CVE-2020-15266: Tensorflow Float Cast Overflow Undefined Behavior Vulnerability

MODERATE
Advisory Identifier: GHSA-xwhf-g6j5-j5gc
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CVSS 3.7
CWE-119
Published
Advisory Summary

CVE-2020-15266 is a MODERATE (CVSS 3.7) float cast overflow undefined behavior vulnerability (CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves float cast overflow undefined behavior. Remediation is available by upgrading affected packages to version 2.4.0.

CVE-2020-15266 at a Glance

CVE Identifier CVE-2020-15266
GHSA Identifier GHSA-xwhf-g6j5-j5gc
Severity MODERATE
CVSS v3.1 Base Score 3.7
CWE Classification CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 3.7

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

Attack Vector Network (AV:N)
Attack Complexity High (AC:H)
Privileges Required None (PR:N)
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-2020-15266

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: 2.4.0 
pip install tensorflow>=2.4.0
tensorflow-cpu fixed: 2.4.0 
pip install tensorflow-cpu>=2.4.0
tensorflow-gpu fixed: 2.4.0 
pip install tensorflow-gpu>=2.4.0
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-2020-15266, 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 2.4.0), 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-119: Improper Restriction of Operations within the Bounds of a Memory Buffer, where the product performs operations on a memory buffer, but it reads from or writes to a memory location outside the buffer's intended boundary. this may result in read or write operations on unexpected memory locations that could be linked to other variables, data structures, or internal program data. 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 When the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault. ### Patches We have patched the issue in c0319231333f0f16e1cc75ec83660b01fedd4182 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved. ### 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 in #42129

CVE-2020-15266 Affected Tensorflow Versions

3 component(s)
Fixed Versions:
2.4.0
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 2.4.0
2.4.0
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 2.4.0
2.4.0
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 2.4.0
2.4.0

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-xwhf-g6j5-j5gc
NVD — CVE-2020-15266 NVD
https://nvd.nist.gov/vuln/detail/CVE-2020-15266
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/issues/42129
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-296.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-331.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-139.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow

Frequently Asked Questions

What is CVE-2020-15266?
CVE-2020-15266 is a security vulnerability in Tensorflow involving Float cast overflow undefined behavior under CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer.
Which Tensorflow versions are affected?
Affected versions include releases prior to 2.4.0 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2020-15266?
Upgrading to 2.4.0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 2.4.0. Upgrade your dependency to 2.4.0 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 2.4.0. Upgrade your dependency to 2.4.0 or later.
What is the CVSS score of CVE-2020-15266?
CVE-2020-15266 has a CVSS v3.1 base score of 3.7 (MODERATE) with vector string CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L.
What CWE is associated with CVE-2020-15266?
CVE-2020-15266 is classified under CWE-119: Improper Restriction of Operations within the Bounds of a Memory Buffer (The product performs operations on a memory buffer, but it reads from or writes to a memory location outside the buffer's intended boundary. This may result in read or write operations on unexpected memory locations that could be linked to other variables, data structures, or internal program data.).
How can I check PyPI dependencies for CVE-2020-15266?
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 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-xwhf-g6j5-j5gc",
  "modified" : "2024-10-28T14:46:31Z",
  "published" : "2020-11-13T17:18:29Z",
  "aliases" : [ "CVE-2020-15266" ],
  "summary" : "Float cast overflow undefined behavior",
  "details" : "### Impact\nWhen the `boxes` argument of `tf.image.crop_and_resize` has a very large value, the CPU kernel implementation receives it as a C++ `nan` floating point value. Attempting to operate on this is undefined behavior which later produces a segmentation fault.\n\n### Patches\n\nWe have patched the issue in c0319231333f0f16e1cc75ec83660b01fedd4182 and will release TensorFlow 2.4.0 containing the patch. TensorFlow nightly packages after this commit will also have the issue resolved.\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 in #42129",
  "severity" : [ {
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    "score" : "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:U/C:N/I:N/A:L"
  }, {
    "type" : "CVSS_V4",
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  } ],
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    },
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    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2020-15266"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/issues/42129"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/pull/42143/commits/3ade2efec2e90c6237de32a19680caaa3ebc2845"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-296.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-331.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-139.yaml"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/tensorflow/tensorflow"
  } ],
  "database_specific" : {
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    "severity" : "MODERATE",
    "github_reviewed" : true,
    "github_reviewed_at" : "2020-11-13T17:17:13Z",
    "nvd_published_at" : "2020-10-21T21:15:00Z"
  }
}