CVE-2022-35952 (published 2022-09-16T20:15Z)

TensorFlow is an open source platform for machine learning. The `UnbatchGradOp` function takes an argument `id` that is assumed to be a scalar. A nonscalar `id` can trigger a `CHECK` failure and crash the program. It also requires its argument `batch_index` to contain three times the number of elements as indicated in its `batch_index.dim_size(0)`. An incorrect `batch_index` can trigger a `CHECK` failure and crash the program. We have patched the issue in GitHub commit 5f945fc6409a3c1e90d6970c9292f805f6e6ddf2. The fix will be included in TensorFlow 2.10.0. We will also cherrypick this commit on TensorFlow 2.9.1, TensorFlow 2.8.1, and TensorFlow 2.7.2, as these are also affected and still in supported range. There are no known workarounds for this issue.

CVSS v3 base score: 7.5, HIGH (CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H)

Weakness information:
cwe_id: CWE-617
cwe_name: Reachable Assertion
description: The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.
extended_description: 
            While assertion is good for catching logic errors and reducing the chances of reaching more serious vulnerability conditions, it can still lead to a denial of service.
            For example, if a server handles multiple simultaneous connections, and an assert() occurs in one single connection that causes all other connections to be dropped, this is a reachable assertion that leads to a denial of service.
         
         

Fix information:
repo_url: https://github.com/tensorflow/tensorflow
commit_details: repo_url: https://github.com/tensorflow/tensorflow
author: Sagun Bajra
author_date: 2022-07-14 10:16:55-07:00
msg: Fix security vulnerability with UnbatchGradKernel

PiperOrigin-RevId: 460992964
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: batch_kernels.cc
change_type: ModificationType.MODIFY
diff: @@ -885,8 +885,13 @@ class UnbatchGradResource : public ResourceBase {
     const Tensor& data_t = context->input(0);
     const Tensor& batch_index_t = context->input(1);
     const Tensor& grad_t = context->input(2);
+    const Tensor& batch_key_t = context->input(3);
 
     mutex_lock ml(mu_);
+    if (batch_key_t.NumElements() != 1) {
+      return errors::InvalidArgument("Expected `id` to be scalar. Received ",
+                                     batch_key_t.DebugString());
+    }
 
     const int64_t batch_key = context->input(3).scalar<int64_t>()();
     // Mark our tensor as available.
@@ -902,6 +907,11 @@ class UnbatchGradResource : public ResourceBase {
             "batch_index is empty while the tensor isn't.");
       }
       std::unordered_set<int64_t> missing_tensors;
+      if (batch_index_t.NumElements() != batch_index_t.dim_size(0) * 3) {
+        return errors::InvalidArgument(
+            "batch_index should contain ", batch_index_t.dim_size(0) * 3,
+            " elements. Received ", batch_index_t.NumElements());
+      }
       const auto batch_index =
           batch_index_t.shaped<int64_t, 2>({batch_index_t.dim_size(0), 3});
       for (int i = 0; i < batch_index_t.dim_size(0); ++i) {

programming_language: C++
filename: batch_ops_test.py
change_type: ModificationType.MODIFY
diff: @@ -20,7 +20,9 @@ import numpy as np
 
 from tensorflow.core.protobuf import config_pb2
 from tensorflow.python.eager import context
+from tensorflow.python.framework import constant_op
 from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import errors
 from tensorflow.python.framework import function
 from tensorflow.python.framework import ops
 from tensorflow.python.framework import test_util
@@ -30,6 +32,7 @@ from tensorflow.python.ops import batch_ops
 from tensorflow.python.ops import gen_batch_ops
 from tensorflow.python.ops import gen_functional_ops
 from tensorflow.python.ops import math_ops
+from tensorflow.python.ops import random_ops
 from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.ops import script_ops
 from tensorflow.python.ops import variables
@@ -557,6 +560,56 @@ class BatchOpsTest(test.TestCase):
       # The thread's call should hit the timeout, and thus get 0 results.
       self.assertEqual(len(thread_results), 0)
 
+  def testUnbatchGradInvalidId(self):
+    with self.assertRaises(errors.InvalidArgumentError):
+      self.evaluate(
+          gen_batch_ops.unbatch_grad(
+              original_input=constant_op.constant([1]),
+              batch_index=constant_op.constant([
+                  [0, 0, 0],
+              ], dtype=dtypes.int64),
+              grad=constant_op.constant([
+                  1,
+              ]),
+              id=constant_op.constant([
+                  1,
+                  1,
+              ], dtype=dtypes.int64)))
+
+  def testUnbatchGradInvalidBatchId(self):
+    with self.assertRaises(errors.InvalidArgumentError):
+      self.evaluate(
+          gen_batch_ops.unbatch_grad(
+              original_input=constant_op.constant([1]),
+              batch_index=constant_op.constant([
+                  [0, 0],
+              ], dtype=dtypes.int64),
+              grad=constant_op.constant([
+                  1,
+              ]),
+              id=constant_op.constant([
+                  1,
+              ], dtype=dtypes.int64)))
+
+  def testUnbatchGradInvalidArgs(self):
+    original_input = random_ops.random_uniform(
+        shape=(3, 1), dtype=dtypes.float64, maxval=None)
+    batch_index = random_ops.random_uniform(
+        shape=(3, 1), dtype=dtypes.int64, maxval=65536)
+    grad = random_ops.random_uniform(
+        shape=(3, 1), dtype=dtypes.float64, maxval=None)
+    batch_id = random_ops.random_uniform(
+        shape=(3, 1), dtype=dtypes.int64, maxval=65536)
+    with self.assertRaises(errors.InvalidArgumentError):
+      self.evaluate(
+          gen_batch_ops.unbatch_grad(
+              original_input=original_input,
+              batch_index=batch_index,
+              grad=grad,
+              id=batch_id,
+              container="",
+              shared_name="",
+              name=""))
 
 if __name__ == "__main__":
   test.main()

programming_language: Python