CVE-2020-26271 (published 2020-12-10T22:15Z)

In affected versions of TensorFlow under certain cases, loading a saved model can result in accessing uninitialized memory while building the computation graph. The MakeEdge function 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. 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. This is fixed in versions 1.15.5, 2.0.4, 2.1.3, 2.2.2, 2.3.2, and 2.4.0.

Severity: LOW
CVSS v2 base score: 2.1 (AV:L/AC:L/Au:N/C:P/I:N/A:N)
CVSS v3 base score: 3.3, LOW (CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N)

Weakness information:
cwe_id: CWE-125
cwe_name: Out-of-bounds Read
description: The product reads data past the end, or before the beginning, of the intended buffer.
extended_description: 
            
            
             
			 
         
         
cwe_id: CWE-908
cwe_name: Use of Uninitialized Resource
description: The product uses or accesses a resource that has not been initialized.
extended_description: When a resource has not been properly initialized, the product may behave unexpectedly. This may lead to a crash or invalid memory access, but the consequences vary depending on the type of resource and how it is used within the product.
         

Fix information:
repo_url: https://github.com/tensorflow/tensorflow
commit_details: repo_url: https://github.com/tensorflow/tensorflow
author: Mihai Maruseac
author_date: 2020-12-08 09:31:57-08:00
msg: 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
repository: repo_url: https://github.com/tensorflow/tensorflow
repo_name: tensorflow/tensorflow
description: An Open Source Machine Learning Framework for Everyone
repo_language: C++
owner: tensorflow
file_changes: filename: graph_constructor.cc
change_type: ModificationType.MODIFY
diff: @@ -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)) {

programming_language: C++