diff --git a/mindspore/ccsrc/minddata/dataset/api/datasets.cc b/mindspore/ccsrc/minddata/dataset/api/datasets.cc
index 9a68436b5ee..afac5545e5d 100644
--- a/mindspore/ccsrc/minddata/dataset/api/datasets.cc
+++ b/mindspore/ccsrc/minddata/dataset/api/datasets.cc
@@ -155,8 +155,6 @@ std::shared_ptr<Iterator> Dataset::CreateIteratorCharIF(std::vector<std::vector<
       MS_LOG(ERROR) << "CreateIterator failed." << rc;
       return nullptr;
     }
-
-    return iter;
   } catch (const std::exception &err) {
     MS_LOG(ERROR) << "CreateIterator: Iterator exception caught: " << err.what();
     return nullptr;
diff --git a/mindspore/ccsrc/minddata/dataset/callback/ds_callback.h b/mindspore/ccsrc/minddata/dataset/callback/ds_callback.h
index 95e36c2b81c..3f46296b026 100644
--- a/mindspore/ccsrc/minddata/dataset/callback/ds_callback.h
+++ b/mindspore/ccsrc/minddata/dataset/callback/ds_callback.h
@@ -33,6 +33,9 @@ class DSCallback {
   /// \param step_size number of steps to call DSNStepBegin()
   explicit DSCallback(int32_t step_size = 1) : step_size_(step_size) {}
 
+  /// \brief Destructor
+  ~DSCallback() = default;
+
   /// \brief actual callback function for begin, needs to be overridden in the derived class
   /// \param cb_param, callback parameter passed in from DatasetOp when calling the callback
   /// \return Status
diff --git a/mindspore/ccsrc/minddata/dataset/engine/consumers/tree_consumer.h b/mindspore/ccsrc/minddata/dataset/engine/consumers/tree_consumer.h
index 1fcb0888609..a821eb860b4 100644
--- a/mindspore/ccsrc/minddata/dataset/engine/consumers/tree_consumer.h
+++ b/mindspore/ccsrc/minddata/dataset/engine/consumers/tree_consumer.h
@@ -36,6 +36,9 @@ class TreeConsumer {
  public:
   /// Constructor that prepares an empty tree_adapter
   TreeConsumer();
+
+  /// \brief Destructor
+  ~TreeConsumer() = default;
   /// Initializes the consumer, this involves constructing and preparing the tree.
   /// \param d The dataset node that represent the root of the IR tree.
   /// \return Status error code.
diff --git a/mindspore/ccsrc/minddata/dataset/include/dataset/iterator.h b/mindspore/ccsrc/minddata/dataset/include/dataset/iterator.h
index 6eb7444be52..7bbb8152ac0 100644
--- a/mindspore/ccsrc/minddata/dataset/include/dataset/iterator.h
+++ b/mindspore/ccsrc/minddata/dataset/include/dataset/iterator.h
@@ -92,7 +92,7 @@ class Iterator {
 
     // Destructor
     ~_Iterator() {
-      if (cur_row_) {
+      if (cur_row_ != nullptr) {
         delete cur_row_;
         cur_row_ = nullptr;
       }
diff --git a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc
index ad5ba5874c9..d10828c579c 100644
--- a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc
+++ b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc
@@ -992,14 +992,22 @@ bool Pad(const LiteMat &src, LiteMat &dst, int top, int bottom, int left, int ri
 }
 
 std::vector<std::vector<float>> GetDefaultBoxes(BoxesConfig config) {
+  size_t size = config.num_default.size();
+  if (size <= 1 || config.feature_size.size() != size || config.steps.size() != size ||
+      config.aspect_rations.size() != size) {
+    return {};
+  }
+  if (config.max_scale < config.min_scale) {
+    return {};
+  }
   std::vector<float> fk;
   float num = static_cast<float>(config.img_shape[0]);
   for (int i = 0; i < config.steps.size(); i++) {
+    if (config.steps[i] == 0) {
+      return {};
+    }
     fk.push_back(num / config.steps[i]);
   }
-  if (config.num_default.size() < 2) {
-    return {};
-  }
   float scale_rate = (config.max_scale - config.min_scale) / (config.num_default.size() - 1);
   std::vector<float> scales(config.num_default.size());
   for (int i = 0; i < scales.size(); i++) {
@@ -1043,7 +1051,15 @@ std::vector<std::vector<float>> GetDefaultBoxes(BoxesConfig config) {
 
 void ConvertBoxes(std::vector<std::vector<float>> &boxes, const std::vector<std::vector<float>> &default_boxes,
                   const BoxesConfig config) {
+  if (boxes.size() != default_boxes.size() || config.prior_scaling.size() != 2) {
+    boxes = {};
+    return;
+  }
   for (int i = 0; i < default_boxes.size(); i++) {
+    if (boxes[i].size() != 4 || default_boxes[i].size() != 4) {
+      boxes = {};
+      return;
+    }
     boxes[i][0] = boxes[i][0] * config.prior_scaling[0] * default_boxes[i][2] + default_boxes[i][0];
     boxes[i][1] = boxes[i][1] * config.prior_scaling[0] * default_boxes[i][3] + default_boxes[i][1];
     boxes[i][2] = exp(boxes[i][2] * config.prior_scaling[1]) * default_boxes[i][2];
@@ -1057,6 +1073,9 @@ std::vector<int> ApplyNms(const std::vector<std::vector<float>> &all_boxes, std:
   std::vector<float> areas(boxes_num);
   std::vector<int> order(boxes_num);
   for (int i = 0; i < boxes_num; i++) {
+    if (all_boxes[i].size() < 4) {
+      return {};
+    }
     areas[i] = (all_boxes[i][3] - all_boxes[i][1] + 1) * (all_boxes[i][2] - all_boxes[i][0] + 1);
     order[i] = i;
   }
diff --git a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h
index a3e3a648285..da16b5051df 100644
--- a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h
+++ b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h
@@ -215,7 +215,7 @@ bool GetAffineTransform(std::vector<Point> src_point, std::vector<Point> dst_poi
 /// \brief Matrix transpose.
 /// \param[in] src Input matrix.
 /// \param[in] dst Output matrix.
-bool Transpose(LiteMat &src, LiteMat &dst);
+bool Transpose(const LiteMat &src, LiteMat &dst);
 
 /// \brief Filter the image by a Gaussian kernel
 /// \param[in] src LiteMat image to be processed. Only LiteMat of type UINT8 is supported now.
diff --git a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.cc b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.cc
index 85ee2fca91c..d555a248c29 100644
--- a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.cc
+++ b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.cc
@@ -177,6 +177,10 @@ void LiteMat::Init(int width, LDataType data_type) {
   dims_ = 1;
   height_ = 1;
   channel_ = 1;
+  if (!CheckLiteMat()) {
+    Release();
+    return;
+  }
   c_step_ = width;
   size_ = c_step_ * elem_size_;
   data_ptr_ = AlignMalloc(size_);
@@ -193,6 +197,10 @@ void LiteMat::Init(int width, int height, LDataType data_type) {
   height_ = height;
   dims_ = 2;
   channel_ = 1;
+  if (!CheckLiteMat()) {
+    Release();
+    return;
+  }
   c_step_ = width_ * height_;
   size_ = c_step_ * elem_size_;
   data_ptr_ = AlignMalloc(size_);
@@ -209,6 +217,10 @@ void LiteMat::Init(int width, int height, void *p_data, LDataType data_type) {
   height_ = height;
   dims_ = 2;
   channel_ = 1;
+  if (!CheckLiteMat()) {
+    Release();
+    return;
+  }
   c_step_ = height_ * width_;
   size_ = c_step_ * channel_ * elem_size_;
   data_ptr_ = p_data;
@@ -225,6 +237,10 @@ void LiteMat::Init(int width, int height, int channel, LDataType data_type, bool
   height_ = height;
   dims_ = 3;
   channel_ = channel;
+  if (!CheckLiteMat()) {
+    Release();
+    return;
+  }
   if (align_memory) {
     c_step_ = ((height_ * width_ * elem_size_ + ALIGN - 1) & (-ALIGN)) / elem_size_;
   } else {
@@ -247,6 +263,10 @@ void LiteMat::Init(int width, int height, int channel, void *p_data, LDataType d
   height_ = height;
   dims_ = 3;
   channel_ = channel;
+  if (!CheckLiteMat()) {
+    Release();
+    return;
+  }
   c_step_ = height_ * width_;
   size_ = c_step_ * channel_ * elem_size_;
   data_ptr_ = p_data;
@@ -299,6 +319,24 @@ void LiteMat::AlignFree(void *ptr) {
 
 inline void LiteMat::InitElemSize(LDataType data_type) { elem_size_ = data_type.SizeInBytes(); }
 
+bool LiteMat::CheckLiteMat() {
+  if (width_ <= 0 || height_ <= 0 || channel_ <= 0 || elem_size_ <= 0) {
+    return false;
+  }
+  if (height_ != 1 && height_ > std::numeric_limits<int>::max() / width_) {
+    return false;
+  }
+  int area = height_ * width_;
+  if (channel_ != 1 && channel_ > std::numeric_limits<int>::max() / area) {
+    return false;
+  }
+  int size = area * channel_;
+  if (elem_size_ > std::numeric_limits<int>::max() / size) {
+    return false;
+  }
+  return true;
+}
+
 bool LiteMat::GetROI(int x, int y, int w, int h, LiteMat &m) {
   if (x < 0 || y < 0 || x > width_ - w || h > height_ - y || w <= 0 || h <= 0) {
     return false;
diff --git a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.h b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.h
index 38273e0be76..6acead3ed05 100644
--- a/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.h
+++ b/mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.h
@@ -290,6 +290,8 @@ class LiteMat {
   /// \param[in] c2 The number used to set teh value of step[2].
   void setSteps(int c0, int c1, int c2);
 
+  bool CheckLiteMat();
+
  public:
   void *data_ptr_ = nullptr;
   int elem_size_;
diff --git a/mindspore/ccsrc/minddata/dataset/util/arena.h b/mindspore/ccsrc/minddata/dataset/util/arena.h
index 09d6467e78f..117dcd1a9d5 100644
--- a/mindspore/ccsrc/minddata/dataset/util/arena.h
+++ b/mindspore/ccsrc/minddata/dataset/util/arena.h
@@ -110,7 +110,7 @@ class Arena : public MemoryPool {
   ~Arena() override {
 #ifdef ENABLE_GPUQUE
     if (is_cuda_malloc_) {
-      if (ptr_) {
+      if (ptr_ != nullptr) {
         (void)cudaFreeHost(ptr_);
       }
     }
diff --git a/mindspore/ccsrc/minddata/dataset/util/auto_index.h b/mindspore/ccsrc/minddata/dataset/util/auto_index.h
index 886462248bf..a68d7a586c8 100644
--- a/mindspore/ccsrc/minddata/dataset/util/auto_index.h
+++ b/mindspore/ccsrc/minddata/dataset/util/auto_index.h
@@ -57,7 +57,7 @@ class AutoIndexObj : public BPlusTree<int64_t, V, A, std::less<int64_t>, T> {
 
   Status insert(std::unique_ptr<value_type> &&val, key_type *key = nullptr) {
     key_type my_inx = inx_.fetch_add(1);
-    if (key) {
+    if (key != nullptr) {
       *key = my_inx;
     }
     return my_tree::DoInsert(my_inx, std::move(val));
diff --git a/mindspore/ccsrc/minddata/dataset/util/treap.h b/mindspore/ccsrc/minddata/dataset/util/treap.h
index 50c59b4f761..8e8003f2ce9 100644
--- a/mindspore/ccsrc/minddata/dataset/util/treap.h
+++ b/mindspore/ccsrc/minddata/dataset/util/treap.h
@@ -77,7 +77,7 @@ class Treap {
   // @return
   //    Return the root of the heap. It has the highest priority. But not necessarily the first key.
   std::pair<NodeValue, bool> Top() const {
-    if (root_) {
+    if (root_ != nullptr) {
       return std::make_pair(root_->nv, true);
     } else {
       return std::make_pair(NodeValue{key_type(), priority_type()}, false);
@@ -86,7 +86,7 @@ class Treap {
 
   // Remove the root of the heap.
   void Pop() {
-    if (root_) {
+    if (root_ != nullptr) {
       DeleteKey(root_->nv.key);
     }
   }
@@ -116,9 +116,9 @@ class Treap {
   class iterator : public std::iterator<std::forward_iterator_tag, TreapNode> {
    public:
     explicit iterator(Treap *tr) : tr_(tr), cur_(nullptr) {
-      if (tr_) {
+      if (tr_ != nullptr) {
         cur_ = tr_->root_;
-        while (cur_) {
+        while (cur_ != nullptr) {
           stack_.push(cur_);
           cur_ = cur_->left;
         }
@@ -196,9 +196,9 @@ class Treap {
   class const_iterator : public std::iterator<std::forward_iterator_tag, TreapNode> {
    public:
     explicit const_iterator(const Treap *tr) : tr_(tr), cur_(nullptr) {
-      if (tr_) {
+      if (tr_ != nullptr) {
         cur_ = tr_->root_;
-        while (cur_) {
+        while (cur_ != nullptr) {
           stack_.push(cur_);
           cur_ = cur_->left;
         }
@@ -226,7 +226,7 @@ class Treap {
     const_iterator &operator++() {
       if (cur_) {
         stack_.pop();
-        if (cur_->right) {
+        if (cur_->right != nullptr) {
           TreapNode *n = cur_->right;
           while (n) {
             stack_.push(n);
@@ -247,7 +247,7 @@ class Treap {
       iterator tmp(*this);
       if (cur_) {
         stack_.pop();
-        if (cur_->right) {
+        if ((cur_->right) != nullptr) {
           TreapNode *n = cur_->right;
           while (n) {
             stack_.push(n);
diff --git a/mindspore/ccsrc/minddata/mindrecord/io/shard_index_generator.cc b/mindspore/ccsrc/minddata/mindrecord/io/shard_index_generator.cc
index 35b23dd9037..21e223be24e 100644
--- a/mindspore/ccsrc/minddata/mindrecord/io/shard_index_generator.cc
+++ b/mindspore/ccsrc/minddata/mindrecord/io/shard_index_generator.cc
@@ -357,7 +357,7 @@ MSRStatus ShardIndexGenerator::BindParameterExecuteSQL(
   const std::vector<std::vector<std::tuple<std::string, std::string, std::string>>> &data) {
   sqlite3_stmt *stmt = nullptr;
   if (sqlite3_prepare_v2(db, common::SafeCStr(sql), -1, &stmt, 0) != SQLITE_OK) {
-    if (stmt) {
+    if (stmt != nullptr) {
       (void)sqlite3_finalize(stmt);
     }
     MS_LOG(ERROR) << "SQL error: could not prepare statement, sql: " << sql;
diff --git a/mindspore/ccsrc/minddata/mindrecord/io/shard_writer.cc b/mindspore/ccsrc/minddata/mindrecord/io/shard_writer.cc
index db6315d9dc1..c23e2656084 100644
--- a/mindspore/ccsrc/minddata/mindrecord/io/shard_writer.cc
+++ b/mindspore/ccsrc/minddata/mindrecord/io/shard_writer.cc
@@ -558,6 +558,7 @@ int ShardWriter::LockWriter(bool parallel_writer) {
     flock(fd, LOCK_EX);
   } else {
     MS_LOG(ERROR) << "Shard writer failed when locking file";
+    close(fd);
     return -1;
   }
 #endif
diff --git a/mindspore/ccsrc/minddata/mindrecord/meta/shard_column.cc b/mindspore/ccsrc/minddata/mindrecord/meta/shard_column.cc
index a3df213234e..84b8e45d698 100644
--- a/mindspore/ccsrc/minddata/mindrecord/meta/shard_column.cc
+++ b/mindspore/ccsrc/minddata/mindrecord/meta/shard_column.cc
@@ -424,6 +424,7 @@ MSRStatus ShardColumn::UncompressInt(const uint64_t &column_id, std::unique_ptr<
   int ret_code = memcpy_s(data_ptr->get(), *num_bytes, data, *num_bytes);
   if (ret_code != 0) {
     MS_LOG(ERROR) << "Failed to copy data!";
+    return FAILED;
   }
 
   return SUCCESS;
diff --git a/mindspore/dataset/datapreprocess/preprocess_imagenet_validate_dataset.py b/mindspore/dataset/datapreprocess/preprocess_imagenet_validate_dataset.py
index 5d15318c85c..9321b021eb5 100644
--- a/mindspore/dataset/datapreprocess/preprocess_imagenet_validate_dataset.py
+++ b/mindspore/dataset/datapreprocess/preprocess_imagenet_validate_dataset.py
@@ -34,7 +34,7 @@ def preprocess_imagenet_validation_dataset(train_dataset_path, validation_datase
         validate_sub_dir = os.path.join(validation_dataset_path, sub_dir_name)
         validate_sub_dir = os.path.realpath(validate_sub_dir)
         if not os.path.exists(validate_sub_dir):
-            os.makedirs(validate_sub_dir)
+            os.makedirs(validate_sub_dir, mode=0o750)
 
     real_file_path = os.path.realpath(image_label_mapping_file)
     mappings = [mapping.strip() for mapping in open(real_file_path).readlines()]
diff --git a/mindspore/dataset/engine/validators.py b/mindspore/dataset/engine/validators.py
index bf688a8e577..ad892842889 100644
--- a/mindspore/dataset/engine/validators.py
+++ b/mindspore/dataset/engine/validators.py
@@ -284,7 +284,7 @@ def check_save(method):
         nreq_param_str = ['file_name', 'file_type']
         validate_dataset_param_value(nreq_param_int, param_dict, int)
         if (param_dict.get('num_files') <= 0 or param_dict.get('num_files') > 1000):
-            raise ValueError("num_files should between {} and {}.".format(1, 1000))
+            raise ValueError("num_files should between 0 and 1000.")
         validate_dataset_param_value(nreq_param_str, param_dict, str)
         if param_dict.get('file_type') != 'mindrecord':
             raise ValueError("{} dataset format is not supported.".format(param_dict.get('file_type')))
diff --git a/mindspore/dataset/text/validators.py b/mindspore/dataset/text/validators.py
index e027ade0b19..883ac42e890 100644
--- a/mindspore/dataset/text/validators.py
+++ b/mindspore/dataset/text/validators.py
@@ -318,7 +318,7 @@ def check_from_dataset(method):
             type_check(freq_range, (tuple,), "freq_range")
 
             if len(freq_range) != 2:
-                raise ValueError("freq_range needs to be a tuple of 2 integers or an int and a None.")
+                raise ValueError("freq_range needs to be a tuple of 2 element.")
 
             for num in freq_range:
                 if num is not None and (not isinstance(num, int)):
diff --git a/tests/ut/python/dataset/test_from_dataset.py b/tests/ut/python/dataset/test_from_dataset.py
index 801f1aae32f..878ef48091c 100644
--- a/tests/ut/python/dataset/test_from_dataset.py
+++ b/tests/ut/python/dataset/test_from_dataset.py
@@ -131,7 +131,7 @@ def test_from_dataset_exceptions():
         except (TypeError, ValueError) as e:
             assert s in str(e), str(e)
 
-    test_config("text", (), 1, "freq_range needs to be a tuple of 2 integers or an int and a None.")
+    test_config("text", (), 1, "freq_range needs to be a tuple of 2 element.")
     test_config("text", (2, 3), 1.2345,
                 "Argument top_k with value 1.2345 is not of type [<class 'int'>, <class 'NoneType'>]")
     test_config(23, (2, 3), 1.2345, "Argument col[0] with value 23 is not of type [<class 'str'>]")
diff --git a/tests/ut/python/dataset/test_save_op.py b/tests/ut/python/dataset/test_save_op.py
index 41f34b7b7e2..037460952b6 100644
--- a/tests/ut/python/dataset/test_save_op.py
+++ b/tests/ut/python/dataset/test_save_op.py
@@ -381,7 +381,7 @@ def test_case_05(add_remove_file):
 
     d1 = ds.GeneratorDataset(generator_1d, ["data"], shuffle=False)
 
-    with pytest.raises(Exception, match="num_files should between 1 and 1000."):
+    with pytest.raises(Exception, match="num_files should between 0 and 1000."):
         d1.save(AUTO_FILE, 0)