CVE-2022-21728: Tensorflow Out Of Bounds Read Vulnerability

HIGH
Advisory Identifier: GHSA-6gmv-pjp9-p8w8
Share
CVSS 8.1
CWE-125
Published
Advisory Summary

CVE-2022-21728 is a HIGH (CVSS 8.1) out of bounds read vulnerability (CWE-125: Out-of-bounds Read) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves out of bounds read in tensorflow. Remediation is available by upgrading affected packages to version 2.5.3, 2.6.3, 2.7.1.

CVE-2022-21728 at a Glance

CVE Identifier CVE-2022-21728
GHSA Identifier GHSA-6gmv-pjp9-p8w8
Severity HIGH
CVSS v3.1 Base Score 8.1
CWE Classification CWE-125: Out-of-bounds Read
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 8.1

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required Low (PR:L)
User Interaction None (UI:N)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity None (I:N)
Availability High (A:H)

How to Fix CVE-2022-21728

To remediate this vulnerability, upgrade all affected Tensorflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

tensorflow fixed: 2.5.3 
pip install tensorflow>=2.5.3
tensorflow fixed: 2.6.3 
pip install tensorflow>=2.6.3
tensorflow fixed: 2.7.1 
pip install tensorflow>=2.7.1
tensorflow-cpu fixed: 2.5.3 
pip install tensorflow-cpu>=2.5.3
tensorflow-cpu fixed: 2.6.3 
pip install tensorflow-cpu>=2.6.3
tensorflow-cpu fixed: 2.7.1 
pip install tensorflow-cpu>=2.7.1
tensorflow-gpu fixed: 2.5.3 
pip install tensorflow-gpu>=2.5.3
tensorflow-gpu fixed: 2.6.3 
pip install tensorflow-gpu>=2.6.3
tensorflow-gpu fixed: 2.7.1 
pip install tensorflow-gpu>=2.7.1
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show tensorflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2022-21728, inspect your installed packages using pip:

pip show tensorflow

Analyze the terminal output to locate any version of Tensorflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.5.3), your application is affected.

Note: The pip show tensorflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-125: Out-of-bounds Read, where the product reads data past the end, or before the beginning, of the intended buffer. In Tensorflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

### Impact The [implementation of shape inference for `ReverseSequence`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671) does not fully validate the value of `batch_dim` and can result in a heap OOB read: ```python import tensorflow as tf @tf.function def test(): y = tf.raw_ops.ReverseSequence( input = ['aaa','bbb'], seq_lengths = [1,1,1], seq_dim = -10, batch_dim = -10 ) return y test() ``` There is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values: ```cc const int32_t input_rank = c->Rank(input); if (batch_dim >= input_rank) { return errors::InvalidArgument( "batch_dim must be < input rank: ", batch_dim, " vs. ", input_rank); } // ... DimensionHandle batch_dim_dim = c->Dim(input, batch_dim); ``` Negative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then [the implementation of `Dim`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428) would access elements before the start of an array: ```cc DimensionHandle Dim(ShapeHandle s, int64_t idx) { if (!s.Handle() || s->rank_ == kUnknownRank) { return UnknownDim(); } return DimKnownRank(s, idx); } · static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) { CHECK_NE(s->rank_, kUnknownRank); if (idx < 0) { return s->dims_[s->dims_.size() + idx]; } return s->dims_[idx]; } ``` ### Patches We have patched the issue in GitHub commit [37c01fb5e25c3d80213060460196406c43d31995](https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995). 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](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions. ### Attribution This vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.

CVE-2022-21728 Affected Tensorflow Versions

9 component(s)
Fixed Versions:
2.5.32.6.32.7.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 2.5.3
2.5.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.5.3
2.5.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.5.3
2.5.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.6.0
< 2.6.3
2.6.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.7.0
< 2.7.1
All 1 versions
2.7.0
2.7.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-6gmv-pjp9-p8w8
NVD — CVE-2022-21728 NVD
https://nvd.nist.gov/vuln/detail/CVE-2022-21728
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2022-52.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2022-107.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671

Frequently Asked Questions

What is CVE-2022-21728?
CVE-2022-21728 is a security vulnerability in Tensorflow involving Out of bounds read in Tensorflow under CWE-125: Out-of-bounds Read.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.5.3, 2.6.3, 2.7.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2022-21728?
Upgrading to 2.5.3, 2.6.3, 2.7.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.5.3, 2.6.3, 2.7.1. Upgrade your dependency to 2.5.3, 2.6.3, 2.7.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.5.3, 2.6.3, 2.7.1. Upgrade your dependency to 2.5.3, 2.6.3, 2.7.1 or later.
What is the CVSS score of CVE-2022-21728?
CVE-2022-21728 has a CVSS v3.1 base score of 8.1 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:H.
What CWE is associated with CVE-2022-21728?
CVE-2022-21728 is classified under CWE-125: Out-of-bounds Read (The product reads data past the end, or before the beginning, of the intended buffer.).
How can I check PyPI dependencies for CVE-2022-21728?
Run the dependency tree command: 'pip show tensorflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
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  "id" : "GHSA-6gmv-pjp9-p8w8",
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  "aliases" : [ "CVE-2022-21728" ],
  "summary" : "Out of bounds read in Tensorflow",
  "details" : "### Impact \nThe [implementation of shape inference for `ReverseSequence`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/ops/array_ops.cc#L1636-L1671) does not fully validate the value of `batch_dim` and can result in a heap OOB read:\n\n```python\nimport tensorflow as tf\n\n@tf.function\ndef test():\n  y = tf.raw_ops.ReverseSequence(\n    input = ['aaa','bbb'],\n    seq_lengths = [1,1,1],\n    seq_dim = -10,\n    batch_dim = -10 )\n  return y\n    \ntest()\n```\n\nThere is a check to make sure the value of `batch_dim` does not go over the rank of the input, but there is no check for negative values:\n\n```cc\n  const int32_t input_rank = c->Rank(input);\n  if (batch_dim >= input_rank) {\n    return errors::InvalidArgument( \n        \"batch_dim must be < input rank: \", batch_dim, \" vs. \", input_rank);\n  }\n  // ...\n  \n  DimensionHandle batch_dim_dim = c->Dim(input, batch_dim);\n``` \n    \nNegative dimensions are allowed in some cases to mimic Python's negative indexing (i.e., indexing from the end of the array), however if the value is too negative then [the implementation of `Dim`](https://github.com/tensorflow/tensorflow/blob/5100e359aef5c8021f2e71c7b986420b85ce7b3d/tensorflow/core/framework/shape_inference.h#L415-L428) would access elements before the start of an array:\n\n```cc\n  DimensionHandle Dim(ShapeHandle s, int64_t idx) {\n    if (!s.Handle() || s->rank_ == kUnknownRank) {\n      return UnknownDim();\n    }\n    return DimKnownRank(s, idx);\n  } \n·\n  static DimensionHandle DimKnownRank(ShapeHandle s, int64_t idx) {\n    CHECK_NE(s->rank_, kUnknownRank);\n    if (idx < 0) {\n      return s->dims_[s->dims_.size() + idx];\n    }\n    return s->dims_[idx];\n  }\n```\n\n### Patches\nWe have patched the issue in GitHub commit [37c01fb5e25c3d80213060460196406c43d31995](https://github.com/tensorflow/tensorflow/commit/37c01fb5e25c3d80213060460196406c43d31995).\n\nThe 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.\n\n### For more information\nPlease consult [our security guide](https://github.com/tensorflow/tensorflow/blob/master/SECURITY.md) for more information regarding the security model and how to contact us with issues and questions.\n\n### Attribution\nThis vulnerability has been reported by Yu Tian of Qihoo 360 AIVul Team.",
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}