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Null pointer dereference in Grappler's `IsConstant`

Moderate severity GitHub Reviewed Published Feb 2, 2022 in tensorflow/tensorflow • Updated Feb 3, 2023

Package

pip tensorflow (pip)

Affected versions

< 2.5.3
>= 2.6.0, < 2.6.3
= 2.7.0

Patched versions

2.5.3
2.6.3
2.7.1
pip tensorflow-cpu (pip)
< 2.5.3
>= 2.6.0, < 2.6.3
= 2.7.0
2.5.3
2.6.3
2.7.1
pip tensorflow-gpu (pip)
< 2.5.3
>= 2.6.0, < 2.6.3
= 2.7.0
2.5.3
2.6.3
2.7.1

Description

Impact

Under certain scenarios, Grappler component of TensorFlow can trigger a null pointer dereference. There are 2 places where this can occur, for the same malicious alteration of a SavedModel file (fixing the first one would trigger the same dereference in the second place):

First, during constant folding, the GraphDef might not have the required nodes for the binary operation:

  NodeDef* mul_left_child = node_map_->GetNode(node->input(0));
  NodeDef* mul_right_child = node_map_->GetNode(node->input(1));
  // One child must be constant, and the second must be Conv op.
  const bool left_child_is_constant = IsReallyConstant(*mul_left_child);
  const bool right_child_is_constant = IsReallyConstant(*mul_right_child);

If a node is missing, the correposning mul_*child would be null, and the dereference in the subsequent line would be incorrect.

We have a similar issue during IsIdentityConsumingSwitch:

  NodeDef* input_node = graph.GetNode(tensor_id.node());
  return IsSwitch(*input_node);

Patches

We have patched the issue in GitHub commits 0a365c029e437be0349c31f8d4c9926b69fa3fa1 and 045deec1cbdebb27d817008ad5df94d96a08b1bf.

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

References

@mihaimaruseac mihaimaruseac published to tensorflow/tensorflow Feb 2, 2022
Reviewed Feb 4, 2022
Published by the National Vulnerability Database Feb 4, 2022
Published to the GitHub Advisory Database Feb 9, 2022
Last updated Feb 3, 2023

Severity

Moderate

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v3 base metrics

Attack vector
Network
Attack complexity
Low
Privileges required
Low
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

CVSS v3 base metrics

Attack vector: More severe the more the remote (logically and physically) an attacker can be in order to exploit the vulnerability.
Attack complexity: More severe for the least complex attacks.
Privileges required: More severe if no privileges are required.
User interaction: More severe when no user interaction is required.
Scope: More severe when a scope change occurs, e.g. one vulnerable component impacts resources in components beyond its security scope.
Confidentiality: More severe when loss of data confidentiality is highest, measuring the level of data access available to an unauthorized user.
Integrity: More severe when loss of data integrity is the highest, measuring the consequence of data modification possible by an unauthorized user.
Availability: More severe when the loss of impacted component availability is highest.
CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H

EPSS score

0.260%
(66th percentile)

Weaknesses

CVE ID

CVE-2022-23589

GHSA ID

GHSA-9px9-73fg-3fqp
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