Vulnerability: Out of bounds read in Tensorflow ### Impact
TensorFlow's [type inference](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/core/graph/graph.cc#L223-L229) can cause a heap OOB read as the bounds checking is done in a `DCHECK` (which is a no-op during production):

```cc
if (node_t.type_id() != TFT_UNSET) {
  int ix = input_idx[i];
  DCHECK(ix < node_t.args_size())
      << "input " << i << " should have an output " << ix
      << " but instead only has " << node_t.args_size()
      << " outputs: " << node_t.DebugString();
  input_types.emplace_back(node_t.args(ix));
  // ...
}       
```   
      
An attacker can control `input_idx` such that `ix` would be larger than the number of values in `node_t.args`.
        
### Patches
We have patched the issue in GitHub commit [c99d98cd189839dcf51aee94e7437b54b31f8abd](https://github.com/tensorflow/tensorflow/commit/c99d98cd189839dcf51aee94e7437b54b31f8abd).
  
The fix will be included in TensorFlow 2.8.0. This is the only affected version.

### 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-vq36-27g6-p492
CWE: CWE-125
Severity score: 8.1
Project: https://github.com/tensorflow/tensorflow
Published: 2022-02-09
File: tensorflow/core/graph/graph.cc
Commit message: Handle invalid inputs instead of crashing.

PiperOrigin-RevId: 409549744
Change-Id: I7f5935b34b53f7e426a5462fcc027bdbf5dcda24
Commit author: Dan Moldovan

Vulnerable version (before fix):
 void Node::RunForwardTypeInference() {       const auto& node_t = node->def().experimental_type();       if (node_t.type_id() != TFT_UNSET) {         int ix = input_idx[i];         DCHECK(ix < node_t.args_size())             << "input " << i << " should have an output " << ix             << " but instead only has " << node_t.args_size()             << " outputs: " << node_t.DebugString();         input_types.emplace_back(node_t.args(ix));       } else {         input_types.emplace_back(*no_type);

Fixed version (after fix):
 void Node::RunForwardTypeInference() {       const auto& node_t = node->def().experimental_type();       if (node_t.type_id() != TFT_UNSET) {         int ix = input_idx[i];         if (ix >= node_t.args_size()) {           LOG(WARNING) << name() << " has bad type information: input " << i                        << " should have an output " << ix                        << " but instead only has " << node_t.args_size()                        << " outputs: " << node_t.DebugString()                        << "\nThis indicates either "                           "a bug in op registration or a corrupted graph.";           ClearTypeInfo();           return;         }         input_types.emplace_back(node_t.args(ix));       } else {         input_types.emplace_back(*no_type);

Patch:
patch: @@ -222,10 +222,16 @@ void Node::RunForwardTypeInference() {
       const auto& node_t = node->def().experimental_type();
       if (node_t.type_id() != TFT_UNSET) {
         int ix = input_idx[i];
-        DCHECK(ix < node_t.args_size())
-            << "input " << i << " should have an output " << ix
-            << " but instead only has " << node_t.args_size()
-            << " outputs: " << node_t.DebugString();
+        if (ix >= node_t.args_size()) {
+          LOG(WARNING) << name() << " has bad type information: input " << i
+                       << " should have an output " << ix
+                       << " but instead only has " << node_t.args_size()
+                       << " outputs: " << node_t.DebugString()
+                       << "\nThis indicates either "
+                          "a bug in op registration or a corrupted graph.";
+          ClearTypeInfo();
+          return;
+        }
         input_types.emplace_back(node_t.args(ix));
       } else {
         input_types.emplace_back(*no_type);
path: tensorflow/core/graph/graph.cc