CVE-2021-29553: Tensorflow gpu Heap OOB Vulnerability

LOW
Advisory Identifier: GHSA-h9px-9vqg-222h
Share
CVSS 2.5
CWE-125
Published
Advisory Summary

CVE-2021-29553 is a LOW (CVSS 2.5) heap oob vulnerability (CWE-125: Out-of-bounds Read) affecting Tensorflow gpu libraries in the PyPI ecosystem. The issue involves heap oob in `quantizeanddequantizev3`. Remediation is available by upgrading affected packages to version 2.3.3, 2.4.2, 2.1.4, 2.2.3.

CVE-2021-29553 at a Glance

CVE Identifier CVE-2021-29553
GHSA Identifier GHSA-h9px-9vqg-222h
Severity LOW
CVSS v3.1 Base Score 2.5
CWE Classification CWE-125: Out-of-bounds Read
Affected Product Tensorflow gpu
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 2.5

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

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

How to Fix CVE-2021-29553

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: 2.3.3 
pip install tensorflow-gpu>=2.3.3
tensorflow fixed: 2.3.3 
pip install tensorflow>=2.3.3
tensorflow fixed: 2.4.2 
pip install tensorflow>=2.4.2
tensorflow-cpu fixed: 2.1.4 
pip install tensorflow-cpu>=2.1.4
tensorflow-cpu fixed: 2.2.3 
pip install tensorflow-cpu>=2.2.3
tensorflow-gpu fixed: 2.4.2 
pip install tensorflow-gpu>=2.4.2
tensorflow-cpu fixed: 2.3.3 
pip install tensorflow-cpu>=2.3.3
tensorflow-cpu fixed: 2.4.2 
pip install tensorflow-cpu>=2.4.2
tensorflow-gpu fixed: 2.1.4 
pip install tensorflow-gpu>=2.1.4
tensorflow fixed: 2.1.4 
pip install tensorflow>=2.1.4
tensorflow fixed: 2.2.3 
pip install tensorflow>=2.2.3
tensorflow-gpu fixed: 2.2.3 
pip install tensorflow-gpu>=2.2.3
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-2021-29553, 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 2.3.3), 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-125: Out-of-bounds Read, where the product reads data past the end, or before the beginning, of the intended buffer. 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 An attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`: ```python import tensorflow as tf tf.raw_ops.QuantizeAndDequantizeV3( input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30], signed_input=False, range_given=False, narrow_range=False, axis=3) ``` This is because the [implementation](https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument: ```cc const int depth = (axis_ == -1) ? 1 : input.dim_size(axis_); ``` ### Patches We have patched the issue in GitHub commit [99085e8ff02c3763a0ec2263e44daec416f6a387](https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387). The fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Aivul Team from Qihoo 360.

CVE-2021-29553 Affected Tensorflow gpu Versions

12 component(s)
Fixed Versions:
2.3.32.4.22.1.42.2.3
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.4.0
< 2.4.2
2.4.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.1.4
2.1.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.4.2
≥ 2.4.0
2.4.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.3.0
< 2.3.3
2.3.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.4.0
< 2.4.2
2.4.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.1.4
2.1.4
tensorflow
pypi/tensorflow
PyPI
< 2.1.4
2.1.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.2.0
< 2.2.3
2.2.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.3
2.2.3

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-h9px-9vqg-222h
NVD — CVE-2021-29553 NVD
https://nvd.nist.gov/vuln/detail/CVE-2021-29553
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387
Tensorflow gpu Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2021-481.yaml
Tensorflow gpu Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2021-679.yaml
Tensorflow gpu Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2021-190.yaml
Tensorflow gpu Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2021-29553?
CVE-2021-29553 is a security vulnerability in Tensorflow gpu involving Heap OOB in `QuantizeAndDequantizeV3` under CWE-125: Out-of-bounds Read.
Which Tensorflow gpu versions are affected?
Affected versions include releases prior to 2.3.3, 2.4.2, 2.1.4, 2.2.3 across affected packages: tensorflow-gpu, tensorflow, tensorflow-cpu.
What version fixes CVE-2021-29553?
Upgrading to 2.3.3, 2.4.2, 2.1.4, 2.2.3 (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 2.3.3, 2.4.2, 2.1.4, 2.2.3. Upgrade your dependency to 2.3.3, 2.4.2, 2.1.4, 2.2.3 or later.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.3.3, 2.4.2, 2.1.4, 2.2.3. Upgrade your dependency to 2.3.3, 2.4.2, 2.1.4, 2.2.3 or later.
What is the CVSS score of CVE-2021-29553?
CVE-2021-29553 has a CVSS v3.1 base score of 2.5 (LOW) with vector string CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2021-29553?
CVE-2021-29553 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-2021-29553?
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 
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  "id" : "GHSA-h9px-9vqg-222h",
  "modified" : "2024-10-31T20:51:10Z",
  "published" : "2021-05-21T14:23:51Z",
  "aliases" : [ "CVE-2021-29553" ],
  "summary" : "Heap OOB in `QuantizeAndDequantizeV3`",
  "details" : "### Impact\nAn attacker can read data outside of bounds of heap allocated buffer in `tf.raw_ops.QuantizeAndDequantizeV3`:\n\n```python\nimport tensorflow as tf\n\ntf.raw_ops.QuantizeAndDequantizeV3(\n  input=[2.5,2.5], input_min=[0,0], input_max=[1,1], num_bits=[30],\n  signed_input=False, range_given=False, narrow_range=False, axis=3)\n```   \n\nThis is because the [implementation](https://github.com/tensorflow/tensorflow/blob/11ff7f80667e6490d7b5174aa6bf5e01886e770f/tensorflow/core/kernels/quantize_and_dequantize_op.cc#L237) does not validate the value of user supplied `axis` attribute before using it to index in the array backing the `input` argument:\n\n```cc\nconst int depth = (axis_ == -1) ? 1 : input.dim_size(axis_);\n```\n\n### Patches\nWe have patched the issue in GitHub commit [99085e8ff02c3763a0ec2263e44daec416f6a387](https://github.com/tensorflow/tensorflow/commit/99085e8ff02c3763a0ec2263e44daec416f6a387).\n  \nThe fix will be included in TensorFlow 2.5.0. We will also cherrypick this commit on TensorFlow 2.4.2, TensorFlow 2.3.3, TensorFlow 2.2.3 and TensorFlow 2.1.4, 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 Aivul Team from Qihoo 360.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:L/AC:H/PR:L/UI:N/S:U/C:N/I:N/A:L"
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  }, {
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    "github_reviewed_at" : "2021-05-18T20:59:57Z",
    "nvd_published_at" : "2021-05-14T20:15:00Z"
  }
}