CVE-2020-15206: Tensorflow Denial of Service Vulnerability

HIGH
Advisory Identifier: GHSA-w5gh-2wr2-pm6g
Share
CVSS 9.0
CWE-20
Published
Advisory Summary

CVE-2020-15206 is a HIGH (CVSS 9.0) denial of service vulnerability (CWE-20: Improper Input Validation) affecting Tensorflow libraries in the PyPI ecosystem. The issue involves denial of service in tensorflow. Remediation is available by upgrading affected packages to version 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1.

CVE-2020-15206 at a Glance

CVE Identifier CVE-2020-15206
GHSA Identifier GHSA-w5gh-2wr2-pm6g
Severity HIGH
CVSS v3.1 Base Score 9.0
CWE Classification CWE-20: Improper Input Validation
Affected Product Tensorflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 9.0

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:C/C:H/I:H/A:H).

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

How to Fix CVE-2020-15206

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: 1.15.4 
pip install tensorflow>=1.15.4
tensorflow fixed: 2.0.3 
pip install tensorflow>=2.0.3
tensorflow fixed: 2.1.2 
pip install tensorflow>=2.1.2
tensorflow fixed: 2.2.1 
pip install tensorflow>=2.2.1
tensorflow fixed: 2.3.1 
pip install tensorflow>=2.3.1
tensorflow-cpu fixed: 1.15.4 
pip install tensorflow-cpu>=1.15.4
tensorflow-cpu fixed: 2.0.3 
pip install tensorflow-cpu>=2.0.3
tensorflow-cpu fixed: 2.1.2 
pip install tensorflow-cpu>=2.1.2
tensorflow-cpu fixed: 2.2.1 
pip install tensorflow-cpu>=2.2.1
tensorflow-cpu fixed: 2.3.1 
pip install tensorflow-cpu>=2.3.1
tensorflow-gpu fixed: 1.15.4 
pip install tensorflow-gpu>=1.15.4
tensorflow-gpu fixed: 2.0.3 
pip install tensorflow-gpu>=2.0.3
tensorflow-gpu fixed: 2.1.2 
pip install tensorflow-gpu>=2.1.2
tensorflow-gpu fixed: 2.2.1 
pip install tensorflow-gpu>=2.2.1
tensorflow-gpu fixed: 2.3.1 
pip install tensorflow-gpu>=2.3.1
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-2020-15206, 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 1.15.4), 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-20: Improper Input Validation, where the product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly. 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 Changing the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments. We have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode. ### Patches We have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d. We recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1. ### 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 Shuaike Dong, from Alipay Tian Qian Security Lab && Lab for Applied Security Research, CUHK.

CVE-2020-15206 Affected Tensorflow Versions

15 component(s)
Fixed Versions:
1.15.42.0.32.1.22.2.12.3.1
Product / Package Ecosystem Affected Versions Fixed Version
tensorflow
pypi/tensorflow
PyPI
< 1.15.4
1.15.4
tensorflow
pypi/tensorflow
PyPI
≥ 2.0.0
< 2.0.3
2.0.3
tensorflow
pypi/tensorflow
PyPI
≥ 2.1.0
< 2.1.2
2.1.2
tensorflow
pypi/tensorflow
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow
pypi/tensorflow
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
< 1.15.4
1.15.4
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.0.0
< 2.0.3
2.0.3
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.1.0
< 2.1.2
2.1.2
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow-cpu
pypi/tensorflow-cpu
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
< 1.15.4
1.15.4
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.0.0
< 2.0.3
2.0.3
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.1.0
< 2.1.2
2.1.2
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.2.0
< 2.2.1
All 1 versions
2.2.0
2.2.1
tensorflow-gpu
pypi/tensorflow-gpu
PyPI
≥ 2.3.0
< 2.3.1
All 1 versions
2.3.0
2.3.1

References

GitHub Advisory / Wiki ADVISORY
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g
NVD — CVE-2020-15206 NVD
https://nvd.nist.gov/vuln/detail/CVE-2020-15206
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/f760f88b4267d981e13f4b302c437ae800445968
Security Fix Commit FIX COMMIT
https://github.com/tensorflow/tensorflow/commit/fcfef195637c6e365577829c4d67681695956e7d
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-286.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-321.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-129.yaml
Tensorflow Source Repository REPOSITORY
https://github.com/tensorflow/tensorflow
Tensorflow Release RELEASE
https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
Tensorflow Security Information SECURITY
http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

Frequently Asked Questions

What is CVE-2020-15206?
CVE-2020-15206 is a security vulnerability in Tensorflow involving Denial of Service in Tensorflow under CWE-20: Improper Input Validation.
Which Tensorflow versions are affected?
Affected versions include releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 across affected packages: tensorflow, tensorflow-cpu, tensorflow-gpu.
What version fixes CVE-2020-15206?
Upgrading to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is tensorflow affected?
Yes, tensorflow is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.
Is tensorflow-cpu affected?
Yes, tensorflow-cpu is affected in releases prior to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1. Upgrade your dependency to 1.15.4, 2.0.3, 2.1.2, 2.2.1, 2.3.1 or later.
What is the CVSS score of CVE-2020-15206?
CVE-2020-15206 has a CVSS v3.1 base score of 9.0 (HIGH) with vector string CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H.
What CWE is associated with CVE-2020-15206?
CVE-2020-15206 is classified under CWE-20: Improper Input Validation (The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.).
How can I check PyPI dependencies for CVE-2020-15206?
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-w5gh-2wr2-pm6g",
  "modified" : "2024-10-28T14:54:48Z",
  "published" : "2020-09-25T18:28:40Z",
  "aliases" : [ "CVE-2020-15206" ],
  "summary" : "Denial of Service in Tensorflow",
  "details" : "### Impact\nChanging the TensorFlow's `SavedModel` protocol buffer and altering the name of required keys results in segfaults and data corruption while loading the model. This can cause a denial of service in products using `tensorflow-serving` or other inference-as-a-service installments.\n\nWe have added fixes to this in f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d (both going into TensorFlow 2.2.0 and 2.3.0 but not yet backported to earlier versions). However, this was not enough, as #41097 reports a different failure mode.\n\n### Patches\nWe have patched the issue in adf095206f25471e864a8e63a0f1caef53a0e3a6 and will release patch releases for all versions between 1.15 and 2.3. Patch releases for versions between 1.15 and 2.1 will also contain cherry-picks of f760f88b4267d981e13f4b302c437ae800445968 and fcfef195637c6e365577829c4d67681695956e7d.\n\nWe recommend users to upgrade to TensorFlow 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.\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 Shuaike Dong, from Alipay Tian Qian Security Lab && Lab for Applied Security Research, CUHK.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H"
  }, {
    "type" : "CVSS_V4",
    "score" : "CVSS:4.0/AV:N/AC:L/AT:P/PR:N/UI:N/VC:N/VI:N/VA:N/SC:H/SI:H/SA:H"
  } ],
  "affected" : [ {
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    },
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  }, {
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    "versions" : [ "2.3.0" ]
  }, {
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      "ecosystem" : "PyPI",
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    },
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    } ]
  }, {
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    },
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      } ]
    } ],
    "versions" : [ "2.2.0" ]
  }, {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "tensorflow-gpu"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "2.3.0"
      }, {
        "fixed" : "2.3.1"
      } ]
    } ],
    "versions" : [ "2.3.0" ]
  } ],
  "references" : [ {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g"
  }, {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2020-15206"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6"
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    "url" : "https://github.com/tensorflow/tensorflow/commit/fcfef195637c6e365577829c4d67681695956e7d"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-286.yaml"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-321.yaml"
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    "type" : "WEB",
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    "url" : "http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html"
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  "database_specific" : {
    "cwe_ids" : [ "CWE-20" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2020-09-25T17:41:59Z",
    "nvd_published_at" : "2020-09-25T19:15:00Z"
  }
}