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CVE-2020-15194

MEDIUM
Published 2020-09-25T18:40:46
Actions:

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CVSS Score

V3.1
5.3
/10
CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:L
Base Score Metrics
Exploitability: N/A Impact: N/A

EPSS Score

v2025.03.14
0.002
probability
of exploitation in the wild

There is a 0.2% chance that this vulnerability will be exploited in the wild within the next 30 days.

Updated: 2025-06-25
Exploit Probability
Percentile: 0.447
Higher than 44.7% of all CVEs

Attack Vector Metrics

Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
NONE
Scope
UNCHANGED

Impact Metrics

Confidentiality
NONE
Integrity
NONE
Availability
LOW

Description

In Tensorflow before versions 1.15.4, 2.0.3, 2.1.2, 2.2.1 and 2.3.1, the `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments. Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. The issue is patched in commit 390611e0d45c5793c7066110af37c8514e6a6c54, 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 MODERATE

Denial of Service in Tensorflow

GHSA-9mqp-7v2h-2382

Advisory Details

### Impact The `SparseFillEmptyRowsGrad` implementation has incomplete validation of the shapes of its arguments: https://github.com/tensorflow/tensorflow/blob/0e68f4d3295eb0281a517c3662f6698992b7b2cf/tensorflow/core/kernels/sparse_fill_empty_rows_op.cc#L235-L241 Although `reverse_index_map_t` and `grad_values_t` are accessed in a similar pattern, only `reverse_index_map_t` is validated to be of proper shape. Hence, malicious users can pass a bad `grad_values_t` to trigger an assertion failure in `vec`, causing denial of service in serving installations. ### Patches We have patched the issue in 390611e0d45c5793c7066110af37c8514e6a6c54 and will release a patch release for all affected versions. 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 is a variant of [GHSA-63xm-rx5p-xvqr](https://github.com/tensorflow/tensorflow/security/advisories/GHSA-63xm-rx5p-xvqr)

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

5.0

CVSS Vector

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

References

WEB https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9mqp-7v2h-2382
ADVISORY https://nvd.nist.gov/vuln/detail/CVE-2020-15194
WEB https://github.com/tensorflow/tensorflow/commit/390611e0d45c5793c7066110af37c8514e6a6c54
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-cpu/PYSEC-2020-274.yaml
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow-gpu/PYSEC-2020-309.yaml
WEB https://github.com/pypa/advisory-database/tree/main/vulns/tensorflow/PYSEC-2020-117.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/commit/390611e0d45c5793c7066110af37c8514e6a6c54
https://github.com/tensorflow/tensorflow/security/advisories/GHSA-9mqp-7v2h-2382
http://lists.opensuse.org/opensuse-security-announce/2020-10/msg00065.html
Published: 2020-09-25T18:40:46
Last Modified: 2024-08-04T13:08:22.713Z
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