Vulnerability: Null pointer dereference in TensorFlow  ### Impact
When [building an XLA compilation cache](https://github.com/tensorflow/tensorflow/blob/274df9b02330b790aa8de1cee164b70f72b9b244/tensorflow/compiler/jit/xla_platform_info.cc#L43-L104), if default settings are used, TensorFlow triggers a null pointer dereference:

```cc 
  string allowed_gpus =
      flr->config_proto()->gpu_options().visible_device_list();
``` 
    
In the default scenario, all devices are allowed, so `flr->config_proto` is `nullptr`.
    
### Patches
We have patched the issue in GitHub commit [e21af685e1828f7ca65038307df5cc06de4479e8](https://github.com/tensorflow/tensorflow/commit/e21af685e1828f7ca65038307df5cc06de4479e8).
The fix will be included in TensorFlow 2.8.0. We will also cherrypick this commit on TensorFlow 2.7.1, TensorFlow 2.6.3, and TensorFlow 2.5.3, as these are also affected and still in supported range.

### 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-fpcp-9h7m-ffpx
CWE: CWE-476
Severity score: 5.3
Project: https://github.com/tensorflow/tensorflow
Published: 2022-02-09
File: tensorflow/compiler/jit/xla_platform_info.cc
Commit message: Fix Null-pointer dereference in BuildXlaCompilationCache

If ConfigProto is not used, then use the default settings which is to allow all devices.

PiperOrigin-RevId: 420391800
Change-Id: I88161ad7042990aef678e77b597a2fb2c8f815be
Commit author: Smit Hinsu

Vulnerable version (before fix):
 Status BuildXlaCompilationCache(DeviceBase* device, FunctionLibraryRuntime* flr,   client_options.set_intra_op_parallelism_threads(       device->tensorflow_cpu_worker_threads()->num_threads);    string allowed_gpus =       flr->config_proto()->gpu_options().visible_device_list();   TF_ASSIGN_OR_RETURN(absl::optional<std::set<int>> gpu_ids,                       ParseVisibleDeviceList(allowed_gpus));   client_options.set_allowed_devices(gpu_ids);    auto client = xla::ClientLibrary::GetOrCreateLocalClient(client_options);   if (!client.ok()) {

Fixed version (after fix):
 Status BuildXlaCompilationCache(DeviceBase* device, FunctionLibraryRuntime* flr,   client_options.set_intra_op_parallelism_threads(       device->tensorflow_cpu_worker_threads()->num_threads);    if (flr->config_proto()) {     string allowed_gpus =         flr->config_proto()->gpu_options().visible_device_list();     TF_ASSIGN_OR_RETURN(absl::optional<std::set<int>> gpu_ids,                         ParseVisibleDeviceList(allowed_gpus));     client_options.set_allowed_devices(gpu_ids);   }    auto client = xla::ClientLibrary::GetOrCreateLocalClient(client_options);   if (!client.ok()) {

Patch:
patch: @@ -82,11 +82,13 @@ Status BuildXlaCompilationCache(DeviceBase* device, FunctionLibraryRuntime* flr,
   client_options.set_intra_op_parallelism_threads(
       device->tensorflow_cpu_worker_threads()->num_threads);
 
-  string allowed_gpus =
-      flr->config_proto()->gpu_options().visible_device_list();
-  TF_ASSIGN_OR_RETURN(absl::optional<std::set<int>> gpu_ids,
-                      ParseVisibleDeviceList(allowed_gpus));
-  client_options.set_allowed_devices(gpu_ids);
+  if (flr->config_proto()) {
+    string allowed_gpus =
+        flr->config_proto()->gpu_options().visible_device_list();
+    TF_ASSIGN_OR_RETURN(absl::optional<std::set<int>> gpu_ids,
+                        ParseVisibleDeviceList(allowed_gpus));
+    client_options.set_allowed_devices(gpu_ids);
+  }
 
   auto client = xla::ClientLibrary::GetOrCreateLocalClient(client_options);
   if (!client.ok()) {
path: tensorflow/compiler/jit/xla_platform_info.cc