CVE-2023-25666: Tensorflow TensorFlow Has Floating Point Exception Vulnerability

HIGH
Advisory Identifier: GHSA-f637-vh3r-vfh2
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CVSS 7.5
CWE-697
Published
Advisory Summary

CVE-2023-25666 is a HIGH (CVSS 7.5) tensorflow has floating point exception vulnerability (CWE-697: Incorrect Comparison) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves tensorflow has floating point exception in audiospectrogram. Remediation is available by upgrading affected packages to version 2.11.1.

CVE-2023-25666 at a Glance

CVE Identifier CVE-2023-25666
GHSA Identifier GHSA-f637-vh3r-vfh2
Severity HIGH
CVSS v3.1 Base Score 7.5
CWE Classification CWE-697: Incorrect Comparison
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.5

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

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
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-2023-25666

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: 2.11.1 
pip install tensorflow>=2.11.1
tensorflow-cpu fixed: 2.11.1 
pip install tensorflow-cpu>=2.11.1
tensorflow-gpu fixed: 2.11.1 
pip install tensorflow-gpu>=2.11.1
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-2023-25666, 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 2.11.1), 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-697: Incorrect Comparison, where the product compares two entities in a security-relevant context, but the comparison is incorrect. 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 version:2.11.0 //core/ops/audio_ops.cc:70 Status SpectrogramShapeFn(InferenceContext* c) { ShapeHandle input; TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 2, &input)); int32_t window_size; TF_RETURN_IF_ERROR(c->GetAttr("window_size", &window_size)); int32_t stride; TF_RETURN_IF_ERROR(c->GetAttr("stride", &stride)); .....[1] DimensionHandle input_length = c->Dim(input, 0); DimensionHandle input_channels = c->Dim(input, 1); DimensionHandle output_length; if (!c->ValueKnown(input_length)) { output_length = c->UnknownDim(); } else { const int64_t input_length_value = c->Value(input_length); const int64_t length_minus_window = (input_length_value - window_size); int64_t output_length_value; if (length_minus_window < 0) { output_length_value = 0; } else { output_length_value = 1 + (length_minus_window / stride); .....[2] } output_length = c->MakeDim(output_length_value); } Get the value of stride at [1], and the used at [2] ```python import tensorflow as tf para = {'input': tf.constant([[14.], [24.]], dtype=tf.float32), 'window_size': 1, 'stride': 0, 'magnitude_squared': False} func = tf.raw_ops.AudioSpectrogram @tf.function(jit_compile=True) def fuzz_jit(): y = func(**para) return y fuzz_jit() ``` ### Patches We have patched the issue in GitHub commit [d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14](https://github.com/tensorflow/tensorflow/commit/d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14). The fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1 ### 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 r3pwnx

CVE-2023-25666 Affected Tensorflow Versions

3 component(s)
Fixed Versions:
2.11.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 2.11.1
2.11.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.11.1
2.11.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.11.1
2.11.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-f637-vh3r-vfh2
NVD — CVE-2023-25666 NVD
https://nvd.nist.gov/vuln/detail/CVE-2023-25666
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2023-25666?
CVE-2023-25666 is a security vulnerability in Tensorflow involving TensorFlow has Floating Point Exception in AudioSpectrogram under CWE-697: Incorrect Comparison.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.11.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2023-25666?
Upgrading to 2.11.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.11.1. Upgrade your dependency to 2.11.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.11.1. Upgrade your dependency to 2.11.1 or later.
What is the CVSS score of CVE-2023-25666?
CVE-2023-25666 has a CVSS v3.1 base score of 7.5 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H.
What CWE is associated with CVE-2023-25666?
CVE-2023-25666 is classified under CWE-697: Incorrect Comparison (The product compares two entities in a security-relevant context, but the comparison is incorrect.).
How can I check PyPI dependencies for CVE-2023-25666?
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-f637-vh3r-vfh2",
  "modified" : "2023-03-27T22:01:33Z",
  "published" : "2023-03-24T21:57:18Z",
  "aliases" : [ "CVE-2023-25666" ],
  "summary" : "TensorFlow has Floating Point Exception in AudioSpectrogram ",
  "details" : "### Impact\nversion:2.11.0 //core/ops/audio_ops.cc:70\n\nStatus SpectrogramShapeFn(InferenceContext* c) { ShapeHandle input; TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 2, &input)); int32_t window_size; TF_RETURN_IF_ERROR(c->GetAttr(\"window_size\", &window_size)); int32_t stride; TF_RETURN_IF_ERROR(c->GetAttr(\"stride\", &stride)); .....[1]\n\nDimensionHandle input_length = c->Dim(input, 0); DimensionHandle input_channels = c->Dim(input, 1);\n\nDimensionHandle output_length; if (!c->ValueKnown(input_length)) { output_length = c->UnknownDim(); } else { const int64_t input_length_value = c->Value(input_length); const int64_t length_minus_window = (input_length_value - window_size); int64_t output_length_value; if (length_minus_window < 0) { output_length_value = 0; } else { output_length_value = 1 + (length_minus_window / stride); .....[2] } output_length = c->MakeDim(output_length_value); }\n\nGet the value of stride at [1], and the used at [2]\n```python\nimport tensorflow as tf\n\npara = {'input': tf.constant([[14.], [24.]], dtype=tf.float32), 'window_size': 1, 'stride': 0, 'magnitude_squared': False}\nfunc = tf.raw_ops.AudioSpectrogram\n\n@tf.function(jit_compile=True)\ndef fuzz_jit():\n   y = func(**para)\n   return y\n\nfuzz_jit()\n```\n\n### Patches\nWe have patched the issue in GitHub commit [d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14](https://github.com/tensorflow/tensorflow/commit/d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14).\n\nThe fix will be included in TensorFlow 2.12.0. We will also cherrypick this commit on TensorFlow 2.11.1\n\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\n### Attribution\nThis vulnerability has been reported by r3pwnx\n",
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    "url" : "https://github.com/tensorflow/tensorflow/commit/d0d4e779da0d0f56499c6fa5ba09f0a576cc6b14"
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    "url" : "https://github.com/tensorflow/tensorflow"
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  "database_specific" : {
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