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CVE-2020-15206

CRITICAL
Published 2020-09-25T18:45:51
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CVSS Score

V3.1
9.0
/10
CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.005
probability
of exploitation in the wild

There is a 0.5% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.636
Higher than 63.6% of all CVEs

Attack Vector Metrics

Attack Vector
NETWORK
Attack Complexity
HIGH
Privileges Required
NONE
User Interaction
NONE
Scope
CHANGED

Impact Metrics

Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH

Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, 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. Fixed were added in commits 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. The issue is patched in commit adf095206f25471e864a8e63a0f1caef53a0e3a6, and is released in TensorFlow versions 1.15.4, 2.0.3, 2.1.2, 2.2.1, or 2.3.1.

Available Exploits

No exploits available for this CVE.

Related News

No news articles found for this CVE.

Affected Products

tensorflow

tensorflow

Affected Versions:

< 1.15.4 >= 2.0.0, < 2.0.3 >= 2.1.0, < 2.1.2 >= 2.2.0, < 2.2.1 >= 2.3.0, < 2.3.1

GitHub Security Advisories

Community-driven vulnerability intelligence from GitHub

✓ GitHub Reviewed HIGH

Denial of Service in Tensorflow

GHSA-w5gh-2wr2-pm6g

Advisory Details

### 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.

Affected Packages

PyPI tensorflow
ECOSYSTEM: ≥0 <1.15.4
PyPI tensorflow
ECOSYSTEM: ≥2.0.0 <2.0.3
PyPI tensorflow
ECOSYSTEM: ≥2.1.0 <2.1.2
PyPI tensorflow
ECOSYSTEM: ≥2.2.0 <2.2.1
PyPI tensorflow
ECOSYSTEM: ≥2.3.0 <2.3.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥0 <1.15.4
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.0.0 <2.0.3
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.1.0 <2.1.2
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.2.0 <2.2.1
PyPI tensorflow-cpu
ECOSYSTEM: ≥2.3.0 <2.3.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥0 <1.15.4
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.0.0 <2.0.3
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.1.0 <2.1.2
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.2.0 <2.2.1
PyPI tensorflow-gpu
ECOSYSTEM: ≥2.3.0 <2.3.1

CVSS Scoring

CVSS Score

7.5

CVSS Vector

CVSS:3.1/AV:N/AC:H/PR:N/UI:N/S:C/C:H/I:H/A:H

References

WEB https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g
ADVISORY https://nvd.nist.gov/vuln/detail/CVE-2020-15206
WEB https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6
WEB https://github.com/tensorflow/tensorflow/commit/f760f88b4267d981e13f4b302c437ae800445968
WEB https://github.com/tensorflow/tensorflow/commit/fcfef195637c6e365577829c4d67681695956e7d
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-286.yaml
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-321.yaml
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-129.yaml
PACKAGE https://github.com/tensorflow/tensorflow
WEB https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
WEB http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html

Advisory provided by GitHub Security Advisory Database. Published: September 25, 2020, Modified: October 28, 2024

References

https://github.com/tensorflow/tensorflow/releases/tag/v2.3.1
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-w5gh-2wr2-pm6g
https://github.com/tensorflow/tensorflow/commit/adf095206f25471e864a8e63a0f1caef53a0e3a6
http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
Published: 2020-09-25T18:45:51
Last Modified: 2024-08-04T13:08:22.955Z
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