Harden FastWordpieceTokenizer, FastBertNormalizer, and PhraseTokenizer with

  bounds verification and initialization checks:
  * Prevent null pointer dereferences by validating required FlatBuffer fields.
  * Prevent OOB reads during detokenization by checking token IDs against vocab size.
  * Secure FastBertNormalizer against adversarial heap slicing by tracking string pool limits.

PiperOrigin-RevId: 925446199

Author: tf-text-github-robot

tensorflow_text/core/kernels/BUILD

@@ -211,6 +211,7 @@ tf_cc_library(
         ":darts_clone_trie_builder",
         ":darts_clone_trie_wrapper",
         ":fast_bert_normalizer_model",
+        "@com_google_absl//absl/base:core_headers",
         "@com_google_absl//absl/memory",
         "@com_google_absl//absl/status",
         "@com_google_absl//absl/strings",
@@ -1255,9 +1256,11 @@ cc_library(
         ":string_vocab",
         ":whitespace_tokenizer",
         ":whitespace_tokenizer_config_builder",
+        "@com_google_absl//absl/base:core_headers",
         "@com_google_absl//absl/container:flat_hash_map",
         "@com_google_absl//absl/container:flat_hash_set",
         "@com_google_absl//absl/random",
+        "@com_google_absl//absl/status",
         "@com_google_absl//absl/status:statusor",
         "@com_google_absl//absl/strings",
         # lite/kernels/shim:status_macros tensorflow dep,

tensorflow_text/core/kernels/fast_bert_normalizer.h

@@ -15,9 +15,12 @@
 #ifndef THIRD_PARTY_TENSORFLOW_TEXT_CORE_KERNELS_FAST_BERT_NORMALIZER_H_
 #define THIRD_PARTY_TENSORFLOW_TEXT_CORE_KERNELS_FAST_BERT_NORMALIZER_H_
 
+#include <cstddef>
 #include <cstdint>
 #include <vector>
 
+#include "absl/base/optimization.h"
+#include "absl/status/status.h"
 #include "absl/strings/string_view.h"
 #include "icu4c/source/common/unicode/utf8.h"
 #include "tensorflow/lite/kernels/shim/status_macros.h"
@@ -83,7 +86,12 @@ class FastBertNormalizer {
   //  lifetime of the instance.
   static absl::StatusOr<FastBertNormalizer> Create(
       const uint32_t* trie_data, int data_for_codepoint_zero,
-      const char* normalized_string_pool) {
+      const char* normalized_string_pool,
+      size_t normalized_string_pool_size = static_cast<size_t>(-1)) {
+    if (trie_data == nullptr || normalized_string_pool == nullptr) {
+      return absl::InvalidArgumentError(
+          "trie_data or normalized_string_pool is null");
+    }
     FastBertNormalizer result;
     SH_ASSIGN_OR_RETURN(auto trie,
                         trie_utils::DartsCloneTrieWrapper::Create(trie_data));
@@ -92,6 +100,7 @@ class FastBertNormalizer {
     result.data_for_codepoint_zero_ = data_for_codepoint_zero;
     result.normalized_string_pool_ =
         reinterpret_cast<const char*>(normalized_string_pool);
+    result.normalized_string_pool_size_ = normalized_string_pool_size;
     return result;
   }
 
@@ -103,11 +112,20 @@ class FastBertNormalizer {
   //    through the lifetime of the instance.
   static absl::StatusOr<FastBertNormalizer> Create(
       const void* model_flatbuffer) {
+    if (model_flatbuffer == nullptr) {
+      return absl::InvalidArgumentError("model_flatbuffer is null");
+    }
     // `GetFastBertNormalizerModel()` is autogenerated by flatbuffer.
     auto model = GetFastBertNormalizerModel(model_flatbuffer);
+    if (model == nullptr || model->trie_array() == nullptr ||
+        model->normalized_string_pool() == nullptr) {
+      return absl::InvalidArgumentError(
+          "FastBertNormalizerModel or its required fields are null");
+    }
     return Create(
         model->trie_array()->data(), model->data_for_codepoint_zero(),
-        reinterpret_cast<const char*>(model->normalized_string_pool()->data()));
+        reinterpret_cast<const char*>(model->normalized_string_pool()->data()),
+        model->normalized_string_pool()->size());
   }
 
   // Normalizes the input based on config `lower_case_nfd_strip_accents`.
@@ -290,6 +308,12 @@ class FastBertNormalizer {
     }
     const int offset = (data & text_norm::kNormalizedStringOffsetMask) >>
                        text_norm::kBitsToEncodeUtf8LengthOfNormalizedString;
+    if (ABSL_PREDICT_FALSE(
+            offset < 0 ||
+            (normalized_string_pool_size_ != static_cast<size_t>(-1) &&
+             offset + len > normalized_string_pool_size_))) {
+      return "";
+    }
     return absl::string_view(normalized_string_pool_ + offset, len);
   }
 
@@ -331,6 +355,9 @@ class FastBertNormalizer {
   // The string pool of normalized strings. Each normalized string is a
   // substring denoted by (offset and length).
   const char* normalized_string_pool_;
+
+  // The size of normalized_string_pool_ if known, or -1.
+  size_t normalized_string_pool_size_ = static_cast<size_t>(-1);
 };
 
 }  // namespace text

tensorflow_text/core/kernels/fast_wordpiece_tokenizer.cc

@@ -17,9 +17,11 @@
 #include <memory>
 
 #include "absl/base/attributes.h"
+#include "absl/base/optimization.h"
 #include "absl/status/status.h"
 #include "absl/status/statusor.h"
 #include "absl/strings/match.h"
+#include "absl/strings/str_cat.h"
 #include "absl/strings/str_join.h"
 #include "absl/strings/string_view.h"
 #include "icu4c/source/common/unicode/uchar.h"
@@ -48,6 +50,11 @@ FastWordpieceTokenizer::Create(const void* config_flatbuffer) {
   FastWordpieceTokenizer tokenizer;
   // `GetFastWordpieceTokenizerConfig()` is autogenerated by flatbuffer.
   tokenizer.config_ = GetFastWordpieceTokenizerConfig(config_flatbuffer);
+  if (tokenizer.config_ == nullptr ||
+      tokenizer.config_->trie_array() == nullptr) {
+    return absl::InvalidArgumentError(
+        "FastWordpieceTokenizerConfig or its trie_array is null.");
+  }
   auto trie_or = trie_utils::DartsCloneTrieWrapper::Create(
       tokenizer.config_->trie_array()->data());
   if (!trie_or.ok()) {
@@ -127,8 +134,23 @@ FastWordpieceTokenizer::DetokenizeToTokens(
         "true in the config flatbuffer. Please rebuild the model flatbuffer "
         "by setting support_detokenization=true.");
   }
+  if (config_->vocab_array() == nullptr ||
+      config_->vocab_is_suffix_array() == nullptr) {
+    return absl::InternalError(
+        "Missing vocab_array or vocab_is_suffix_array in config.");
+  }
+  const int vocab_size = config_->vocab_array()->size();
+  const int is_suffix_size = config_->vocab_is_suffix_array()->size();
   for (int id : input) {
+    if (ABSL_PREDICT_FALSE(id < 0 || id >= vocab_size ||
+                           id >= is_suffix_size)) {
+      return absl::OutOfRangeError(
+          absl::StrCat("Token ID out of bounds: ", id));
+    }
     auto vocab = config_->vocab_array()->Get(id);
+    if (ABSL_PREDICT_FALSE(vocab == nullptr)) {
+      return absl::InternalError("Null vocab string in vocab_array.");
+    }
     auto is_suffix = config_->vocab_is_suffix_array()->Get(id);
     if (!subwords.empty() && !is_suffix) {
       // When current subword is not a suffix token, it marks the start of a new
@@ -140,6 +162,9 @@ FastWordpieceTokenizer::DetokenizeToTokens(
     // Special case: when a suffix token e.g. "##a" appears at the start of the
     // input ids, we preserve the suffix_indicator.
     if (subwords.empty() && is_suffix) {
+      if (ABSL_PREDICT_FALSE(config_->suffix_indicator() == nullptr)) {
+        return absl::InternalError("Missing suffix_indicator in config.");
+      }
       subwords.emplace_back(config_->suffix_indicator()->string_view());
     }
     subwords.emplace_back(vocab->string_view());

tensorflow_text/core/kernels/phrase_tokenizer.cc

@@ -20,7 +20,10 @@
 #include <string>
 #include <vector>
 
+#include "absl/base/optimization.h"
+#include "absl/status/status.h"
 #include "absl/strings/match.h"
+#include "absl/strings/str_cat.h"
 #include "absl/strings/str_join.h"
 #include "absl/strings/string_view.h"
 #include "tensorflow/lite/kernels/shim/status_macros.h"
@@ -34,6 +37,12 @@ namespace text {
   PhraseTokenizer tokenizer;
   // `GetPhraseTokenizerConfig()` is autogenerated by flatbuffer.
   tokenizer.phrase_config_ = GetPhraseTokenizerConfig(config_flatbuffer);
+  if (tokenizer.phrase_config_ == nullptr ||
+      tokenizer.phrase_config_->vocab_trie() == nullptr ||
+      tokenizer.phrase_config_->whitespace_config() == nullptr) {
+    return absl::InvalidArgumentError(
+        "PhraseTokenizerConfig or required fields are null.");
+  }
   tokenizer.trie_ = absl::make_unique<sentencepiece::DoubleArrayTrie>(
       tokenizer.phrase_config_->vocab_trie()->nodes());
   tokenizer.prob_ = static_cast<float>(tokenizer.phrase_config_->prob()) / 100;
@@ -174,8 +183,19 @@ absl::StatusOr<std::vector<std::string>> PhraseTokenizer::DetokenizeToTokens(
         "true in the config flatbuffer. Please rebuild the model flatbuffer "
         "by setting support_detokenization=true.");
   }
+  if (phrase_config_->vocab_array() == nullptr) {
+    return absl::InternalError("Missing vocab_array in config.");
+  }
+  const int vocab_size = phrase_config_->vocab_array()->size();
   for (int id : input) {
+    if (ABSL_PREDICT_FALSE(id < 0 || id >= vocab_size)) {
+      return absl::OutOfRangeError(
+          absl::StrCat("Token ID out of bounds: ", id));
+    }
     auto vocab = phrase_config_->vocab_array()->Get(id);
+    if (ABSL_PREDICT_FALSE(vocab == nullptr)) {
+      return absl::InternalError("Null vocab string in vocab_array.");
+    }
     output_tokens.emplace_back(vocab->string_view());
   }
   return output_tokens;