wave.open to set audio parameters
         if self._is_azure_storage_url(str(file_path)):
-            local_temp_path = Path(DB_DATA_PATH, "temp_audio.wav")
-            with wave.open(str(local_temp_path), "wb") as wav_file:
-                wav_file.setnchannels(num_channels)
-                wav_file.setsampwidth(sample_width)
-                wav_file.setframerate(sample_rate)
-                wav_file.writeframes(data)
-
-            async with aiofiles.open(local_temp_path, "rb") as f:
-                audio_data = await f.read()
+            with tempfile.NamedTemporaryFile(
+                suffix=".wav", dir=DB_DATA_PATH, delete=False
+            ) as tmp:
+                local_temp_path = Path(tmp.name)
+
+            try:
+                with wave.open(str(local_temp_path), "wb") as wav_file:
+                    wav_file.setnchannels(num_channels)
+                    wav_file.setsampwidth(sample_width)
+                    wav_file.setframerate(sample_rate)
+                    wav_file.writeframes(data)
+                async with aiofiles.open(local_temp_path, "rb") as f:
+                    audio_data = await f.read()
                 if self._memory.results_storage_io is None:
                     raise RuntimeError("self._memory.results_storage_io is not initialized")
                 await self._memory.results_storage_io.write_file(file_path, audio_data)
-            os.remove(local_temp_path)
+            finally:
+                local_temp_path.unlink(missing_ok=True)
 
         # If local, we can just save straight to disk and do not need to delete temp file after
         else:
diff --git a/tests/unit/models/test_data_type_serializer.py b/tests/unit/models/test_data_type_serializer.py
index d710afd830..e59dc173e3 100644
--- a/tests/unit/models/test_data_type_serializer.py
+++ b/tests/unit/models/test_data_type_serializer.py
@@ -10,6 +10,8 @@
 
 import pytest
 from PIL import Image
+import glob
+from pyrit.common.path import DB_DATA_PATH
 
 from pyrit.models import (
     AllowedCategories,
@@ -426,3 +428,29 @@ async def test_get_data_filename_uses_db_data_path_when_results_path_falsy():
     result_str = str(result).replace("\\", "/")
     assert "/fallback/db_data" in result_str
     assert result_str.endswith(".png")
+
+
+@pytest.mark.asyncio
+async def test_save_formatted_audio_cleans_up_temp_file_on_azure_upload_failure(patch_central_database):
+    """Regression test: temp file must be deleted even when Azure upload fails."""
+    serializer = data_serializer_factory(category="prompt-memory-entries", data_type="audio_path")
+
+    mock_memory = MagicMock()
+    mock_storage_io = AsyncMock()
+    mock_storage_io.write_file.side_effect = RuntimeError("Azure upload failed")
+    mock_memory.results_storage_io = mock_storage_io
+
+    azure_url = "https://account.blob.core.windows.net/container/audio/test.wav"
+
+    # Record existing wav files BEFORE test runs
+    existing_wav_files = set(glob.glob(str(DB_DATA_PATH / "*.wav")))
+
+    with patch.object(type(serializer), "_memory", new_callable=PropertyMock, return_value=mock_memory):
+        with patch.object(serializer, "get_data_filename", new_callable=AsyncMock, return_value=azure_url):
+            with pytest.raises(RuntimeError, match="Azure upload failed"):
+                await serializer.save_formatted_audio(data=b"\x00\x01\x02")
+
+    # Check no NEW wav files leaked after test
+    leaked_files = set(glob.glob(str(DB_DATA_PATH / "*.wav"))) - existing_wav_files
+    assert len(leaked_files) == 0, f"Temp files leaked: {leaked_files}"
+