Commit message: Prevent use after free.

A very old version of the code used `result` as a simple pointer to a resource. Two years later, the pointer got changed to a `unique_ptr` but author forgot to remove the call to `Unref`. Three years after that, we finally uncover the UAF.

PiperOrigin-RevId: 387924872
Change-Id: I70fb6f199164de49fac20c168132a07b84903f9b
CVE: CVE-2021-37652
CWE: CWE-416
Vulnerability description: TensorFlow is an end-to-end open source platform for machine learning. In affected versions the implementation for `tf.raw_ops.BoostedTreesCreateEnsemble` can result in a use after free error if an attacker supplies specially crafted arguments. The [implementation](https://github.com/tensorflow/tensorflow/blob/f24faa153ad31a4b51578f8181d3aaab77a1ddeb/tensorflow/core/kernels/boosted_trees/resource_ops.cc#L55) uses a reference counted resource and decrements the refcount if the initialization fails, as it should. However, when the code was written, the resource was represented as a naked pointer but later refactoring has changed it to be a smart pointer. Thus, when the pointer leaves the scope, a subsequent `free`-ing of the resource occurs, but this fails to take into account that the refcount has already reached 0, thus the resource has been already freed. During this double-free process, members of the resource object are accessed for cleanup but they are invalid as the entire resource has been freed. We have patched the issue in GitHub commit 5ecec9c6fbdbc6be03295685190a45e7eee726ab. The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

Project: tensorflow
File: resource_ops.cc

  void Compute(OpKernelContext* context) override {
    // Get the stamp token.
    const Tensor* stamp_token_t;
    OP_REQUIRES_OK(context, context->input("stamp_token", &stamp_token_t));
    int64_t stamp_token = stamp_token_t->scalar<int64>()();

    // Get the tree ensemble proto.
    const Tensor* tree_ensemble_serialized_t;
    OP_REQUIRES_OK(context, context->input("tree_ensemble_serialized",
                                           &tree_ensemble_serialized_t));
    std::unique_ptr<BoostedTreesEnsembleResource> result(
        new BoostedTreesEnsembleResource());
    if (!result->InitFromSerialized(
            tree_ensemble_serialized_t->scalar<tstring>()(), stamp_token)) {
      result->Unref();
      OP_REQUIRES(
          context, false,
          errors::InvalidArgument("Unable to parse tree ensemble proto."));
    }

    // Only create one, if one does not exist already. Report status for all
    // other exceptions.
    auto status =
        CreateResource(context, HandleFromInput(context, 0), result.release());
    if (status.code() != tensorflow::error::ALREADY_EXISTS) {
      OP_REQUIRES_OK(context, status);
    }
  }

Project: tensorflow
File: resource_ops.cc

  void Compute(OpKernelContext* context) override {
    // Get the stamp token.
    const Tensor* stamp_token_t;
    OP_REQUIRES_OK(context, context->input("stamp_token", &stamp_token_t));
    int64_t stamp_token = stamp_token_t->scalar<int64>()();

    // Get the tree ensemble proto.
    const Tensor* tree_ensemble_serialized_t;
    OP_REQUIRES_OK(context, context->input("tree_ensemble_serialized",
                                           &tree_ensemble_serialized_t));
    std::unique_ptr<BoostedTreesEnsembleResource> result(
        new BoostedTreesEnsembleResource());
    if (!result->InitFromSerialized(
            tree_ensemble_serialized_t->scalar<tstring>()(), stamp_token)) {
      result->Unref();
      result.release();  // Needed due to the `->Unref` above, to prevent UAF
      OP_REQUIRES(
          context, false,
          errors::InvalidArgument("Unable to parse tree ensemble proto."));
    }

    // Only create one, if one does not exist already. Report status for all
    // other exceptions.
    auto status =
        CreateResource(context, HandleFromInput(context, 0), result.release());
    if (status.code() != tensorflow::error::ALREADY_EXISTS) {
      OP_REQUIRES_OK(context, status);
    }
  }