Vulnerability: Heap out of bounds access in MakeEdge in TensorFlow ### Impact
Under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The [`MakeEdge` function](https://github.com/tensorflow/tensorflow/blob/3616708cb866365301d8e67b43b32b46d94b08a0/tensorflow/core/common_runtime/graph_constructor.cc#L1426-L1438) creates an edge between one output tensor of the `src` node (given by `output_index`) and the input slot of the `dst` node (given by `input_index`). This is only possible if the types of the tensors on both sides coincide, so the function begins by obtaining the corresponding `DataType` values and comparing these for equality:

```cc
  DataType src_out = src->output_type(output_index);
  DataType dst_in = dst->input_type(input_index);
  //...
```

However, there is no check that the indices point to inside of the arrays they index into. Thus, this can result in accessing data out of bounds of the corresponding heap allocated arrays.

In most scenarios, this can manifest as unitialized data access, but if the index points far away from the boundaries of the arrays this can be used to leak addresses from the library.

### Patches
We have patched the issue in GitHub commit [0cc38aaa4064fd9e79101994ce9872c6d91f816b](https://github.com/tensorflow/tensorflow/commit/0cc38aaa4064fd9e79101994ce9872c6d91f816b) and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.

Since this issue also impacts TF versions before 2.4, we will patch all releases between 1.15 and 2.3 inclusive.

### For more information
Please consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.
Vulnerability ID: GHSA-q263-fvxm-m5mw
CWE: CWE-125
Severity score: 4.4
Project: https://github.com/tensorflow/tensorflow
Published: 2020-12-10
File: tensorflow/core/common_runtime/graph_constructor.cc
Commit message: Prevent unitialized memory access in `GraphConstructor::MakeEdge`

The `MakeEdge` implementation assumes that there exists an output at `output_index` of `src` node and an input at `input_index` of `dst` node. However, if this is not the case this results in accessing data out of bounds. Because we are accessing an array that is a private member of a class and only in read only mode, this usually results only in unitialized memory access. However, it is reasonable to think that malicious users could manipulate these indexes to actually read data outside the class, thus resulting in information leakage and further exploits.

PiperOrigin-RevId: 346343288
Change-Id: I2127da27c2023d27f26efd39afa6c853385cab6f
Commit author: Mihai Maruseac

Vulnerable version (before fix):
 limitations under the License. #include "tensorflow/core/lib/gtl/inlined_vector.h" #include "tensorflow/core/lib/strings/scanner.h" #include "tensorflow/core/lib/strings/str_util.h" #include "tensorflow/core/platform/logging.h" #include "tensorflow/core/platform/macros.h" #include "tensorflow/core/public/version.h" void GraphConstructor::Undo() {  Status GraphConstructor::MakeEdge(Node* src, int output_index, Node* dst,                                   int input_index) {   DataType src_out = src->output_type(output_index);   DataType dst_in = dst->input_type(input_index);   if (!TypesCompatible(dst_in, src_out)) {

Fixed version (after fix):
 limitations under the License. #include "tensorflow/core/lib/gtl/inlined_vector.h" #include "tensorflow/core/lib/strings/scanner.h" #include "tensorflow/core/lib/strings/str_util.h" #include "tensorflow/core/platform/errors.h" #include "tensorflow/core/platform/logging.h" #include "tensorflow/core/platform/macros.h" #include "tensorflow/core/public/version.h" void GraphConstructor::Undo() {  Status GraphConstructor::MakeEdge(Node* src, int output_index, Node* dst,                                   int input_index) {   if (output_index >= src->num_outputs()) {     return errors::InvalidArgument(         "Output ", output_index, " of node ", src->name(),         " does not exist. Node only has ", src->num_outputs(), " outputs.");   }   if (input_index >= dst->num_inputs()) {     return errors::InvalidArgument(         "Input ", input_index, " of node ", dst->name(),         " does not exist. Node only has ", dst->num_inputs(), " inputs.");   }    DataType src_out = src->output_type(output_index);   DataType dst_in = dst->input_type(input_index);   if (!TypesCompatible(dst_in, src_out)) {

Patch:
patch: @@ -44,6 +44,7 @@ limitations under the License.
 #include "tensorflow/core/lib/gtl/inlined_vector.h"
 #include "tensorflow/core/lib/strings/scanner.h"
 #include "tensorflow/core/lib/strings/str_util.h"
+#include "tensorflow/core/platform/errors.h"
 #include "tensorflow/core/platform/logging.h"
 #include "tensorflow/core/platform/macros.h"
 #include "tensorflow/core/public/version.h"
@@ -1425,6 +1426,17 @@ void GraphConstructor::Undo() {
 
 Status GraphConstructor::MakeEdge(Node* src, int output_index, Node* dst,
                                   int input_index) {
+  if (output_index >= src->num_outputs()) {
+    return errors::InvalidArgument(
+        "Output ", output_index, " of node ", src->name(),
+        " does not exist. Node only has ", src->num_outputs(), " outputs.");
+  }
+  if (input_index >= dst->num_inputs()) {
+    return errors::InvalidArgument(
+        "Input ", input_index, " of node ", dst->name(),
+        " does not exist. Node only has ", dst->num_inputs(), " inputs.");
+  }
+
   DataType src_out = src->output_type(output_index);
   DataType dst_in = dst->input_type(input_index);
   if (!TypesCompatible(dst_in, src_out)) {
path: tensorflow/core/common_runtime/graph_constructor.cc