CVE-2022-29205: Tensorflow gpu Segfault Due To Missing Support Vulnerability

MODERATE
Advisory Identifier: GHSA-54ch-gjq5-4976
Share
CVSS 5.5
CWE-476 CWE-908
Published
Advisory Summary

CVE-2022-29205 is a MODERATE (CVSS 5.5) segfault due to missing support vulnerability (CWE-476: NULL Pointer Dereference) affecting Tensorflow gpu libraries in the PyPI ecosystem. The issue involves segfault due to missing support for quantized types. Remediation is available by upgrading affected packages to version 2.6.4, 2.7.2, 2.8.1.

CVE-2022-29205 at a Glance

CVE Identifier CVE-2022-29205
GHSA Identifier GHSA-54ch-gjq5-4976
Severity MODERATE
CVSS v3.1 Base Score 5.5
CWE Classification CWE-476: NULL Pointer Dereference
Affected Product Tensorflow gpu
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 5.5

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

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

How to Fix CVE-2022-29205

To remediate this vulnerability, upgrade all affected Tensorflow gpu 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-gpu fixed: 2.6.4 
pip install tensorflow-gpu>=2.6.4
tensorflow-gpu fixed: 2.7.2 
pip install tensorflow-gpu>=2.7.2
tensorflow fixed: 2.6.4 
pip install tensorflow>=2.6.4
tensorflow fixed: 2.7.2 
pip install tensorflow>=2.7.2
tensorflow fixed: 2.8.1 
pip install tensorflow>=2.8.1
tensorflow-cpu fixed: 2.6.4 
pip install tensorflow-cpu>=2.6.4
tensorflow-cpu fixed: 2.7.2 
pip install tensorflow-cpu>=2.7.2
tensorflow-cpu fixed: 2.8.1 
pip install tensorflow-cpu>=2.8.1
tensorflow-gpu fixed: 2.8.1 
pip install tensorflow-gpu>=2.8.1
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-gpu

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2022-29205, inspect your installed packages using pip:

pip show tensorflow-gpu

Analyze the terminal output to locate any version of Tensorflow gpu in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than 2.6.4), your application is affected.

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

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-476: NULL Pointer Dereference, where the product dereferences a pointer that it expects to be valid but is null. In Tensorflow gpu, 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 There is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types (added after migration to TF 2.x): ```python import numpy as np import tensorflow as tf tf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1]))) ``` In these scenarios, since the kernel is missing, a [`nullptr` value is passed](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482) to [`ParseDimensionValue`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320) for the `py_value` argument. Then, this is dereferenced, resulting in segfault. ### Patches We have patched the issue in GitHub commit [237822b59fc504dda2c564787f5d3ad9c4aa62d9](https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9). The fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Hong Jin from Singapore Management University.

CVE-2022-29205 Affected Tensorflow gpu Versions

9 component(s)
Fixed Versions:
2.6.42.7.22.8.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.6.4
2.6.4
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow
pypi/tensorflow
PyPI
< 2.6.4
2.6.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow
pypi/tensorflow
PyPI
≥ 2.8.0
< 2.8.1
2.8.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.6.4
2.6.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.7.0
< 2.7.2
2.7.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.8.0
< 2.8.1
2.8.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.8.0
< 2.8.1
2.8.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54ch-gjq5-4976
NVD — CVE-2022-29205 NVD
https://nvd.nist.gov/vuln/detail/CVE-2022-29205
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9
Tensorflow gpu Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow gpu Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320
Tensorflow gpu Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482
Tensorflow gpu Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4
Tensorflow gpu Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2
Tensorflow gpu Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1
Tensorflow gpu Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0

Frequently Asked Questions

What is CVE-2022-29205?
CVE-2022-29205 is a security vulnerability in Tensorflow gpu involving Segfault due to missing support for quantized types under CWE-476: NULL Pointer Dereference.
Which Tensorflow gpu versions are affected?
Affected versions include releases prior to 2.6.4, 2.7.2, 2.8.1 across affected packages: tensorflow-gpu, tensorflow, tensorflow-cpu.
What version fixes CVE-2022-29205?
Upgrading to 2.6.4, 2.7.2, 2.8.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow-gpu affected?
Yes, tensorflow-gpu is affected in releases prior to 2.6.4, 2.7.2, 2.8.1. Upgrade your dependency to 2.6.4, 2.7.2, 2.8.1 or later.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.6.4, 2.7.2, 2.8.1. Upgrade your dependency to 2.6.4, 2.7.2, 2.8.1 or later.
What is the CVSS score of CVE-2022-29205?
CVE-2022-29205 has a CVSS v3.1 base score of 5.5 (MODERATE) with vector string CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H.
What CWE is associated with CVE-2022-29205?
CVE-2022-29205 is classified under CWE-476: NULL Pointer Dereference (The product dereferences a pointer that it expects to be valid but is NULL.).
How can I check PyPI dependencies for CVE-2022-29205?
Run the dependency tree command: 'pip show tensorflow-gpu'. 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 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-54ch-gjq5-4976",
  "modified" : "2022-05-24T22:12:52Z",
  "published" : "2022-05-24T22:12:52Z",
  "aliases" : [ "CVE-2022-29205" ],
  "summary" : "Segfault due to missing support for quantized types",
  "details" : "### Impact\nThere is a potential for segfault / denial of service in TensorFlow by calling `tf.compat.v1.*` ops which don't yet have support for quantized types (added after migration to TF 2.x):\n\n```python\nimport numpy as np\nimport tensorflow as tf\n\ntf.compat.v1.placeholder_with_default(input=np.array([2]),shape=tf.constant(dtype=tf.qint8, value=np.array([1])))\n```\n\nIn these scenarios, since the kernel is missing, a [`nullptr` value is passed](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482) to [`ParseDimensionValue`](https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320) for the `py_value` argument. Then, this is dereferenced, resulting in segfault.\n\n### Patches\nWe have patched the issue in GitHub commit [237822b59fc504dda2c564787f5d3ad9c4aa62d9](https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9).\n\nThe fix will be included in TensorFlow 2.9.0. We will also cherrypick this commit on TensorFlow 2.8.1, TensorFlow 2.7.2, and TensorFlow 2.6.4, 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 Hong Jin from Singapore Management University.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:N/I:N/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.6.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.7.0"
      }, {
        "fixed" : "2.7.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.8.0"
      }, {
        "fixed" : "2.8.1"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.6.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.7.0"
      }, {
        "fixed" : "2.7.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-cpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.8.0"
      }, {
        "fixed" : "2.8.1"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "2.6.4"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.7.0"
      }, {
        "fixed" : "2.7.2"
      } ]
    } ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.8.0"
      }, {
        "fixed" : "2.8.1"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-54ch-gjq5-4976"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2022-29205"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/commit/237822b59fc504dda2c564787f5d3ad9c4aa62d9"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/tensorflow/tensorflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L296-L320"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/blob/f3b9bf4c3c0597563b289c0512e98d4ce81f886e/tensorflow/python/eager/pywrap_tfe_src.cc#L480-L482"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/releases/tag/v2.6.4"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/releases/tag/v2.7.2"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/releases/tag/v2.8.1"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/releases/tag/v2.9.0"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-476", "CWE-908" ],
    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2022-05-24T22:12:52Z",
    "nvd_published_at" : "2022-05-20T23:15:00Z"
  }
}