diff --git a/flares.py b/flares.py
index 9a365fa..0f06a99 100644
--- a/flares.py
+++ b/flares.py
@@ -6851,7 +6851,9 @@ def sparks_csv_export(
     haemo_obj: BaseRaw,
     save_path: str,
 ) -> None:
-
+    """Export sparks data to CSV with SHA256 checksum verification (Issue #106)."""
+    import hashlib
+    
     raw = haemo_obj
     data, times = raw.get_data(return_times=True)
     ann_col = np.full(times.shape, "", dtype=object)
@@ -6868,7 +6870,26 @@ def sparks_csv_export(
     df = pd.DataFrame(data.T, columns=raw.ch_names)
     df.insert(0, "annotation", ann_col)
     df.insert(0, "time", times)
-    df.to_csv(save_path, index=False)
+    
+    # Write CSV to temporary file first
+    temp_path = save_path + ".tmp"
+    df.to_csv(temp_path, index=False)
+    
+    # Calculate SHA256 checksum of the data file
+    sha256_hash = hashlib.sha256()
+    with open(temp_path, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            sha256_hash.update(chunk)
+    checksum_hex = sha256_hash.hexdigest()
+    
+    # Append checksum to end of file
+    with open(temp_path, "a") as f:
+        f.write(f"\n# SHA256: {checksum_hex}")
+    
+    # Atomic rename
+    import os
+    os.rename(temp_path, save_path)
+    print(f"Saved {save_path} with checksum: {checksum_hex[:16]}...")
 
 
 def peak_power_fast(
@@ -7166,8 +7187,24 @@ def write_qc_excel_summary(
     for i in range(n_participants):
         ws.column_dimensions[get_column_letter(i + 2)].width = 14
     ws.freeze_panes = "B2"
-
-    wb.save(output_path)
+    
+    # Save to temporary file first (Issue #106: checksum verification)
+    import hashlib
+    import os
+    
+    temp_path = output_path + ".tmp"
+    wb.save(temp_path)
+    
+    # Calculate SHA256 checksum
+    sha256_hash = hashlib.sha256()
+    with open(temp_path, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            sha256_hash.update(chunk)
+    checksum_hex = sha256_hash.hexdigest()
+    
+    # Atomic rename
+    os.rename(temp_path, output_path)
+    print(f"Saved {output_path} with checksum: {checksum_hex[:16]}...")
 
 
 def plot_and_enqueue_waveform_metrics(