diff --git a/deepface/modules/detection.py b/deepface/modules/detection.py
index c31a026..934216f 100644
--- a/deepface/modules/detection.py
+++ b/deepface/modules/detection.py
@@ -80,6 +80,30 @@ def extract_faces(
             just available in the result only if anti_spoofing is set to True in input arguments.
     """
 
+    def is_valid_landmark(coord, width, height):
+        """
+        Check if a landmark coordinate is within valid image bounds
+
+        Args: 
+            coord: (x, y) tuple or None; width; height: image dimensions
+            Returns True if coord is a valid (x, y) inside the image, else False
+
+        Returns: 
+            bool: True if coordinate is valid and within bounds, False otherwise
+        """
+        if coord is None:
+            return False
+
+        # handle case where coord might not be a tuple/list
+        try: 
+            x, y = coord
+        except (TypeError, ValueError):
+            return False
+
+        # check if coordinates are within image bounds
+        return 0 <= x < width and 0 <= y < height
+
+
     resp_objs = []
 
     # img might be path, base64 or numpy array. Convert it to numpy whatever it is.
@@ -149,22 +173,37 @@ def extract_faces(
         w = min(width - x - 1, int(current_region.w))
         h = min(height - y - 1, int(current_region.h))
 
+        # landmark vaildation
+        landmarks = {
+            "left_eye":current_region.left_eye,
+            "right_eye":current_region.right_eye,
+            "nose":current_region.nose,
+            "mouth_left":current_region.mouth_left,
+            "mouth_right":current_region.mouth_right
+        }
+
+        # Sanitize landmarks - set invalid ones to None
+        for key, value in landmarks.items():
+            if not is_valid_landmark(value, width, height):
+                landmarks[key] = None
+
+
         facial_area = {
             "x": x,
             "y": y,
             "w": w,
             "h": h,
-            "left_eye": current_region.left_eye,
-            "right_eye": current_region.right_eye,
+            "left_eye": landmarks["left_eye"],
+            "right_eye": landmarks["right_eye"],
         }
 
         # optional nose, mouth_left and mouth_right fields are coming just for retinaface
         if current_region.nose is not None:
-            facial_area["nose"] = current_region.nose
+            facial_area["nose"] = landmarks["nose"]
         if current_region.mouth_left is not None:
-            facial_area["mouth_left"] = current_region.mouth_left
+            facial_area["mouth_left"] = landmarks["mouth_left"]
         if current_region.mouth_right is not None:
-            facial_area["mouth_right"] = current_region.mouth_right
+            facial_area["mouth_right"] = landmarks["mouth_right"]
 
         resp_obj = {
             "face": current_img,
diff --git a/tests/test_landmark_sanitization.py b/tests/test_landmark_sanitization.py
new file mode 100644
index 0000000..4fc6e44
--- /dev/null
+++ b/tests/test_landmark_sanitization.py
@@ -0,0 +1,78 @@
+import numpy as np
+import pytest
+from deepface.modules.detection import extract_faces, DetectedFace, FacialAreaRegion
+
+def sanitize_landmarks(region, width, height):
+    def is_valid_landmark(coord, width, height):
+        if coord is None:
+            return False
+        try:
+            x, y = coord
+        except (TypeError, ValueError):
+            return False
+        return 0 <= x < width and 0 <= y < height
+
+    landmarks = {
+        "left_eye": region.left_eye,
+        "right_eye": region.right_eye,
+        "nose": region.nose,
+        "mouth_left": region.mouth_left,
+        "mouth_right": region.mouth_right,
+    }
+    for key, value in landmarks.items():
+        if not is_valid_landmark(value, 100, 100):
+            landmarks[key] = None
+    return landmarks
+
+def test_sanitize_landmarks():
+    region = FacialAreaRegion(
+        x=10, y=10, w=50, h=50,
+        left_eye=(-5, 20),  # invalid
+        right_eye=(20, 200),  # invalid
+        nose=(30, 30),  # valid
+        mouth_left=(150, 20),  # invalid
+        mouth_right=(20, -10),  # invalid
+        confidence=0.9
+    )
+    landmarks = sanitize_landmarks(region, 100, 100)
+    print("Sanitized landmarks:", landmarks)
+    assert landmarks["left_eye"] is None
+    assert landmarks["right_eye"] is None
+    assert landmarks["nose"] == (30, 30)
+    assert landmarks["mouth_left"] is None
+    assert landmarks["mouth_right"] is None
+    print("Test passed: Invalid landmarks are sanitized to None.")
+
+def test_extract_faces_sanitizes_landmarks(monkeypatch):
+    # Create a dummy image
+    img = np.zeros((100, 100, 3), dtype=np.uint8)
+    
+    # Create a DetectedFace with off-image landmarks
+    facial_area = FacialAreaRegion(
+        x=10, y=10, w=50, h=50,
+        left_eye=(-5, 20),  # invalid
+        right_eye=(20, 200),  # invalid
+        nose=(30, 30),  # valid
+        mouth_left=(150, 20),  # invalid
+        mouth_right=(20, -10),  # invalid
+        confidence=0.9
+    )
+    detected_face = DetectedFace(img=img, facial_area=facial_area, confidence=0.9)
+    
+    # Patch detect_faces to return our test face
+    monkeypatch.setattr("f_deepface.deepface.modules.detection.detect_faces", lambda *args, **kwargs: [detected_face])
+    
+    # Use a different backend that will call detect_faces
+    result = extract_faces(img, detector_backend="opencv", enforce_detection=False)
+    facial_area_out = result[0]["facial_area"]
+    
+    print("Output facial_area:", facial_area_out)  # Debug print
+    
+    assert facial_area_out["left_eye"] is None
+    assert facial_area_out["right_eye"] is None
+    assert facial_area_out.get("nose") == (30, 30)
+    assert facial_area_out.get("mouth_left") is None
+    assert facial_area_out.get("mouth_right") is None
+
+if __name__ == "__main__":
+    test_sanitize_landmarks() 
\ No newline at end of file